Remote Sensing in Soil Science

Developments in Soil Science 15 REMOTE SENSING IN SOIL SCIENCE Further Titles in this Series 1. I. VALETON BAUXITES ...

Author: M.A. Mulders

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Developments in Soil Science 15

REMOTE SENSING IN SOIL SCIENCE

Further Titles in this Series 1. I. VALETON BAUXITES 2. I A H R FUNDAMENTALS O F TRANSPORT PHENOMENA IN POROUS MEDIA

3. F.E. A L L I S O N SOIL ORGANIC MATTER AND ITS ROLE IN CROP PRODUCTION 4. R. W. SIMONSON (Editor) NON-AGRICULTURAL APPLICATIONS O F SOIL SURVEYS

5 A . G.H. B O L T and M.G.M. B R U G G E N W E R T (Editors) SOIL CHEMISTRY. A. BASIC ELEMENTS 5B. G.H. B O L T (Editor) SOIL CHEMISTRY. B. PHYSICO-CHEMICAL MODELS 6. H.E. D R E G N E SOILS O F ARID REGIONS

7. H. A U B E R T and M. P I N T A TRACE ELEMENTS IN SOILS

8. M. S C H N I T Z E R and S. U. K H A N (Editors) SOIL ORGANIC MATTER

9. B.K.G. T H E N G FORMATION AND PROPERTIES OF CLAY-POLYMER COMPLEXES 10. D. Z A C H A R SOIL EROSION

11A. L.P. WILDING, N.E. SMECK and G.F. H A L L (Editors) PEDOGENESIS AND SOIL TAXONOMY. I. CONCEPTS AND INTERACTIONS 1 IB. L.P. WILDING, N.E. SMECK and G.F. H A L L (Editors) PEDOGENESIS AND SOIL TAXONOMY. 11. THE SOIL ORDERS

12. E.B.A. BISDOM and J. DUCLOUX (Editors) SUBMICROSCOPIC STUDIES O F SOILS 13. P. K O O R E V A A R , G . MENELIK and C. DIRKSEN ELEMENTS O F SOIL PHYSICS 1 4 . G.S. CAMPBELL SOIL PHYSICS WITH BASIC

--

TRANSPORT MODELS FOR SOIL-PLANT

SYSTEMS

Developments in Soil Science 15

REMOTE SENSING IN SOIL SCIENCE M.A. MULDERS Department of Soil Science and Geology, Agricultural University of Wageningen, P.O. Box 37, Wageningen, The Netherlands

ELSEVIER

-

Amsterdam

- Oxford - New

York -Tokyo 1987

ELSEVIER SCIENCE PUBLISHERS B.V. Sara Burgerhartstraat 25 P.O. Box 211,1000 AE Amsterdam, T h e Netherlands

Distribution for the United States and Canada: ELSEVIER SCIENCE PUBLISHING COMPANY INC. 52, Vanderbilt Avenue New York, NY 10017,U.S.A.

Lihrary of Cnngcss CataloginginPublication Data

Mulders , Michel Adrianus, 1941Renote s e n s i n g i n s o i l s c i e n c e . (Developments i n s o i l s c i e t x e ; 1:) I n c l u d e s b : i i i c g r a p h i e s and i n d e x . 1. S o i l science--Renote s e n s i n g . I . T i t l e . 11. S e r i e s . f5C. .135.Md 19:'i i 31.4 'CLi '7 57-54,3 ISBN 0-444-4,713-X

ISBN 0-444-42783-X (Vol. 15) ISBN 0-444-40882-7 (Series) 0 Elsevier Science Publishers B.V., 1987

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form of by any means, electronic, mechanical, photocopying, recording o r otherwise, without the prior written permission of the publisher, Elsevier Science Publishers B.V./Science & Technology Division, P.O. Box 330,1000 AH Amsterdam, T h e Netherlands. Special regulations for readers in t h e USA - This publication has been registered with the Copyright Clearance Center Inc. (CCC), Salem, Massachusetts. Information can be obtained from the CCC about conditions under which photocopies of parts of this publication may be made in the USA. All other copyright questions, including photocopying outside of the USA, should be referred to the publisher. Printed in T h e Netherlands

V PREFACE

The soil scientist is involved in the study of environment since the environmental conditions have

to be evaluated for their impact on soil

formation. However, it may be that the impact of past environmental conditions has

been

of

even more

importance on soil morphology

than the present

conditions. Therefore geo- and morphogenesis form also part of his field of study. His subject of interest is often not visible. In areas covered by vegetation, he has to use combinations of aspects such as natural vegetation or land use and relief to find a clue to the geographical extension of soil bodies. The combinations are not f i x e d but depend on the type of landscape. For example, vegetation may be the effect of human interference and may not at all offer a clue to soil condition. Scientists involved in geographical distribution of soil, especially in medium and small scale surveys, obtain much profit of remote sensing techniques because they offer an overview over large areas and make the study of various landscape elements individually as well as their interrelationship possible. During the past decade, remote sensing techniques developed rather fast. Therefore, it is possible that a soil surveyor becomes old-fashioned by not knowing the potential use of modern techniques. This book is dealing with remote sensing techniques and their application in the field of soil science. It may be used by students and scientists in soil science, geography, geology, hydrology, ecology, agriculture and civil engineering. Basic knowledge of soils, geomorphology, geology and physics will provide useful background. The reader is stepwise introduced to remote sensing by the following subjects:

-

basic physics concerning the interaction of electromagnetic radiation with matter (chapter 2);

-

spectral data of soils, rocks and plants (chapter 3) as a transition of chapter 2 to chapters 9, 10 and 11;

-

technical aspects (chapters 4 , 5, 6 and 7 ) ; interpretation of remote sensing data (chapters 8, 9, 11, 12 and 13).

A guide for reading is presented in the following scheme:

VI Chapters

Subject

solar radiation

Physical aspects

i n t e r a c t i o n processes

Future prospects

The p u r p o s e of

14

t h e hook i s t o p r e s e n t ,

b e s i d e s remote s e n s i n g t e c h n i q u e s and

i n t e r p r e t a t i o n methods a s w e l l a s most

application,

of

the basic parameters

u s a b l e f o r m o d e l l i n g of t h e i n t e r a c t i o n .

ACKNOIJLEDCEHENTS The wide r a n g e of t e c h n i q u e s and a p p l i c a t i o n s made i t n e c e s s a r y t o d i s c u s s v a r i o u s t o p i c s w i t h s p e c i a l i s t s . Thanks a r e due f o r d i s c u s s i o n on p a r t s o f t h e m a n u s c r i p t t o s e v e r a l Dutch c o l l e a g e s . The a u t h o r f e e l s g r e a t l y i n d e h t e d t o D r . Loedeman, G.F.

Ir. E.P.IJ.

Epema and Ir. R .

Attema,

Ir. J . T .

s c i e n c e of

Schurer,

I r . L. Routen, 14.

Ir. J . H .

t e n Rerge, D r s .

Jordens f o r t h e i r suggestive c r i t i c i s m .

Acknowledgement i s made t o c o - o p e r a t o r s grassland

K.

van d e r Veer, D r . 1 r .

of

t h e Department of

f i e l d c r o p s and

t h e A g r i c u l t u r a l U n i v e r s i t y Wageningen f o r t h e v a l u a b l e

i n f o r m a t i o n , t h e y p r o v i d e d on s o i l c o n d i t i o n and f i e l d c r o p s i n t h e i r e x p e r i mental

fields.

Rennema ( -t ) project.

The

However my g r e a t e s t d e b t of

g r a t i t u d e is t o Prof.

Th.

Ir.

linguistic

abilities

of

Drs.

J.M.

de

Zwart

have

van Hummel-Mom

and Mw.

M.H.

van Eldik-v.

M i l t e n h u r g of

been

O.D.

t h e m a n u s c r i p t and t o Mr. P.G.M.

Versteep,, Hr. G .

of

I ' m indebted t h e Depart-

ment of s o i l s c i e n c e and geology of t h e A g r i c u l t u r a l U n i v e r s i t y TJageningen type-writing

J.

f o r h i s encouragement and i n i t i a t i v e f o r s t a r t i n g up t h i s book-

c o n s i d e r a b l e v a l u e f o r a c o r r e c t p r e s e n t a t i o n of t h e E n g l i s h t e x t . t o Mw.

Dr.

for

Ruurman and Hr.

J e r o n i m u s of t h e s a n e d e p a r t m e n t f o r p e r f o r m i n g t h e d r a w i n g s .

VII

CONTENTS PREFACE ACKNOWLEDGEMENTS 1. INTRODUCTION 1.1. Remote sensing 1.2. Concept of soil 1.3. Soil mapping 1.4. Remote sensing in soil science 1.5. Conclusions 1.6. References 1.7. Additional reading

PAGES

2.

12-54 12-16 16-18 18 19-22

3.

4.

INTERACTION OF ELECTROMAGNETIC RADIATION WITH MATTER 2.1. The nature of electromagnetic radiation 2.2. Radiation laws 2.3. Solar irriadiance and earth emittance 2.4. Concepts of matter 2.5. Atomic-molecular effects on the interaction process; polarization, dielectric constant, refractive index and absorption factor 2.6. Macroscopic effects on the interaction process; a description using the wave model of EMR 2.7. Thermal properties 2.8. Atmospheric effect on EMR 2.9. Energy balance 2.10. Spectral reflectance 2.11. Conclusions 2.12. References 2.13. Additional reading

1-11 1-4 4-5 5-8 8-10 11 11 11

22-26 26-36 36-40 40-45 45-48 48-50 50-52 52-53 53-54

DATA ON INTERACTION OF SHORT WAVE RADIATION WITH NATURAL OBJECTS 3.1. Interaction of short wave radiation with minerals and rocks Spectral reflectance Spectral emissivity 3.2. Interaction of short wave radiation with soils Spectral reflectance Thermal data 3.3. Interaction of short wave radiation with plants Spectral reflectance Thermal properties 3.4. Implications for remote sensing 3.5. Conclusions 3.6. References 3.7. Additional reading

55-60 55-58 58-60 60-75 60-69 69-75 75-86 75-83 83-86 86-87 87-88 88-90 90-91

DETECTION OF ELECTROMAGNETIC RADIATION 4.1. Human vision 4.2. Photographic techniques 4.3. Non-photographic techniques 4.4. Remote sensing from various platforms 4.5. The nature of remote sensing data 4.6. Ground-investigations 4.7. Conclusions

93-124 93-101 101-109 109-112 112-1 15 115-117 117-121 12 1-1 22

55-91

VIII 4.8. 4.9.

References Additional reading

122-123 123-124

5.

PROCESSING OF REMOTE SENSING DATA AND AUTOMATED CLASSIFICATION 5.1. T e c h n i c a l a s p e c t s i n p r o c e s s i n g of p h o t o g r a p h i c imagery 5.2. P r o c e s s i n g of d i g i t a l d a t a 5.3. Information e x t r a c t i o n process 5.4. Automated c l a s s i f i c a t i o n 5.5. Geometrical a s p e c t s 5.6. Conclusions 5.7. References 5.8. Additional reading

125-140 125-131 131-1 35 135-136 136-138 138 138- 1 3 9 139-140 140

6.

IMAGE CHARACTERISTICS R e s o l u t i o n and scale 6.1. Grey t o n e , c o n t r a s t and c o l o u r 6.2. Airphotos 6.3. Images d e r i v e d from l i n e - s c a n n i n g d e v i c e s 6.4. Image-enhancement 6.5. Conclusions 6.6. References 6.7. Additional reading 6.8.

1 4 1-1 5 4 141-1 4 3 143-144 144-148 148-151 151-153 153-1 5 4 154 154

7.

AERIAL PHOTOGRAPHY 7.1. General a s p e c t s 7.2. Stereoscopy 7.3 Aerial mapping cameras 7.4. Photomosaics, o r t h o p h o t o g r a p h s and s t e r e o t r i p l e t s 7.5. Requirements f o r a e r i a l s u r v e y 7.6. True c o l o u r a e r i a l photography 7.7. I n f r a r e d a e r i a l photography 7.8. M u l t i s p e c t r a l a e r i a l photography 7.9. U l t r a v i o l e t photography 7.10. Conclusions 7.11. R e f e r e n c e s 7.12. A d d i t i o n a l r e a d i n g

155- 1 8 0 155-16 2 162-167 167-171 172 172-174 174-1 76 176-177 177-1 7 8 178 178- 179 179-180 180

8.

GENERAL DIRECTIONS FOR PHYSIOGRAPHIC INTERPRETATION OF REMOTE SENSING IMAGERY I N S O I L MAPPING 8.1. Methods of i m a g e - i n t e r p r e t a t i o n 8.2. Landtypes 8.3. R e l i e f , s l o p e and s i t e 8.4. Natural drainage patterns 8.5. Natural vegetation 8.6. Land u s e , c r o p s and p a r c e l l i n g 8.7. Drainage c o n d i t i o n 8.8. Other a s p e c t s 8.9. Conclusions 8.10. R e f e r e n c e s 8.11. A d d i t i o n a l r e a d i n g

ixi-zin 182-186 186-18R 188- 192 192-200 2nn-20 3 20 3- 20 5 20 5 206-208 209 209 210

INTERPRETATION OF AIRPHOTOS FOR SOIL MAPPING AND LAND EVALUATIOfi 9.1. I n t e r p r e t a t i o n of black-and-white a i r p h o t o s 9.2. The legend of t h e a i r p h o t o - i n t e r p r e t a t i o n map From a i r p h o t o - i n t e r p r e t a t i o n map.to s o i l map 9.3.

211-245 211-219 219-222 223-2 26

9.

IX 9.4. 9.5. 9.6. 9.7. 9.8. 9.9. 9.10. 9.11. 9.12.

Land evaluation and planning of field survey Interpretation of true COlOUK airphotos Interpretation of black-and-white Infrared airphotos Interpretation of false colour airphotos Application of multispectral photography Interpretation of sequential aerial photography Conclusions References Additional reading

10. AIRBORNE LINE-SCANNING IN THE 0.3 - 8 um ZONE 10.1. Airborne line-scanners 10.2. Detection in the Ultraviolet 10.3. Detection in the Visible zone and near Infrared 10.4. Detection in the mid Infrared 10.5. Conclusions 10.6. References 10.7. Additional reading 11. REMOTE 11.1 11.2. 11.3. 11.4. 11.5. 11.6. 11.7. 11.8. 11.9.

SENSIITG FROM SPACE IN THE 0.3 - 3 pm ZONE Manned space missions and unmanned satellites Technical aspects Landsat Annotations Landsat MSS imagery Processing and interpretation of Landsat MSS data. Interpretation of Thematic Mapper (TM) data Application Conclusions and comments References Additional reading

226-235 235 235 236-239 239-240 240-24 1 241-242 24 2-24 3 243-245 246-255 246-248 248-249 249-253 253 253 254 254-255 256-287 256-258 258-264 264-266 266-281 28 1-284 284 284-285 285-287 28 7

12. THERMAL INFRARED LINE-SCANNING AND RADIOMETRY IN THE INFRARED

AND MICRC-WAVE ZONES 12.1. Airborne Infrared line-scanners and Infrared imagers 12.2. Satellite programs 12.3. Characteristics of airborne thermal Infrared imagery 12.4. Thermal models 12.5. Interpretation of thermal data 12.6. Application of thermal Infrared line scanning. 12.7. Non-imaging sensing in the Infrared and passive Microwave sensing 12.8. Conclusions 12.9. References 12.10 Additional reading 13. ACTIVE 13.1. 13.2. 13.3.

13.4. 13.5. 13.6.

SENSOR SYSTEMS Laser systems Radar systems Interaction of Microwaves with objects at the earth surface Surface roughness Slope/orientation Dielectric properties Determination of soil moisture Ground penetrating radar Vegetation backscattering Radar image characteristics

288-314 289 289-291 291-295 295-300 300-305 305-306 306-309 309 309-31 1 311-313 314-354 3 14-3 15 315-323 323-332 323-324 325 325-329 329-332 332- 3 34 334-33 5 3 35- 339

X 13.7. 13.8 13.9. 13.10 13.11 13.12

Interpretation of radar imagery Remote sensing with radio waves Applications and future developments Conclusions References Additional reading

339-346 347-348 348-350 350-351 351-353 353-354

1 4 . IMPLICATIONS OF REMOTE SENSING 14.1. Summary on applications 14.2. Land evaluation 14.3. Methodology 14.4. Recent and future developments 14.5. Political and legal considerations 14.6. Education and training 14.7. References 14.8. Additional reading

355-370 355-356 356-357 357-360 360-366 366-367 367-369 369-370 370

Plates 1 - 5 Abbreviations, symbols, units of m e a s u r e INDEX

37 1-373 374-375 37 6- 3 7 9

1 1.

INTRODUCTIOIJ

Ry way of an introduction, the meaning of the term remote sensing and the concepts of soil are discussed. The role of remote sensing in soil science is a logical consequence of these concepts. 1.1.

Remote sensing Remote sensing

OK

teledetection (French: t616dGtection),

sensu strict0

means sensing from a distance, whereby the distance itself is not defined. A well-known form of remote sensing is the use of OUK senses. An example

of a sensing mechanism,

OK

sensor. is the eye, which is sensitive to solar

radiation of a particular wavelength. Looking at an object means sensing the light reflected by

that object.

characteristics (recognition) and

The signals are translated into object into distance.

in'tensity of strong sunlight we can use filters (e.g.

In Order to reduce the sunglasses).

Defects of

the eye may be corrected by the use of optical lenses, while we can observe at a far distance with the aid of binoculars. As

stated before, the distance itself is not defined, therefore, X-ray

machines collecting information from a very short distance as well as radar operating from a l o n g distance can be regarded as remote sensing means. In engineering, a measuring device which collects signals at one place, these being displayed at another place by using radiocommunication, is called a remote sensing unit. In the present text, a remote sensor, is defined as a device collecting data from a distance that varies from a few metres to hundreds of kilometres. The data may be kept in a storable form (e.g. tapes etc).

aerial photographs, magnetic

In contrast to our memory, which is not capable of exactly

recalling past scenery, the stored information enables the user to look simultaneously at various recordings of the scenery of a specific place but recorded at different times. Remote sensing may be executed in various ways, using Electromagnetic Radiation (EMR),

soundwaves

OK

gravity forces. An important part of remote

sensing belongs to the field of study of the geophysicians. For remote sensing of the environment there are three basic aspects:

-

the physical aspects related to the interaction of EMR with objects or features at the earth surface resulting in specific data which can be

2

used for recognition and identification of these objects and features,

-

the morphographic and physiographic aspects related to the appearance of the environment on remote sensing imagery enahling identification and description of objects and features which may be used for a subdivision of land in land-units,

-

the morphogenetic aspects related to the appearance of the environment and the processes that have shaped the land-units (landscape genesis). If

radiation

of

wavelengths

outside

the

Visible

zone

of

the

Electromagnetic Spectrum (EMS) is used, and as a consequence the image is not familiar to the human eye, physical aspects will become more important. For soil science, we focus in this text on remote sensing by E m . The systems used f o r remote sensing may be passive when the EMR available in nature is used, o r

active when the EMR has to be supplied for remote

detection. Various stations are used for remote sensing of the earth (see par. 4.4),

like groundborne platforms

(e.g.

aircraft) and spaceborne platforms (e.g.

towers),

airborne platforms (e.g.

satellites). The wavelength zones of

the EMS normally used for remote sensing may vary from the Visible, the Near Infrared, the Far Infrared (e.g. (see par. 2.1).

thermal infrared) to that of the Microwaves

An active system using Microwaves is radar (chapter

13).

Remote sensing is not a new science, since one of the techniques, aerial photography, has been used for decades. The first aerial photographs were taken from balloons, around 1850 (De Breuck en Daels, 1967). During the

Second World War, considerable experience was gained in

interpreting airphotos for military purposes. The so-called false COlOUK-fflm was

invented for

the detection of

green painted camouflaged tanks and

artillery of the enemy. A t present airphoto-interpretation is an important aid for mapping the natural environment, in particular in less-developed countries and more generally in areas having a low population density. Besides mapping, the modern and more sophisticated techniques of remote sensing are making a number of interesting other applications possible. They may expand our "view" by the use of various devices as well as by the use o f different wavelength zones throughout the EMS. Moreover, a relatively accurate view may be obtained through the application of spectral signatures in combination with shape, size, grade, density and site as diagnostic characteristics of objects and features. Typical for remote sensing research is the multiconcept, which comprises the following:

3 multispectral (or multiband) observation, which is the observation in different wavebands enabling a spectral signature of objects; multistation, which is the observation from different stations at the same altitude

(stereosco.py) or different altitudes (multistage with

different scaies); multipolarized observation used for the study of polarizing properties of objects; multidate

multitemporal) observation, which is the observation of the

(OK

same area or object at different times e.g. in different seasons; in this manner, dynamic features like soil moisture and plant growth can be monitored in the areas under consideration; multi-enhancement or the enhancement of

imagery derived from digital

processing or photographic recording. The extensive application of purposes

remote sensing techniques for military

is linked to the advantages of radar and

nighttime operations and the use of

'thermal' scanning in

satellites for detection from out of

space. Automatic data acquisition has a high priority as a result of the large amount of data to be gathered and processed, and the fact that the information usually has to be available at the shortest possible notice. The difficulties encountered in inventoring and monitoring the natural environment are generally of a more complex nature than those encountered in the military field. Environmental studies are concerned with the identification and understanding of a large variety of natural features and dynamic processes, which are often interrelated in a very complex way. By using remote sensing techniques, we are able to study the interrelations and interactions fixed in the images. The interpretation of

these

images, often

in

close

cooperation with

other

disciplines in order to reveal the underlying basic processes and relationships, will enable us to control and ameliorate the use of the environment. The

application

of

modern

remote

sensing

techniques

and

physics

in

environmental sciences is not an easy task. Once a certain technique is accepted, the use of it might become a habit and only reluctantly will it be replaced. On the other hand scientists might become so mesmerized by the possibilities

of

modern

remote

sensing

established values of the older techniques.

that

they

tend

to

forget

the

4

It is regrettable to state that some of the remote sensing techniques are still in a juvenile stage as regards their methodology, despite the expected potentialities. Therefore in order to avoid disappointment during this stage of the development of remote sensing, it is essential to indicate with care the

best-fitted

and

proven

remote

sensing

technique

for

a

particular

environmental study. 1.2.

Concept of soil The Russian and American concepts of soil are briefly discussed below.

The Russian school developed the following concept of soil: Soils are natural bodies, each with a unique morphology resulting from a unique combination of climate, living matter, earthy parent materials, relief and age of landform. The morphology of each soil, as expressed by a vertical section through the differing horizons, reflects the combined effects of

the particular set of

genetic factors responsible for its development (Glinka, 1927).

Soil as defined in the U.S.

Soil Taxonomy (Soil Survey Staff, 1975) is

"the collection of natural soil bodies on the earth's surface, in places modified or even made by man of earthy materials, containing living matter and supporting, or capable of supporting, plants out-of-doors". Soil according to this definition does not need to have discernible horizons, although the presence or absence of horizons and their nature is of extreme importance to its classification. Soils have many properties that fluctuate with the seasons like temperature, moisture and biologic regimes. The smallest unit of soil is a pedon. It has three dimensions. Its lower limit is the often vague limit between the soil and "not soil" below. Its lateral dimensions are large enough to represent the nature of any horizon and variability that may be present. In practice, the lateral dimensions have to be determined by examination of trenches or digging with a spade or by augering at frequent intervals. The pedon is usually too small to be a practical mapping unit in soil surveys. A larger unit is needed, a combination of pedons or a polypedon, which occurs as a landscape component or natural soil body. This unit is then a mappable feature distinguished from its surroundings on

the basis of

discriminating criteria, which may be parent material, age of landform, relief and

other

soil

forming

factors.

According

to

the

U.S.

Soil

Taxonomy,

differences between polypedons may be related to the nature and arrangement of horizons or the soil as

a

whole e.g.

differences in mineralogy, structure,

5 consistence, texture of subhorizons and moisture regime. Between natural soil bodies there can be transitional zones e.g.

horizons can become thinner at

places and properties can change gradually. This is illustrated in fig. 1.1. In large-scale soil mapping (par. 1.3), exact soil boundaries. normally

In medium-scale

indicated in the centre of

it is often possible to present

soil mapping,

the boundaries are

transitional zones or complexes of

polypedons are presented on the map. 1.3.

Soil Mapping A systematic soil survey comprises the mapping of individual soil units

or polypedons. The maps can be used in the planning of many different forms of land-use and management practices. Basic data of this nature are of particular value in less developed countries in order to make a prediction of the most desirable form of land-use. systematic

A

soil

survey

usually

involves

airphoto-interpretation

combined with systematic field checking on the nature and homogeneity of the soil units. Generally, the upper metre of soil is described. During the course of the survey, the establishment of

the diagnostic criteria of each uniL and a

continued refinement of the mapping legend takes place. If necessary, specific field

investigations (deep

augerings, up

to

4

or

5

m)

are

initiated.

Furthermore, in order to improve the field-observations, soil sampling for laboratory analysis is carried out, s o that earlier estimates can be adjusted, resulting in more reliable future estimates. However, the field-observations are the main bases of soil mapping, since cost is often the limiting factor with regard to laboratory analysis. The

kind

of

information

collected

by

fieldchecks

and

additional

laboratory analysis during the soil survey usually depends on the purpose of the survey. A survey conducted for multiple goals requires information on a broad scale, while for a limited, well-defined aim, only information on a few characteristics of the soils is wanted. According to the Soil Survey Manual (Soil Survey Staff, 1951), a soil map is a map designed to show the distribution of soil types or other soil mapping units in relation to other prominent physical and cultural features of the earth's surface. From a comprehensive soil map, a series of interpretation maps may be derived, showing for example: the suitability of soils for certain

6

Fig. 1.1 Example of a natural soil body assemblage. X soils of the foot slope Y soils of the slope Z soils of the plateau transitional s o i l s X I , Z' with many properties of X or Z polypedons respectively XY, YZ with properties of X and Y, and Y and Z polypedons respectively minor boundary of polypedons indications: major boundary of polypedons u V U brown or red mottles -grey soil matrix due to presence of groundwater

--

--

------

crops, the erosion hazards under defined classes of management, drainage requirements for an optimum production, or the irrigation potentialities of the area. The optimum scale of the soil survey depends on a number of factors (see Soil Survey Staff, 1 9 5 1 ) :

I -

the purpose to be served;

-

the intensity of land use; the pattern of soils;

-

the scale of remote sensing imagery and other cartographic materials available.

The pattern of soils may be so dense that the distribution of soils can only be shown accurately on large-scale maps (e.g.

1:10,000 or 1:5,000).

However,

often a scale of 1:20,000 is sufficient. Difference is made between the scale of field mapping and the publication scale. The former is often reduced two or three times to the publication scale. The minimum dimensions of units that can be shown on the publication map may be given as follows: 25 mm2 for rounded or square forms;

-

2 mm diameter for elongated forms.

Those units that are too small for presentation on the final map can be described under associated soils. To obtain a broad idea about the amount of augerings needed at a certain publication scale, the following rule can be applied.

If aided by

augering(s)

per

remote-sensing-means, it is necessary to have

cm2 map area at publication scale.

1-3

The exact amount is

determined by landscape complexity within the limits given. Besides augerings, there are profile descriptions of soil pits, laboratory analyses, physical field-data, deep augerings and observations with regard to parent material, slope and

topographic position, which present

further evidence on soil

properties and soil geography. There is no generally accepted classification of scales. The following classes are proposed: detailed

1:lO.OOO

scale and larger

semi-detailed

smaller than 1:lO.OOO up

large-scale

to 1:25.000 scale reconnaissance

smaller than 1:25.000 up

(medium intensity) to 1:lOO.OOO

scale

reconnaissance

smaller than 1:lOO.OOO

(low intensity)

up to 1:250.000 scale

exploratory

smaller than 1 :250 .OOO up to 1:500.000 scale

medium-scale

8

smaller than 1:500.000

schematic

scale

The presentation of soil maps is largely dependent on scale. At a largescale, taxonomic units and phases are generally preferred. At a small-scale, a physiographic entry may give more direct information as well as contrasts among regions

so

that broad areas can be viewed as a whole.

In most less developed countries, detailed soil maps are not sufficiently available, and exploratory and reconnaissance maps have to be compiled to point out areas with a high potential, which thereafter have to be mapped in greater detail. In view of this, remote-sensing-means are indispensable tools and morphographic or physiographic descriptions (see par. 8.1) make up often the first entry to the legend of these maps, because:

-

the knowledge of

soil forming processes

is generally too

low

for

indication of taxonomic units,

-

landtypes and landforms determine the landscape performance, that is a daily reality to man; the physiographic maps are readily understood and geographic soil associations can be indicated both at the second and the third level.

1.4.

Remote sensing in soil science Soil science comprises the mapping of natural soil bodies as well as the

study of dynamical aspects. The mapping of natural soil bodies or soil geography is concerned mainly with the more or less permanent properties of soil whereas the study of dynamical aspects regards features such as soil temperature, soil moisture and structural changes e.g.

surface sealing.

Most remote sensing techniques use radiation which shows only a shallow penetration upon interaction with soil, rock and plant materials. By using these techniques, it is only possible to obtain direct information about the surface of soils and rocks or about vegetation covering the soil. Fieldwork is necessary to estimate the properties of the three-dimensional soil profile. Through combinations of interpretation aspects, soil profile properties may be inferred, but of course these suppositions have to be verified by fieldwork. Therefore, it would be a mistake to regard the interpretation of such remote sensing data as decisive for soil distribution without the undertaking of fieldwork. Even

remote

sensing

aids

that

have

a

deeper

penetration

(e.g.

microwaves), or provide data (with thermal Infrared) which are the result of

9

soil physical structure that is not limited to the soil surface alone, do not enable to reveal the complete complex of soil properties. The above emphasis is given to stress the necessity of fieldwork. Besides this, there is the basic physics, which deserves our attention as another aspect of modern remote sensing. Imagery obtained by the use of Visible radiation is familiar to the eye and in fact may be interpreted through direct recognition and identification, which in cases may be followed by deducing the underlying processes. However, other types of radiation, e.g.

UV, IR or Microwaves, may also be used

for image production to visualize certain properties of the earth's surface. A proper understanding of such imagery needs a physical basis focused on the interaction process of the radiation under consideration with the objects and features at the earth's surface. Specific studies require specific remote sensing techniques. The choice as to which remote-sensing-means is to be used, can be determined by four features.

-

the purpose of the study;

-

the scale of the study;

-

the specific characteristics of objects at the earth's surface in the area under consideration;

-

the climatic conditions.

The purpose of the study may be one or more of the following:

-

soil inventory; airphoto-interpretation is a good aid for this purpose at large and medium scales; at small scales, the use of satellite data as well as airphotos is recommended;

-

mapping of

dynamical features, such as

erosion and soil moisture;

multitemporal techniques are required for the study of dynamics;

-

land evaluation; this requires a good insight in natural vegetation and land-use as well as in soil dynamical aspects; airphoto-interpretation and multitemporal techniques are very useful. The scale of the study determines to a great extend the choice of the

most appropriate techniques. For large scale surveys, airborne methods are required, medium scale surveys may be aided by both airborne and spaceborne methods whereas small-scale surveys are served most by the use of satellite-

data. One should realise that the characteristics of the objects at the earth's surface are in fact the most decisive with regard to the choice of remotesensing-means. To illustrate this, three contrasting situations with specific climatic conditions will be considered: ( 1 ) the temperate zone, ( 2 ) the arid, semi-arid and sub-artic zones, and ( 3 ) the tropical rainforest. The

temperate

climatic

zones

are

generally

intensively

used

for

agricultural purpose. The soil is mainly covered by crops or planted forests and in places by semi-natural vegetation. The semi-natural vegetation may show a close relationship with the soil conditions but in case of crops or planted forests, the vegetative cover of soil cannot be regarded as an important key to determine the soil condition. Only locally (on arable land) is the soil surface bare during some period of the year. Therefore, spectral signature of the soil surface generally only offers information on places which are part of a greater unit (the natural soil body).

The dimensions of the natural soil

body have to be determined through a combination of different aspects which is usual in aiKphOtO-inteKpKetatiO~. Arid, semi-arid and sub-artic regions are characterized by a scarce vegetation-cover and bare rock or soils. Spectral signatures of the soil surface may offer valuable information for soil mapping. Up to now, airphotointerpretation in these regions is the most current tool for soil mapping, but there are good possibilities for the application of multispectral remote sensing in improving accuracy and decreasing the amount of fieldwork in mapping of soil. The third situation we want to consider is the tropical rain forest. In these regions, the natural vegetation, together with the aspects of relief, slope and drainage pattern, offers a good key to soil distribution in many places. Modern remote sensing techniques providing for a synoptic view and airphoto-interpretation have proved to be of great value for mapping of soils in these regions. Finally, climatic circumstances may be decisive with regard to the choice of the most appropriate remote sensing technique. When the climatic conditions rule out techniques that make use of short wave radiation (Visible or Near Infrared) due to permanent cloud cover, one should make use of radiation (radar), which can penetrate humid air and clouds.

long wave

11 1.5.

Conclusions The application of various remote sensing aids may reveal different soil

properties and the interpretation units may show a close relation to soil conditions. Unfortunately, ideal remote sensing techniques are limited to research projects., Mostly, one' has to work with means that are basically not intended for soil survey purposes. From this it can be inferred that there is a good reason that one should have knowledge of the applicability of the present great range in remote sensing techniques. Another reason may be found in the advantages arising from the application of different techniques. Knowledge of basic physics is essential for their optimum use. 1.6

References

Breuck, W. de, and Daels, L., 1967. Luchtfoto's en hun toepassingen. E. StoryScientia. P.V.R.A. Gent, 176 pp. Glinka, K.D., 1927. Dokuchaiev's Ideas in the Development of Pedology and Cognate Sciences. In Russian Pedol. Invest. I. Acad. Sci. U.S.S.R., Leninggrad, 32 pp. Soil Survey Staff, 1951. Soil Survey Manual. Agric. Res. Adm. US Dept. of Agric.: 503 pp. Soil Survey Staff, 1975. Soil Taxonomy. A Basic System of Soil Classification Dept. of Agric. for making and interpreting Soil Surveys. U.S. Handbook No 436, 754 pp. 1.7

Additional reading

Barrett, E.C. pnd Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and Hall, 336 pp. Estes, J.E. and Senger, L.W. (ed), 1974. Remote Sensing Techniques for Environmental Analysis. Hamilton Publ. Cy, Santa Barbara, California, U.S.A., 340 pp. Mulders, M.A., 1977. Application of Teledetection in Pedology. 1-er Colloque PBdologie T616d6tection A.I.S.S. (I.S.S.S.), Rome: pp. 311-324. Reeves, R.G., Anson, A. and London, D. (ed), 1975. Manual of Remote Sensing. Amer. SOC. of Photogramm. Falls Church, Virginia, Vol. I and 11, 2144 PP * Rudd, R.D., 1974. Remote Sensing. A better View. Duxbury Press, North Scituate, Masachussetts, U.S.A., 135 pp.

12 2.

INTERACTION OF ELECTROMAGNETIC RADIATION WITH MATTER

Energy can occur in different forms e.g.

kinetic, potential, mechanical,

chemical, electrical and thermal energy. Ocean waves make themselves manifest by their way of propagation. The waves are due to a disturbance at the air-water interface. They are transverse, that is the vibration of the particles is perpendicular to the direction of the propagation. A number of aspects connected with wave motion becomes visible when observing these waves, such as direction, wavelength, amplitude, velocity and frequency

.

Electromagnetic radiation (EMR) is energy that propagates through vacuum (free space) or through material media in the form of an advancing interaction between electric and magnetic fields.

It can make itself manifest by its

interaction with matter. Light and thermal energy are examples of EMR. Besides by radiation, thermal energy may travel by conduction and convection. In this chapter, physical concepts of EMR and its interaction with the atmosphere and objects at the earth's surface are discussed. The interaction process is of great importance to the remote sensing specialist. 2.1.

The nature of electromagnetic radiation The properties of EM waves can be summarized as follows (see Fig. 2.1):

-

the waves are transverse; the electric (E) and magnetic ( H ) vectors are perpendicular to the direction of propagation, mutual perpendicular and in phase. EM waves can be characterized by wavelength, amplitude, phase, frequency,

direction, velocity, polarization and coherence of the radiation. EMR which has a fixed direction of the electric vector is said to be plane polarized. Polarization of light can take place upon interaction with matter. The coherence of waves concerns the relationship of phases; coherent waves or uniform plane waves have a regular or systematic relationship between their phases, while incoherent waves have phases that are related in a random fashion. Radiant energy of natural sources is normally incoherent, however, some artificial sources, such as radar and lasers, are constructed to produce coherent radiation. Interference in a point

OCCUKS

when the EM field in that point is made up

out of contributions from more than one coherent source. When the distances

13

Fig. 2.1 Electric ( E ) and magnetic ( H ) vectors of an EM wave. the waves have travelled differ by a whole number of wavelengths, there will he a maximum of intensity. When the distance transversed differs by odd multiples of a half wavelength, the two waves will exactly cancel each other. Interference may occur when reflections of the surface and of an interface meet each other. A surface illuminated by laser light looks grainy and seems to sparkle.

As the waves are scattered from neighbouring points on the surface, they interfere with one another and reinforce one another if in phase, or cancel one another when out of phase. The interference pattern depends on the angle at which the surface is viewed (Schawlow, 1968). Ordinary light does not produce such interference, because the light waves are unrelated to one another as to phase. The polarization of a uniform plane wave refers to the time varying hehaviour of the electric vector field at some fixed point in space. Consider a uniform plane wave travelling in the z direction with the E and 11 vectors in the x-y plane (Fig. 2.1).

If Ex

= 0

and only Ey is present, the

wave is said to he polarized in the y direction: a similar statement holds for polarization in the x direction. If both Ex and Ey are present and in phase, the resultant electric vector will have a direction dependent on the relative amplitudes of Ex and Ey. The direction of the resultant vector is constant with time and the wave is said to be linearly polarized. If E, and Ey are not in phase, that is, if they don't

reach their maximum

values at the same time, then the direction of the resultant electric vector

14 will not be constant with time. In the particular case where Ex and Ey have equal magnitudes and a 90-degree phase difference: the wave is said to be circularly polarized. Other out of phase cases, produce elliptical polarization (Jordan et al., 1968). The generation of EM waves occurs in wave trains or bursts of radiation. Each wave train, elementary quantum or photon, carries a radiant energy ( Q in of the wave, so that

J) which is proportional to the frequency (f in s-')

J

where h is Planck's constant with a value of 6.626 x The EM waves travel through vacuum at a fixed velocity (c

=

S.

2,998 x lo8 m 6 - l ) .

The general relationship between velocity (c in m s-l) wavelength ( A in m) and wave frequency (f in s-l) is: (2 - 2)

c = f A Combining 2

-

1 and 2

-

2 results in

Q=h' x

(2

-

3)

Consequently, the energy of a photon is proportional to the frequency (2

-

2), and inversely proportional to the wavelength (2-3). The processes involved in the generation of EMR produce radiant energy with specific photon energy, frequency and wavelength. These quantities provide a scale for the so-called electromagnetic spectrum (EMS).

Particular zones are

essential for life, e.g. the Visible zone and the Infrared, or are made use of for practical reasons, e.g. Microwaves and Radiowaves (see Fig. 2.2). The radio spectrum is also indicated in Fig. 2.2. Part of it, that is from Very

- High

-

Frequency (VHF) up to Extremely

-

High

-

Frequency (EHF) is used for

radar and is called Microwaves. For subdesignations of this zone, the reader is referred to chapter 13.

15

g E

!5

v

v

E

F

E

S

E

E

x

m

0

m

0

m

m

m 0

m 0

m

m 0

o m

I

1

I

I

1

1

1

1

I

0

0

E 1

a

0

E m I

E

E m

U m

I

1

0

E

m

E O

E

m 0

m 0

1

1

1

E x

E x

E x

m

m 0

0 0

m

I

1

J

wavelength (m)-

w; N

N

N

N

N

N

N

N

N

I

I

I

I

I

I

I

I

0

0

0

0

0

0

0

0

7

c

c

c

c

7

c

c

I

1

I

1

1

I

1

I

N 0

!

?

E

t

"

"

S

"

I W

N I W

0

-

N I N W

N

I X

I

w

0 0

0 0

0

-

7

c

c

W

W

3

-

:

o

I

N

-

N

I N

c

N

Y

I Y

" E o

0

0

_

_

0

_

N I

Y

0

c

>

-

7

_

-1

300 30 3 300 30 3 300 30 3 GHz GHz GHZ MHz MHz MHz KHz KHz KHz

H = high L = low E = extremely

Fig. 2.2

U = ultra V = very M = medium

l!b

3bf;8;01 ;51;)0 3343 60

3iO km

1

1

1

109876 5 4 3

2

1 KHz

1 1 1 1 I

1

I

The electromagnetric spectrum Abbreviations: V,B,G,Y,O,R = violet, blue, green, yellow, orange, red respectively

16 The Visible zone is subdivided acc. to Weast ( 1 9 7 4 ) into the following bands : COlOUK

Wavelength in nm

Wavelength in nm representative for COlOUK 410 470 520 580 600 650

400-424 424-491 491-575 575-585 585-647 647-700

violet blue green yellow orange red

However, the eye shows a low sensitivity outside this zone respectively down to 380 nm in the short wavelength range, and up to 7 8 0 nm in the long wavelength range (Schurer et al.,

1 9 8 0 ) Therefore, the Visible zone is often

extended. 2.2.

Radiation laws All bodies with temperatures above absolute zero emit radiant energy.

The radiation laws use the concept of a perfect absorber and radiator, the so-

. These laws are:

called black body

-

the Stefan

-

Boltzmann's

law, which states that the total of

emitted from a black body (Me in Wm-')

radiation

is proportional to the fourth power of

its absolute temperature (T in K) according M e = o T4

where a

(2

=

2

15 c

in which c

=

k4 =

TI

2

h

5.7

4)

10-8 wm-2 K-4

3

velocity of light in m s-l

h = Planck's constant (see 2

-

1)

k = Boltzmann's constant = 1.38 x

-

-

5K-l

Kirchhoff's law; since no real body is a perfect emitter, the real emittance

(M) of a radiator is a fraction of the emittance of a perfect radiator (Me), thus

17

where

E

the emissivity (M/Me) of the real body, has a value between 0 (white

body or perfect reflector) and 1 (black body);

-

the wavelength, which

is

correlated to the maximum radiant emittance of the black body ( A max),

Wien’s

displacement law;

this

states

that

is

inversely proportional to its absolute temperature T according to:

Where C 3

=

2898

IJ

m K; the equation indicates that as the temperature

increases, the dominant wavelength of the radiation emitted shifts towards the short wavelengths (see F: :. 2 . 3 ) ;

-5 I

lo5 lo4

E ul

lo3

4J

+

9

v

lo2

c

V W

::.lo-:

U.

0 Wavelength (pn)

Fig 2.3

-

The spectral radiance of a blackbody (after Higham e.a. from Jamieson et al., 1963)

1973, adapted

Planck’s law. describes the spectral relationships between temperature and

radiative properties of a black body when thermodynamic equilibrium exists;

18 the law may be expressed by 1

M dX= 2 X

where M

X

h c2 X

TI

dX

=

(2

radiant energy in Wm-2 within a unit range of d X

h

=

Planck's constant (see 2 - I ) ,

c

=

velocity of light m s - ' ,

k

=

Roltzmann's constant (see 2

A =

wavelength in m,

T

absolute temperature in K,

=

-

-

J)

,

4).

e = base for natural logarithms. The equation enables the assessment of proportions of total emittance for a range between selected wavelengths. 2.3. Solar irradiance and earth emittance The spectrum of solar irradiance (radiant power received per unit area) outside the earth's atmosphere resembles that of a 6000 K black body spectrum, while the spectrum of terrestrial emittance (power emitted per unit area) approximates the 300 K black body. There is a global equilibrium between heat gained from the sun and heat lost to space. Fig. 2.4.

shows the EMS of solar and terrestrial radiation. Solar radiation is

significantly attenuated by the earth's atmosphere. The spectrum of solar radiation at the earth's

surface is in fact a

transmission spectrum, since part of the radiation i s specularly reflected, scattered, or absorbed by the molecules present in the earth's atmosphere. The total solar irradiance arriving at the earth's surface can be divided into a direct and a diffuse component. The latter is the result of scattering by atmospheric aerosols and molecules and will vary with the visual range in spectral properties and intensity. Most of the solar radiation which reaches the earth's surface has wavelengths shorter than 4.0 urn, whereas the radiation emitted by the earth is found mainly in the band 4.0

-

40 um (infrared).

Maxima in solar radiation and

terrestrial radiation are found respectively at 0.5 and 10 um. 2.4. Concepts of matter In remote sensing of the environment, many different types of matter are encountered, these being:

19

-I

uv

VIS I

body i r r a d i a n c e a t 6000 K

2000

E

I

1000 I

I / I

x

v ~

-.

:xtraterrestrial solar irradiance

a cu I E

-

Infrared 1

500

Direct beam (normal incidence) Solar i r r a d i a n c e a t the e a r t h ' s surface

I

I I

0, L

W

w C

200

100

50

20

7

5

2

t -.

Estimated infrared emission

-.

A

Di f f u s e solar irradiance a t the earth's surface

10

1 0.7 0.1

lack body emittance 300 K

-.

'\, I

-.

/ Absorption band

-.

0.2

0.5

1.0

2.0

5.0

10

20

50

100

Wavelength (pm)

Fig. 2.4 Electromagnetic spectra of solar irradiance and terrestrial emittance (modified after Barrett and Curtis, 1976, originally Sellers, 1965)

-

diatomic gases (e.g.

02, N 2 ,

CO);

- polyatomic gases (e.g. H 2 0 , C02); - complex molecular organic materials (vegetation and soil organic matter);

-

solid inorganic substances (minerals).

To understand the interaction of EMR with matter, we need to go down to the atomic and molecular level. If external energy is available, the atoms of a gas may become ionized that

20

is, electrons may be freed from an atom, leaving it as an ion with a net positive charge. On the other hand, electrons may attach themselves to an atom, thus forming a negative ion. In a metal, some of the electrons are free to move from one atom to the next giving rise to the conduction of electricity (Jordan et al., 1968). Substances that contain few or no free charges and consequently are poor conductors of electric current, are called dielectric substances. A good dielectric is one in which the absorption of electric energy is a minimum: a vacuum is the only perfect dielectric (Reeves, 1 9 7 5 ) . In structures such as molecules, the energy states give rise to specific features. Although the number of energy states increases with the density of the structure, that is from gas over liquid to solid, a general understanding may be obtained from the energy states of molecules, such as in gases. Molecules in gases possess three types of internal energy states: rotational, vibrational and electronic. For any electronic state, a variety of vibrational states is possible, and for any vibrational state a variety of rotational states is possible. The total internal energy of the molecules at any time is the sum of the energy of the three states. Electronic states are separated by energy differences corresponding to the energy carried by photons in the UV, blue and green regions; pure vibrational states by

photon energy in the yellow, red and near

Infrared and pure

rotational states by middle - far Infrared and Microwave portions of the EM spectrum (Lintz and Simonett, 1 9 7 6 ) . In liquids, the atoms or molecules are in continual motion but there is a certain amount of ordrr extending over a relatively short distance.

In solids unrestricted motion is not possible and the molecules are fixed in position in an orderly arrangement. The basic unit is

a

crystal.

Because rotational energy states are precluded in liquids and solids, only vibrational and electronic states remain. A number of fundamental vibrational modes are:

- the OH, S i - 0, Si - the H - 0

-

11

-

0

-

Si, Al - 0 - Si and Fe -

0

stretching modes,

and A1 - OH bending modes.

The modes of vibration show allowed frequency bands separated by forbidden regions. Crystals possess a long range order, a periodicity of structure. The forces acting between the a t o m in crystals are determined by the way in which the outer electrons of the composing atoms are distributed in space. One may

21 distinguish between the following extreme types (Dekker, 1958) : a. ionic crystals (e.g.

NaCl),

b. valence crystals (e.g. diamond C.

,

metals (Cu, Ag),

d. van der Waals crystals (many organic crystals). In ionic crystals, one or more electrons of one type of atoms are transferred to another, leading to the formation of positive and negative ions. The cohesive energy is provided mainly by Coulomb interaction between the heterogeneous ions. At elevated temperatures these crystals exhibit ionic conductivity. Ionic crystals are characterized by a strong absorption in the Infrared. In valence crystals, the neighbouring atoms share their valence electrons under the formation of strong bonds.

They are very hard and show a poor

electrical and thermal conductivity. In metals, the outer electrons of the atoms have a high degree of mobility to which these materials owe their high electrical and thermal conductivity. The cohesive energy is provided by Coulomb interaction between the positive ion and the "negative smeared out charge" of the conduction electrons. Molecules like H20 and HC1 may be considered to consist of two ions. They possess a permanent dipole moment which is equal to the effective charge per ion, times the separation of the ions. The interaction between such permanent dipoles provides, besides other forces, the cohesive energy in van der Waals crystals such as organic crystals. In this case, the other forces refer to the socalled dispersion forces which are due to fluctuating dipoles by combination of moving electrons and the nucleus of an atom. The weakness of the forces is expressed by the low melting point of these materials. Between the extreme groups, there are many intermediate ones e.g.

semi-conductors, being intermediate between valence crystals and

metals. To

understand

these

intermediate

groups,

the

electron

orbits

are

considered as energy levels separated by energy gaps. Crystals for which a certain number of energy levels are completely filled with electrons, the other (dielectrics).

levels being

completely

empty, are insulators

On the other hand, a metallic character is caused by the

presence of an incompletely filled energy level. If the energy gap between the empty and the filled energy levels is low, as for intermediate groups, an insulator may become a semi-conductor by thermal

22 e x i t a t i o n . When t h i s happens, some of t h e e l e c t r o n s of t h e upper f i l l e d l e v e l a r e e x i t e d i n t o t h e n e x t empty l e v e l and c o n d u c t i o n becomes p o s s i b l e (Dekker,

1958). I n normal l i q u i d s o r g a s e s ,

t h e o r i e n t a t i o n of

and t h e p h y s i c a l p r o p e r t i e s become independant of

t h e m o l e c u l e s i s random

t h e d i r e c t i o n a l o n g which

t h e y are measured; t h e y a r e i s o t r o p i c . The p h y s i c a l p r o p e r t i e s of s i n g l e c r y s t a l s i n g e n e r a l depend on t h e d i r e c t i o n a l o n g which t h e y a r e measured r e l a t i v e t o t h e c r y s t a l a x e s . T h i s phenomenon i s c a l l e d anisotropy.

Trigonal,

t e t r a g o n a l and hexagonal systems a r e o p t i c a l l y

u n i a x i a l , b e i n g i s o t r o p i c f o r t r a n s m i s s i o n p a r a l l e l t o t h e p r i n c i p a l a x i s of symmetry. Orthorombic, m o n o c l i n i c and t r i c l i n i c systems a r e o p t i c a l l y b i a x i a l . However, c u b i c systems a r e o p t i c a l l y i s o t r o p i c . Besides

s o l i d matter,

rocks

may

also

c o n t a i n l i q u i d s and

s o i l s , t h e p r e s e n c e of w a t e r and a i r i s a must.

gases.

For

The s o l i d s i n r o c k s and t h e

rock fragments o r m i n e r a l s i n s o i l s may range from l a r g e b l o c k s w i t h e i t h e r smooth, p o l i s h e d s u r f a c e s , o r rough s u r f a c e s , t o s m a l l p a r t i c l e s t h a t v a r y i n s h a p e and packing. The macroscopic p r o p e r t i e s , as w e l l as t h e a t o m i c - m o l e c u l a r - and l a t t i c e s t r u c t u r e s , d e t e r m i n e t h e i n t e r a c t i o n w i t h EMR.

2 . 5 . Atomic

-

molecular e f f e c t s

on

the

i n t e r a c t i o n process:

polarization,

d i e l e c t r i c c o n s t a n t , r e f r a c t i v e i n d e x and a b s o r p t i o n f a c t o r . Since m a t t e r i s l a r g e l y made up of charged " p a r t i c l e s " ,

external e l e c t r i c

and magnetic f i e l d s must e x e r t some k i n d of i n f l u e n c e . This i n f l u e n c e w i l l be p r e s e n t whether

t h e p a r t i c l e s a r e f r e e t o move about o r a r e t i g h t l y hound

together (Jordan et al., In

t h e c a s e of

1968).

good c o n d u c t o r s such as m e t a l s ,

t h e e l e c t r i c f i e l d of

the

i n c i d e n t wave c a u s e s c o n d u c t i o n c u r r e n t s t h a t produce t h e i r own e l e c t r i c f i e l d and g i v e r i s e t o v e r y s t r o n g r e r a d i a t i o n of t h e EM wave ( m i r r o r

-

effect).

D i e l e c t r i c s o r i n s u l a t o r s d i f f e r from c o n d u c t o r s , i n t h a t they c o n t a i n no f r e e charges, ions,

atoms,

but

r a t h e r c h a r g e s which a r e t i g h t l y bound t o g e t h e r

p a r t i a l molecules

e x t e r n a l EM f i e l d

causes a

and molecules.

s m a l l but

The a p p l i c a t i o n of

s i g n i f i c a n t s e p a r a t i o n of

t o form a

steady

t h e bound

c h a r g e s , s o t h a t each i n f i n i t e s i m a l element of volume behaves as i f i t were a n e l e c t r o s t a t i c dipole.

The induced d i p o l e . f i e l d t e n d s t o oppose t h e a p p l i e d

field (polarization). On a n atomic s c a l e , e l e c t r o n i c p r o c e s s e s a r e i m p o r t a n t , and c h a r g e s e p a r a t i o n

23

can occur due to the displacement of the negative electron cloud relative to the positive nucleus; this is called electronic polarization. On a molecular scale, vibrational processes (par. 2.4) with atomic or ionic and orientational polarization are important. Atomic or ionic polarization results from the displacement of atoms or ions within molecules (due to an external field). Orientational polarization arises in materials whose molecules are permanently polarized but randomly oriented; an external EM field causes the molecules to align themselves. On a still larger scale, one encounters space-charge polarization.

In that

case, free conduction electrons are present, but are prevented from moving over relatively great distances by barriers such as grain boundaries. The application of an external EM field results in piling up of these electrons against these barriers producing the separation of charge required to polarize the material (Jordan et al., 1968). For each type of polarization there is a typical resonance frequency, which has the precise radiant energy (h.f see 2-1) needed for the energy transition. Material properties important for the interaction are the permittivity or dielectric constant

(E

) and the conductivity ( u ) .

The dielectric constant of a medium is defined by the equation (Weast ed., 1974) :

where F is the force of attraction between two charges Q and Q' separated by a distance R in a uniform medium (capacitance of a capacitor with specific dielectric material).

where

E

Often

E~

is used, the relative dielectric constant:

is the dielectric constant of free space (8.859 x lo-"

The dielectric constant is

a

V-'

A s m-')

measure for the amount of polarization upon

interaction. To obtain normalization, so-called static

E~

values may be derived

by application of a static EM field (frequence zero). The static cL. values of most dielectric media are between 1 and 6 , but water having dipole molecules has an exceptionally high value of about 80 (Prins,

24

1955). Temperature, p r e s s u r e and composition have impact on t h e

E

v a l u e s . So

does t h e f r e q u e n c y of dynamic o r a l t e r n a t i n g f i e l d s . t h e frequency i s low ( e . g .

If

a t Microwave f r e q u e n c i e s and Radiobands),

t h e m a t e r i a l behaves e i t h e r l i k e a conductor o r semi-conductor, f r e q u e n c i e s i t behaves l i k e a d i e l e c t r i c (e.g. The

p o l a r i z a t i o n of

while a t high

I n f r a r e d and V i s i b l e ) .

e l e c t r o n s may be a t t a i n e d

simultaneously with an

i n s t a n t a n e o u s EM f i e l d b u t t h e o t h e r t y p e s of p o l a r i z a t i o n r e q u i r e r e l a t i v e l y much t i m e

t o a t t a i n t h e i r s t a t i c value.

Dekker

(1958) mentions a t i m e f o r

d i p o l a r p o l a r i z a t i o n which v a r i e s between days and of

S.

S i n c e t h e masses

the microscopic bodies c o n t r i b u t i n g t o the p o l a r i z a t i o n increase i n t h e

range of e l e c t r o n s , i o n s , m o l e c u l e s up t o complex m a t e r i a l s l i k e g r a i n s , t h e resonance

frequencies

for

these

successive

polarization

effects

have

to

d e c r e a s e . This i s , because i n e r t i a of t h e p a r t i c l e s becomes r e l a t i v e l y g r e a t and c o n s e q u e n t l y t h e p a r t i c l e s a r e u n a b l e t o

f o l l o w r a p i d o s c i l l a t i o n s of t h e

applied field. By way of i l l u s t r a t i o n , E~ v a l u e s a t r a d i o f r e q u e n c i e s a r e g i v e n i n t a b l e 2.1. Most m a t e r i a l s show v a l u e s between 1 and 14 w i t h i n t h i s f r e q u e n c y range. For example, sodium c h l o r i d e h a v i n g a n

gr

of 6.12

a t VLF shows a lower v a l u e i n

the Visible ( E = ~ 2.25 acc. t o P r i n s , 1955). Its resonance f r e q u e n c i e s are i n Table 2.1.

R e l a t i v e d i e l e c t r i c c o n s t a n t of s o l i d s a t r a d i o f r e q u e n c y and a t T 17 - 22" C u n l e s s s p e c i f i e d d i f f e r e n t l y (Weast ed., 1974).

=

solids apatite

1 11

It

optic axis 11

frequency

€1.

VHF 3 x lo8

9.50 7.41 5.5 8.0 6.8 14.2 86 170 12 5.3 4.34 4.21 8.50 8.00 5.66 6.12 7.10 6.3

I,

11

diamond dolimite 1 optic axis 11

I,

I,

108 11 I,

11

I,

f e r r o u s o x i d e (15°C) rutile 1 optic axis 11

,I

I,

11 11

1,

z i r c o n 1 ,I1 o p t i c a x i s sodium c a r b o n a t e (10H20) quartz 1 optic axis 11

11

It

11

It

It

VLF

1 I

I'

104 I,

11

gypsum sodium c h l o r i d e tourmaline 1 o p t i c a x i s It

HF

11

calcite I optic axis I,

It

6 x lo7 3 x lo7

11

11 11 11

11

25 the Infrared. The relatively heavy ions involved cannot follow the rapid ossillations in the Visible. The same applies for frequencies in the Visible,

E

of water for the high

being around 1,77.

E

r In an electric field, the frictional work done in polarization of atoms

and molecules absorbs energy from the field. When the field is removed the orientation is lost by thermal agitation. If free charge carriers are present, the current also causes heat loss because of the resistance of the material. At high frequencies (Infrared, Visible and UV), the losses are relatively high, only electronic or ionic (or atomic)

polarizations are active and

permanent dipoles are not able to follow the field variations. At low frequencies (radio and audio),

the losses are relatively small and

permanent dipoles contribute their full share to the polarization. Another term used to describe the interaction of EMR with matter is the index of refraction ( n ) which indicates the ratio of the velocity of EMR travelling through free space (c) to its velocity in a specified medium (A) n = -nA n= C

(2

-

10)

vA where n A is the refractive index of the specified medium, and no that of free space. For the same frequency,

E

of dielectrics is related to n as follows:

(2

Er=n2

-

11)

Normally, the EM wave experiences exponential damping in traversing the material. The damping in electronic, atomic or ionic displacements is caused by the restoring and frictional forces. Although for electronic polarization in a specific case with low damping, absorption and emission at a critical frequency may be produced simultaneously (selective reflection acc. to Jenkins et al., 1957), absorbed.

generally, a considerable portion of the incident radiation is

The radiation absorbed is converted into radiation of a lower

frequency and a longer wavelength: mainly thermal radiation. Lambert's law relates the original intensity (10) to the intensity (I) after passing through a thickness x of a material with an absorption factor k:

I

=

Ige-kx

(2

-

12)

The wave may penetrate only a very short distance in good conductors

26

before

being

reduced

to a negligible

small percentage of

its original

strength. The depth of penetration 6

or skin depth is defined as that depth in which

the wave has been attenuated to l/e or approximately 37 percent of its original value. At that distance kx

=

1 (see 2

-

12) and since 6

=

x in that

-

13)

case 6s = - 1

(2

k

For absorbing media, the index of refraction does not properly describe the interaction process. One has to use a loss term in addition. This is expressed by the complex refractive index (it),

which is given by:

where k is the absorption factor (2 - 12), and j= From this relation together with 2

-

11,

a.

it follows for absorbing media

that

where

E

is the complex dielectric constant ( X,T)

with

defining velocity and wavelength in the material, and

E' E"

as the real part is the imaginary

part which expresses the energy losses in the medium.

E"

and

E"

=

2nK or n

=

2K

(2

-

15)

(2

-

16)

2.6. Macroscopic effects on the interaction process; a description using the wave model of EMR. In section 2.5,

the displacement of charges (polarization) is introduced.

The EM field which causes the polarization is an alternating field. The displacements are elastic and have a restoring force which is proportional to the displacement itself. They can be treated as harmonic oscillations. The external EM energy is in resonance when its photon energy is equal to the

27 difference between two energy levels of the atoms or molecules in the target. Actually, the atoms

OK

molecules also react to EMR of any frequency: the

socalled nonresonant reaction. The molecules and atoms act as oscillators if an EM wave passes over them. The EM wave induces a vibration of the oscillator in

the target, so that it oscillates with the frequency not with its own resonance frequency

wo

w(=2nf)

of the field and

*

In principle, a vibrating charge is an emitter of E m . In gases, there is an individual incoherent scattering by each oscillator. There is no particular interference among the oscillators of gases. However, the molecules or atoms of solids (and of liquids or even cloud droplets) show an orderly arrangement, which results in interference of the reemitted waves. The interference is destructive in all directions except for the forward direction where it is constructive. In the forward direction, the reemitted waves build up to a single refracted wave. This is not so near the surface of the material. There is a thin layer (about $ A thick) of oscillators at the surface for which the back radiation is not completely

canceled

by

interference.

The

oscillators adds up to a reflected wave.

radiation "backward"

of

these

The intensity of the reflected

radiation is proportional to N2, where N represents the number of oscillators producing radiation waves which are in phase at a given point in space 4 (Weisskopf, 1965; N2 is proportional to A ). Macroscopic

effects

such

as

true

surface

or

specular

reflection,

scattering and refraction take place at boundaries and are a function of chemicophysical

structure

as

well

as

roughness and

orientation

of

the

boundaries.

To obtain a simple model, EMR is assumed to travel from a less dense medium (air) to a more dense medium with a plane surface. Upon interaction, part of the EMR is reflected from the surface, the rest enters the substance and is transmitted to a degree depending on the absorption characteristics. The angle Bi formed by

the direction of

propagation of

the incident

radiation with the normal to the surface (see Fig. 2.5) differs from

Or the

angle of refraction, which is the angle formed by the direction of propagation of the radiation penetrating the substance with the normal to the surface. Fig.

2.5 presents specular reflection, which occurs when surfaces are smooth

28

i nc i den t ra dia tion

r e f 1 ec t ed r a d i a t i o n

I

J

o p t i c a l l y l e s s dense layer ( A )

o p t i c a l l y more dense layer (B)

transrni tted/ radiation

Fig. 2.5

I

a

o p t i c a l l y l e s s dense 1 a ye r

Specular reflection, refraction and transmission of light.

a) general situation b) specific case: angle between reflected and refracted rays is 90" -parallel to plane of incidence (vertical polarization). 0 perpendicular to plane of incidence (horizontal polarization). Plane of incidence: plane formed by the normal to the surface and the direction of propagation of the incident wave. Horizontal and vertical refer to the plane surface upon which the wave is incident, although the direction can only be near vertical at grazing angles.

29

and

highly

polished.

It follows Snell's

law, which gives

the index of

refraction (n) relative to free space for each medium. When the media A and B are concerned: n

sin 0

n

sin 0

B - _

A

i

2.6.

This relationship is expressed in Fig. derived from this figure: at low angles of

Two

conclusions may be

incidence ( O i

=

10" - 2 0 " ) a

difference in the index of refraction does not cause great differences between O i and

0, (low O i

angles (Oi

=

-

Elr);

Oi

-

0, becomes very high for high n at grazing

70" - 8 0 " ) .

8ol

/

n = l ,O

n=l,l

n=l,3 n=l,5

n=2,0 n=2,7

Fig. 2.6 Relationship between

Oi, 0, and n (n=

nB

- ),

nA The horizontally polarized components of the incident EMR (see Fig. 2.5b) parallel to the interaction surface do not meet

discontinuities in that

surface and therefore are strongly reflected. The Fresnel reflection factors apply to flat smooth boundaries between two homogeneous and isotropic media, coherent monochromatic EMR and a medium in which multiple reflections do not occur. They have the following form:

30

-

E~

n2 cos e

+

Jn2-

= q =n2-cos ei + A'

Rv

'T E~

=

where

\

=

=

sin

-

2

ei

(2

-

18)

sin2 ei

2

cos

ei -

Jn2

-

sin

cos

ei +

Jn2

-

sin2 ei

ei

( 2 - 19)

reflection factor for vertical polarization,

Rh

=

reflection factor f o r horizon polarization,

Ei

=

amplitude of incident electric field with v

E,

=

amplitude of reflected electric field with v or h polarization,

0

=

angle of incidence,

=

index of refraction ratio between two media,

n

i

In table 2.2 equations 2

-

some values are given for

18 and 2

Table 2.2 Values of p n

oi

'G 200 40" 60" 80"

i

-

and Rh calculated according to

= 1.5

-0.104 -0.252 -0.645 -0.795

OK

n

= 1,5

and n

= 2.

n = 2 ph

%

PV

0.012 0.064 0.416 0.632

-0.311 -0.235 -0.518 0.431

0.097 0.055 0.268 0.186

Rh

0.083 0.021 0.012 0.237

h polarization

19.

and ph at Oi 2 0 , 4 0 , 6 0 and 80"

PV

-0.288 -0.146 0.112 0.487

\

OK

Ph

Rh -0.354 -0.424 -0.565 -0.819

0.125 0.179 0.319 0.671

In table 2.2 the reflectance for horizontal polarization:

ph

= (Rh)2

=

Irh where

Irh is intensity of reflected radiation with

Iih horizontal polarization, and

Iih is intensity of

horizontal polarization (item

p v).

incident radiation with

The negative signs indicate phase changes.

These, however, are immaterial for the intensities since the latter are dependent on the squares of the amplitudes. When we consider the intensity figures of table 2 . 2 ,

we see that for

vertical polarization with increasing angle of incidence an angle will be reached where polarization

the intensity becomes zero, this in contrast to horizontal the

intensity

of

which

increases

with

increasing angle

of

31 incidence. The angle at which vertical polarization is lowest, and therefore the reflected radiation is best polarized, is called the Rrewster angle. When this situation occurs Snell's law (2

-

17) can be written as:

sin B i

nB -=

-

sin (90

nA

= tan 0

0,)

(2-20)

i

The situation is presented schematically in Fig. 2.5b. Fig.

2.7a

shows

polarization ( pv) medium with n at about 56'.

reflectance

of

and

horizontal( ph )

vertical

in relation to the angle of incidence for a dielectric

1.5.

=

the

The polarizing angle or Brewster angle (tan Oi

From the data in Fig. 2.7a,

1.5)

=

is

it may be concluded that upon

interaction at Oi larger than 3 0 " , the reflected EMR shows a predominance of horizontally polarized radiation (surface reflection).

1 .o

f ref1 ec tance

1 .o

+

reflectance

t

b.

P. I-

1

angle of incidence Brewster angle

1 9n0

I

I

I

I

'

1

I I

'

I

angle of incidence

'

h

goo

Fig. 2.7 Reflectances (Higham et al., 1973) (a) non-absorbing medium (b) absorbing medium Fig. 2.7b shows

ph and p

for an absorbing medium. It appears that the

reflectances are higher than for the non-absorbing medium and that

pv

does

not become zero at the Brewster angle. So

far, targets with a plane surface and coherent radiation have been

considered.

It will be evident that granular materials (e.g.

soils) and

32 incoherent radiation offer more complications. Besides reflection at the surface, internal reflection

OCCUKS

at surface

boundaries within the granular material. The internally reflected ray leaves the grain upon refraction at the grain surface and is added to the total reflected radiance. Therefore for incoherent illumination, the total reflected radiance of a granular object is thought to be composed of a surface component and an internal, or volume component. The total reflectance (PT) may be given by: (2

where

p,

and

pi = internal reflectance (Leu, 1977).

=

-

21)

reflectance of the surface

Minerals show differences in the magnitudes of the surface and the internal components of reflectance depending on their refractive index and absorption. Most low absorptive minerals with low refractive index show a relatively small P

(1) and will become brighter due to a high

p

(A)

when grain size is

decreased. However high absorptive minerals are generally characterized by a high

p

(A)

and low

p

(A).

Most of the colours, we see around us are due to preferential absorption. The reflection from the surface is practically colourless; the principal colour is derived from light that has penetrated and which, after being reduced by the absorbing effect of the medium, is reflected by a second (or third) surface (Weiskopf, 1968). If the surface reflectance is very large, the material is said to have a surface colour (e.g.

metals).

When the radiation reflected from within the

material is predominant, the material exhibits a body colour which accounts for most minerals and vegetation. Diffraction occurs when EMR interacts with an edge oE an object. The reflected wave

fronts spread out

and

the EMR

departs from rectilinear

propagation. Scattering is closely connected both with reflection and with diffraction. When the size of a reflector is somewhat greater than the wavelength of the incident radiation, spherical and regular wavelets are produced in the centre

33 of the reflector to form short segments of plane wave fronts, while at the edges

the

reflected

wave

fronts

spread

out

owing

to

diffraction.

It

is

understandable, that there is greater spreading when the reflector becomes smaller with respect to the incident wavelength. The spreading may become so great that the reflected waves differ very little from uniform spherical waves, and plane wave fronts are not produced; the radiation is said to be scattered (Jenkins et al., 1957) Some of the earliest models assumed that scattering of the surface arose from many point scatterers and followed Lambert's cosine law:

I (Oi)

= I.

where I(Bi)

(2

cos Oi =

-

22)

intensity (W/sr) as a function of angle of incidence (0) and

I. = intensity (W/sr) for Bi = 0.

According to 2 0 , 6 4 I. and 0.34

-

22,

at,Oi l o " , 50" and 70", I (Bi) is respectively 0.98

Io,

10.

The distribution is hemispherical and is often referred to as the normal Lambertian behaviour. The model might be applicable for specific vegetation types when using coherent radiation for detection, but it does not explain the behaviour of scattering from many other surfaces. A

different approach is found in the so-called facet models. In these

models, a rough surface is described through a series of small planar facets. The models treat the scattering or reflection from the assemblage of facets by taking into account their size, slope, orientation and distribution. A wide finite facet, being many wavelengths across, shows a narrow reradiation

pattern, in contrast to a narrow finite facet (approaching the wavelength), which has a wider reradiation pattern. In Fig. 2.8 from left to right, the facet size is increasing. Small facets (at the left) are almost nondirective. Larger facets concentrate the scattered energy more at normal incidence. For an infinite large facet, all the energy is reflected back at the source.

When the illumination is incident from an other direction than normal to the surface, the general shape of the patterns remains the same, but the peak of the reradiation pattern is in the direction of reflection (Fig. 2.8b). Therefore, an infinite plane facet only produces much reradiation back at the

34

small

moderate

large

very large

moderate

(a) normal incidence Fig. 2.8

(b) oblique incidence

Facet patterns at normal (a) and oblique (b) incident illumination.

source when the direction of the incident radiation is normal to the surface. Natural surfaces, generally show a very complicated assemblage of facets, which may be described in a broad way by roughness. Rayleigh's criterion defines roughness as a function of wavelength and Oi. A surface is smooth according to this criterion if:

h < A/(8 cos Oi)

(2

-

23)

where h

=

height: above a plane in wavelengths. The

roughness

concerns

microrelief.

If

the

microrelief

becomes

significantly small, the surface is smooth and reflects with high directivity. When the microrelief is greater than the criterion given above, the surface scatters with a nondirective pattern. However, there will be an upper limit at which the influence of diffractive patterns is negligible and directive reflection dominates (see large facet Fig. 2.8).

As can be seen, the wavelength of the radiation dominates the roughness upon interaction. Most natural surfaces appear to be rough when illuminated by short wavelength radiation such as the Visible, but may be smooth for long wavelength radiation (Microwaves).

The angle of incidence is also important,

the smoothness criteria acc. Rayleigh being at 118 A s 1/5 A and '/3

Oi

= 10'

50' and 70' about

A respectively.

Another aspect related to the angle of incidence and surface roughness is

35 shadow. The shaded area has to be taken into account in calculating the total reflectance.

To illustrate this, Fig 2.9

is given, which shows the effect of normal and

oblique incident radiation on a surface with regular roughness. This figure demonstrates the complexity of roughness. Normal incidence in Fig. 2.9a

results in reflection at the horizontal surfaces only, their sum

being equal to the orthogonal projected surface. The total reflecting surface in Fig. 2.9b

consists of the horizontal upper facet as well as the vertical

facets towards the source and the horizontal lower facets minus the shaded areas of these facets. In this case the total reflecting surface is somewhat larger than the orthogonal projected surface. So

the effect of oblique incidence and consequent shadow is a small

increase in reflected radiation. The simple statement, roughness produces shadow and thus reduction in reflected radiation, has no general validity. The non- Lambertian behaviour of many natural surfaces, which may show a wide distribution of grain sizes, is mentioned above. The work of Coulson (1966), being a study on hemi-spherical reflectance of soil and grass surfa-

i nc ide nt r a d i a t i o n normal t o a surfa c e w i t h re gula r roughness

a.

\

b.

Fig. 2.9

i n ci d ent ra dia tion oblique t o a surfa c e with r egula r roughness

Incident radiation in relation to regular roughness of a surface of which each facet acts as a diffuse reflector.

36 ces, illustrates this (chapter 3 ) . Coulson found at high oblique incidence ( e.g.

Oi

=

53"), maxima in scattered

Visible and near Infrared radiation, not at the specular point, but forward beyond this point as well as in the backward direction (Fig. 2.10). and

pi (2

-

Using

ps

21) and the effect of shadow on rough surfaces, the following

explanation is given.

Fig.

2.10

Model of scattering from natural surfaces at high oblique illumination. The vectors indicate schematically the intensity of scattered radiation from a low absorbent medium.

At high oblique incidence of radiation on rough natural surfaces such as soils, the contribution of

ps

in the forward direction is reduced, since the

irregular surface minus the shaded area offers only few facets for reflection. However, for low absorbent materials,

pi, due to reflection from internal

facets, is high and contributes to the p in forward direction producing a maximum in the scattered radiation. In the antisource direction, however, no shadow is present to reduce Ps and another maximum is found. The latter will be more pronounced for high absorbent materials, which are characterized by a high p s

,

while the forward maximum for these materials is not pronounced,

owing to their low

pi.

2.7. Thermal properties A number of materials which show absorption due to electron orbital motion changes are capable of converting the absorbed energy into emitted radiation of a longer wavelength band without first converting the absorbed

37 energy

into

thermal

energy.

The

process

is

called

luminiscence

or

fluorescence. The fluorescence of natural materials is in the Ultraviolet, Visible or near Infrared. However, at the high frequencies of the Visible and the near Infrared, a considerable portion of the incident energy is wasted due to energy exchange with the components of the surrounding lattice. The absorbed energy ultimately appears as thermal radiation. In such a way, some of the solar radiation in the Visible is converted into middle and far Infrared upon interaction with the earth's surface. Some

concepts

and

parameters

used

in

description of

the

thermal

interaction process are discussed below (see also par. 2.2). The emissivity

E

is defined as the ratio of the spectral emissivity of a

material to that of a black body at the same temperature (2

-

5).

For a black

body, the spectral emissivity is equal to the spectral absorptance, which is by definition equal to 1. For natural bodies, we can distinguish absorbed energy ( M ), reflected energy ( MP) and transmitted energy ( M

). Therefore, the incident energy (Mi) can

be divided into (Janza, 1975):

+ M

M . = M i

a

+ M

p

~

2

-

24)

2

-

25)

or normalizing with Ei

a(X)+

p ( X ) +

r(X)=l

Natural bodies which approach the properties of black bodies with respect to emissivity are

the so-called opaque materials.

considered to have a

0 . Then a

+

p =

p

Opaque bodies may

1 and because a

is low and

E

be

= E:

(2

p

E = 1 -

where

T =

-

26)

is high for opaque natural bodies, while the opposite is

true for highly reflectant natural bodies. Similar to reflectance, one may use the terms absorptance and transmittance. Absorptance is defined as the ratio of the radiant flux absorbed hy a body to the radiant flux incident upon it. Spectral absorptance refers to the

38 absorptance in specified wavebands. Transmittance is the ratio of the radiant energy transmitted through a body to that incident upon it. The emissivity, like reflectance, is sensitive to variables of

look angle,

wavelength and polarization. Janza (1975) used an air-sand interface (a lossless medium with a complex dielectric consistent E~

=

3.2

to indicate the magnitudes of

-

j0 at a real temperature of 27510 for example

the parameters and their variations with the

angle of incidence. Since it concerns a lossless medium, the emissivities f o r vertical polarization and horizontal polarization, respectively ( are given by 1 E

h

/e

-

p

and 1 -

p

E

and

tj,

1,

h, respectively. In that case, the %/O and

curves can be constructed (see Fig. 2.11).

3=

w

1.0

2 0.9

0

," +J

0.8

a,

0.7

8

.r

V

E 0.6

x

c,

.r

0.4

5 .r

VI

0.3

v)

.-

5

0.2 0.1

0 0

Fig.

10

20

30

40 50 60 70 80 90 Angle o f incidence, 8 (degrees)

2.11

Emissivities f o r air-sand interface as a function of angle of incidence (Janza, 1975). (Used by permission of Am. S O C . for Photogrammetry and Remote Sensing.)

Lillesand et al., (1979) give typical emissivity values, the measurements being taken normal to the surface of the objects and at a temperature of 20°C.

39

By way of illustration some of these values are given below: Material

E

distilled water

0.96

wet soil

0.95

dry soil

0.92

sand

0.90

wood

0.90 The radiometric temperature (TB) of an object can be related to the real

temperature (T or thermometric temperature) by using the emissivity values )

(E

TB

=

therefore (Janza, 1975): ET

(2

-

27)

The third measure of temperature is the antenna temperature or TA, as it is measured from remote distances. This measure has to be calibrated against a

standard in the radiometer. In relating the calibrated TA with the TB of the object, the condition of the atmosphere between the object and the antenna has to be taken into account. To indicate temperature change or heat transfer in a medium or a system, a number of expressions are used. The specific heat ( C in Jkg-lK-')

of a substance is the ratio of the total

quantity of heat required to produce unit temperature change in a unit mass of that substance, to that required to produce the same change in a unit mass of water at 15" C (Janza, 1975) The thermal capacity or the ability of material to store heat is equal to the product of density (

p

in Kg. m-3)

and specific heat:

pC

in Jm-3K-'

(at

constant pressure; Reeves, 1975). The thermal conductivity A in JS-lm-lK-l or Wm-lK-'

is defined to be equal to

the quantity of heat that flows through a unit area of a plate of unit thickness, having unit temperature difference between its faces. It is a measure of the ease of heat transfer within a substance. Metals have high conductivity values, while those of insulating materials are low. The change in temperature caused by a certain quantity of heat flow is expressed by the thermal diffusivity (a in m2s-l),

which is equal to:

40

The thermal inertia is a measure of the rate of heat transfer at the interface between two dissimilar media. Materials with low thermal inertia are relatively insensitive to change in temperature at their boundaries. They feel cooler in the hand when hot, and warmer when cold, since the rate of heat transfer is low. The thermal inertia ( P in Jm-' P =

K-'

S M f ) is given by:

m

(2

-

29)

Some examples may serve to illustrate the differences and relationships between the parameters. Materials with a low density normally have a low thermal conductivity. Cork is extremely insensitive to heat flow, due to its high content of air. Air has an extremely low thermal conductivity. The thermal diffusivities of wood and brick may be the same (although wood has a low A and

pC, while brick has a high X and

pC),

that is the change in

temperature in these materials takes place within nearly the same period of time. However, the thermal conductivities are very different and cause the quantities of heat in these materials under the same temperature gradient to be very different. The difference may be expressed by their thermal inertia values. 2 . 8 . Atmospheric effect on EMR

The extraterrestrial solar radiation is influenced on its way to the earth's surface by absorption, scattering, direct reflection at clouds and refraction.

Spectra of the absorptivity of the main constituents of the

atmosphere, and the atmosphere as a whole are given in Fig. 2.12. The most important absorbers of radiation in the atmosphere are: oxygen, ozone, carbon dioxide and water vapour. However, the atmosphere is largely transparent between A 0.3

u m and

0.7

u m.

With increasing wavelength, more or less sharply defined absorption bands alternate with relatively transparent zones. These transparent zones, also known as "windows", are of great importance for remote sensing.

41

31

.r

>

.r

c,

a 0 & I VI

n

4

0 1

0 1

0 1

0 1

0 0.

Fig. 2.12

Spectra of absorptivity of the atmosphere and the atmosphere as a whole (modified after Barrett and Curtis, 1976; originally Fleagle and Businger, 1963).

Scattering by

atmospheric particles

alters

the direction of

solar

radiation in a random way.

Its impact is related to the wavelength of

radiation, the diameters of

the particles, and the optical density of the

atmosphere as well as its absorptivity. The three common types of scattering are (Barrett and Curtis, 1976):

-

Rayleigh scattering, which refers to interactions of solar radiation with molecules and other tiny particles with diameters much less than the incoming radiation;

-

Mie scattering, which is active in the presence of spherical particles

whose diameters approximate the wavelengths of the incoming radiation, e.g. small water droplets (slightly overcast sky) and dust particles;

-

Non selective scattering, which occurs when particles with diameters several times the wavelengths of the incoming radiation are present, e.g. large water droplets (clouds, fog).

Rayleigh scattering helps to explain the dominance of blue in a clear sky and

42

of orange and red at sunset. It is characterized by an inverse fourth power dependence on wavelength (preferential re-emission).

Blue light ( 4 7 0 nm) is

scattered about four times as much as red light (650 nm).

Clear skies,

therefore, show up in blue, owing to the strong scattering of short wavelength radiation. At sunset, the short wavelength is cut out mainly by powerful scattering due to the great pathlength through the atmosphere, and only the long wavelength radiation (including yellow, orange and red) reaches the earth's surface. In Mie scattering, the scattering properties of particles with identical absorption are determined by the R/X ratio (radius over wavelength ratio). The so-called Mie extinction coefficient u (extinction

OK

attenuation due to

scattering and absorption), is equal to the product of the number of particles (N)

times the extinction cross-section:

u= N K

(2

nR2

-

30)

where K = the extin tion fa

or, KnR2 = the extinction cross-section. The wavelength dependency in Mie scattering is different from that in Rayleigh scattering. In contrast to the latter, 'Mie scattering tends to influence longer wavelengths. Generally, both are active, and, depending on the particular atmospheric condition the colour of the atmosphere can range from blue to nearly white. Non-selective scattering causes all wavelengths of the Visible radiation to scatter with equal efficiency.

whitish, since a mixture of

As a consequence clouds and fog appear

all colours in approximately equal quantities

produces white light. Differences in intensity of solar radiation at the surface of the earth may be due to one or more of the following aspects (see Robinson, 1966 and Gibson, 1978) :

-

variations in the radiant emittance of the sun; variations in the distance between earth and sun; amount of water vapour in the atmosphere; dustiness of the atmosphere; altitude of the sun depending on latitude and time o f day;

43

-

elevation of the surface. The amount of water vapour and the dustiness of the atmosphere may be

expressed by the optical transmittance, while the altitude of the sun and the elevation of the surface are factors which determine the path length through the atmosphere. Yost and Wenderoth (1969) discuss the spectral distribution with time of day and with atmospheric conditions at Davis, California on 31 July 1967. From Fig. 2.13,

the wide variation i n spectral distribution which may occur

during a clear day is evident. There is a relative increase i n transmitted Infrared radiation at 750 nm in the afternoon (16.00

and 17.00)

as compared

with that i n the morning. This is thought to be caused by strong scattering of the Visible radiation by relatively large dust particles which have been churned up in the fields during the day.

m v ) Q L W a J

m c , I a J O

E

L

O

u .-

s m

E

C

C

\

'7

N

h L

m-.

140

1

t i m e o f day

- - 09.30

....... 09.55

120

u p p e r c u r v e 12.05

100

----I600

-1zoo

E U

80

s W

aJ

60 40 20

0 350

450

550

650

750

850

950

1050

1150

Wavelength i n nanometers Fig. 2.13.

Spectral distribution of incident solar radiation (during a clear day, 31 July 1967) at Davis, California, after Yost and Wenderoth (1969). Reprinted from 'Remote Sensing in Ecology', edited by Philip L. Johnson, 0 1969 the University of Georgia Press. Reprinted by permission o f the University of Georgia Press.

It will be evident that the spectral distribution with respect to the local conditions have to be taken into account in quantitative studies on remote sensing.

44

The spectral difference between direct

solar radiation and diffuse

skylight, which is the o n l y illuminant of shady areas, is illustrated in Fig. 2.14.

The shady areas are low-intensity regions with a spectrum that shows a

maximum in the blue region. Sensing in the blue may therefore reveal specific properties in these areas. V I V )

c , L

I

c , a J

/-.‘. ., \

\

c . ‘rNE

x u

I

60-

./ ‘\

I

L W S

0 S

\

I

m-.

c,

\

I

40

W -0 .r

u

-

S H

20

0

\

\ \

I I I I I

\ \ \

\

\

\

I

I I

I

\

,’--, \- 1

-

I

1

I

1

1

I

\

\ \ \ \

\

>

I

45

Furthermore, the high penetration capability of Microwaves for rain is evident from the data given in Fig. 2.16, e.g. and X

=

microwaves with X

=

3 cm at heavy rain

6 cm at excessive rain, only show 0 , 5 dB/km attenuation. This helps to

explain the enormous advantages of the application of aequatorial areas with tropical rainforest. Microwaves

4

--

radar in the wet

Infrared

-

wavelength (m)

1 cm

10 cm

1 mm

100 pm

10 pm

500 200 100 50

20 10 5 2

1

0.5

0.2 0.1

0.05 0.02 0.01

2 3 5

10

1o 2

lo5 Frequency ( GHz)

Fig. 2.15

2.9

Atmospheric attenuation (dBkm-l) for a horizonta path at a temperature of 293 K and a watercontent of 7.5 gm-' (Krul, 1982; derived from Preissner, 1978); dB = 10 log Pl/P2, where P1 = power top atmosphere and P2 = power after passage of 1 km atmosphere.

Energy balance With the information given in the previous sections, a two-dimensional

model on the interaction of solar radiation with the earth's surface can be composed; such a model is given schematically in Fig. 2.17.

-

46

Microwaves

4

-

Infrared

Wavelength (m) 1 cm

1 0 cm

L 0

r

m L 0 + h

E

. .. m

100 pm

1 mm

10 pm

50 20 10 5

Y

-0

v

K

2

1

0 .,-

c,

m

3 K

aJ

c, c,

m

u

+ .C

.r

V a W

wl

2 3 5

10

1o3

1 o2

lo5 Frequency (GHz)

Fig. 2.16

Atmospheric attenuation for different rain intensities and for f w or drizzle conditions ( K r u l , 1982; derived from Preissner, 1978).

On its way down to the earth's surface, the incoming solar radiation is altered by the various processes active in the atmosphere. The radiation which reaches the earth's surface under clear weather conditions, is composed of a direct and a diffuse component. Interaction with objects at the earth's surface causes

the

incident

radiation

to

be

reflected,

refracted,

absorbed

or

transmitted. The absorbed energy can be reradiated (emission). The interaction process is guided by the following principle: the energy sum of the different components active in the interaction is equal to the sum of the incident energy. However, over a certain period of time, there can be a gain in radiation upon interaction, the so-called net radiation which is composed of the following components (Janza, 1975):

(k in

wm-2),

47

J

transmission

Fig. 2.17 Two dimensional interaction model of solar radiation with an object at the earth’s surface. R,

=

where

Ris

+

Ris

Rid

+

Rit

-

[ P (Ris

+ Rid) + Rot 1

= incident direct solar radiation (Wm-’);

Rid

=

incident diffuse solar radiation (Wm-’);

Rit

=

incoming longer wavelength radiation (Wm-’) ;

Rot

=

outgoing longer wavelength radiation (Wm-*) ;

p

= reflectance of the surface.

(2

-

31)

48 The net radiation is used for a number of processes (Janza, 1975): S

Q =

+

A

+

LE

+

P

+M

( 2 - 32)

where S

=

A =

heat radiation from or into the soil ( ~ J I I I - ~ ) , heat radiation from or into the air (Clm-2 ),

LE = radiation used for evapotranspiration (Ilm-2), P = radiation required for photosynthesis (Wm-2), M

=

radiation required for miscellaneous conversions (Wm-2).

2.10.

Spectral reflectance By way of introduction to chapter 3, spectral reflectance is treated

below by giving a summary of spectral features. The spectral reflectance is the ratio of the radiant energy within a specific wavelength range reflected by a body, to the incident energy within the same wavelength range. Spectral reflectance curves may be used to indicate spectral properties. The curves may be characterized by features like absorption maxima, denoted below as bands. A summary of these features in the 0.4-2.5 given in Fig. 2.18.

um wavelength region is

The bands found in this spectral range are related to the

presence of H20, Fe(II),

Fe(III),

OH'

OK C03"

in solid matter (see Fitzgerald,

1974). The bands generated by electronic processes (see par. matter are generally broad and

OCCUK

2.4)

in solid

in the Ultraviolet, extending less

frequently into the Visible and near Infrared with a band at 1.1 m as a limit. The ground state of ferrous iron in an octahedral electrical field splits into two levels. The transition allowed between these levels gives rise to the band at 1.1 urn. Transitions between the remaining levels of ferrous iron do only result in very weak bands at 0.43 urn, additional

band

can be

0.45 urn, 0.51 !m and 0.55 um. Furthermore, an

produced

at

1.8-1.9

urn

in a

highly

disordered

octahedral site. Ferric ion has a ground state that will not split in any crystal field. Transitions to higher levels appear only weakly in the spectrum, e.g.

at

0.4 urn and at 0.7 urn. Other transitions 3re observed at 0.45 m, 0.49 m and 0.87 urn.

Fy

49

..... .. ..... ..

0.4 pm

I

1

I

I

I

1

I

1 .o

0.8

0.6

- o f C O i

OH ' Fp'

Fe"'

FQ

!!! I! ! H-0

HO ,

I'

I'

I . . +

O H ' OH' 1

1

L

A 9

1.0

pm

1.5

strong

Fig. 2.18.

1

weak

I

1

'

2.5

2.0

b r o a d band

I

s h a r p band

Absorption bands due to electronic and vibrational processes in the - 2.5 urn wavelength range of the EMS.

0.4

The bands produced by vibrational processes in solid matter are relatively sharp. The vibrational features observed in reflectance spectra in the Visible and near Infrared are due to overtones or combination tones of H 2 0 , C03".

OH'

and

The fundamental vibrational bands can be found in the mid- and far

Infrared. Overtones occur when a fundamental mode is excited with two or more quanta. Combinations occur when two or more fundamental modes and/or overtones of different modes are added or subtracted. Water molecules may occur at various sites in minerals:

-

as free molecules in small interstices or pockets (e.g.

in quartz);

- singly or in clusters as a part of the crystal lattice (e.g. gypsum); - in specific sites in the crystal lattice without being essential to its structure (e.g.

in zeolites);

- physically adsorbed at the surface of mineral grains and between the layers of layer-silicates. The variety in sites also leads to a variety in frequencies of the fundamental modes. In the near Infrared, two water absorption bands occur at 1.4 urn and

1.9 um, respectively, due to overtones or combination tones of the water fundamental. When these bands are sharp, the water molecules are supposed to be located in well defined ordered sites. Broad bands indicate the water

50

molecules to be relatively unordered and at various sites. the hydroxylgroup, the OH stretching mode, results in

The vibration of bands at 1.4 um and 2.8

vm. Combination of the OH stretching mode (at 1.4 m)

with lattice vibrational modes, produces a band at 2.2 Itm. Layer-silicates oriented.

and

Variation

micas in

the

show OH-groups orientation of

which

are

strongly direction-

the OH-groups, due

to

Si-A1

substitution, produces a broadening of the band at 1.4 Lim. I ,

Furthermore, overtone and combination tones of internal vibrations of C03 anion radical, or with the lattice vibrations, result in bands between 1.6

~m

and 2.5 Lim. Data on spectral features covering most of the Infrared region are given by Kahle et al., (1980) and Siegal et al., (1980). A summary is presented in table 2 . 3 .

Interesting is the possibility of detecting gypsum by using near

Infrared radiation. Silicates show

intense absorption

due

to

the

silicon-oxygen

Stretching

vibration at 10 um. However, at the onset of this absorption band at 7-9

m,

they show a peak in reflection. Below, some attention is paid to an important constituent of soils: organic matter. Schmitzer et al.,

(1972) and Flaig et al.,

(1975),

present

data on the spectral reflectance of soil organic matter. Soil organic matter is composed o f : a)

nonhumic substances such as carbohydrates, proteins, peptides, aminoacids, fats, waxes, resins and pigments;

b)

humic substances being humic acids, fulvic acids and humins.

The assignment of specific absorption bands is limited by the fact that in most cases, soil organic matter consists of mixtures of complex molecules, and therefore shows overlapping of absorption bands. To get an impression of its complexity, the main Infrared absorption bands of humic acids are given in table 2.4.

In addition to the modes

presented in this table OH and Si-0-Si are frequently found in soil organic matter. The utility of the bands in table 2.4 has to be tested for remote sensing. 2.11. Conclusions EMR may be generated by a change in electronic energy levels and by

changes in the vibrational and rotational energy of atoms, ions and molecules. It occurs in wave trains or bursts of radiation that carry a radiant energy

51 Table 2.3 Summary on vibrational features according to Siegal et al., (1980). bands in m

Constituents modes symmetric stretch asymmetric stretch H-0-H bend stretching fundamental Al- OK Mg - OH bend Al - OH bend fundamental Fe-0 fundamental stretching

H2O OH' oxides hematite carbonates phosphates sulphates gypsum

overtones and combination of OH stretching in molecular water fundamental bending mode of constitutional water Si-0 bending Si-0 stretching H-0-A1 bending Si-0-Si, A1-O-Si stretches Si) stretch (Si, A l ) - O - ( A l , deformation and bending modes of 0 - ( A l , Si)-0, (Si, Al)-0-(Si, Al), O--(Al. Si)-O.~ Al, Si-0-metal valence stretching

silicates

Table 2.4

3.106 2.903 6.08 2.77 2.2 OK 2.3 11 5 20 7, 11-12, 13-15 9.25, 10.3, 18, 28.5 9, 10.2, 16, 22.2 1.75,

2.3

6

around 5 10 11 12-15 15-20

20-40 20-40

Main Infrared absorption bands of humic acids after Flaig et al., (1975).

modes

-

bands in um

C-H C-H, C-H2, C-H3 carboxylate ion

3.25-3.30 3.39-3.50 3.50-4 .00 5.80-6.10 6.10-6.3 1 6.50 6.60 6.80-7.0 5 7.20-7.50 7.80-8.80

c=0 c=c NO C=Z C-H deformation salts of carboxylic acids

co

which is proportional to the frequency and inversely proportional to the wavelength.

Two laws of radiation for black bodies are formulated: 1)

the total of

radiation emitted from a black body is proportional to the fourth power of its

52

absolute temperature; 2) the wavelength of the maximum radiant emittance of a black body is inversely proportional to its absolute temperature. There is a spectrum of

EMR with wavelength regions such as Ultraviolet,

Visible, Infrared and Microwaves. The particular zones are essential for life (Visible and Infrared) or are made use of for practical reasons (Microwaves and Radiowaves). Solar irradiance has its maximum at approx 0.5 um. Terrestrial emittance shows a maximum which is located at approx 10 um, and has a very low energy level as compared to solar irradiance. The atmosphere modifies solar radiation by absorption

and

scattering

before

it

reaches

the

earth's

surface.

The

absorption by atmospheric particles is relatively strong in the Infrared, but some wavelength zones are relatively free of absorption. These are known as windows and are of much importance to remote sensing. Spectral reflectance may reveal specific properties of materials at the earth's surface. However, the atmospheric windows determine its potential use in remote sensing.

2.12.References Barrett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and Hall: 336 pp. Coulson, K.L., 1966. Effects of Reflection Properties of Natural Surfaces in Aerial Reconnaissance. Applied Optics, Vol 5, No 6: pp. 905-917. Dekker, A.J., 1958. Solid State Physics. London, MacMillan h Co Ltd: 540 pp. Fitzgerald, E., 1974. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Spectral Properties of Materials. ESRO CR-232, Neuilly, France: 231 pp. Flaig, W., Beutelspacher, H. and Rietz, E., 1975. Chemical Composition and Physical Properties of Humic Substances in Soil Components V o l . I. Organic Components (ed. Gieseking, J.E.). Springer Verlag, New York: 213 PP. Fleagle, R.G. and Rusinger, J.A., 1963. An Introduction to Atmospheric Physics. Academic Press, New York. Gibson, H.L., 1978. Photography by Infrared. Its Principles and Applications. John Wiley h S o n s , New York: 545 pp. Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology. European Space Research Organisation: 186 pp. Jamieson et al., 1963. Infrared Physics and Engineering. McGraw Hill. Janza, F.J., 1975. Interaction Mechanisms. Chapter 4 in Manual of Remote Sensing. Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 75179. Jenkins, F.A. and White, H.E., 1957. Fundamentals of Optics. McGraw-Hill Book Cy, Inc., New York: 637 pp. Jordan, E.C., Balmain, K.G., 1968. Electromagnetic waves and Radiating

53 Systems. P r e n t i c e - H a l l I n c . , New J e r s e y : 753 pp. Kahle, A.B. and Rowan, L.G., 1980. E v a l u a t i o n of M u l t i s p e c t r a l Middle I n f r a r e d A i r c r a f t images f o r L i t h o l o g i c Mapping i n t h e East T i n t i c Mountains, Utah. Geology. The Geol. SOC. of Amer., B o u l d e r , Colorado: pp. 234-239. K r u l , L., 1982. F y s i s c h e Aspecten van d e A a r d o b s e r v a t i e w a a r b i j d e nadruk l i g t op h e t systeem. A g r i c u l t u r a l U n i v e r s i t y , Wageningen, The N e t h e r l a n d s . PAO-cursus " T e l e d e t e c t i e i n landbouw e n n a t u u r b e h e e r " : 1 1 pp. Leu, D . J . , 1977. V i s i b l e and Near I n f r a r e d R e f l e c t a n c e of Beach Sands: A s t u d y on t h e S p e c t r a l R e f l e c t a n c e / G r a i n S i z e R e l a t i o n s h i p . Remote S e n s i n g of Environment 6, E l s e v i e r N-Holland: pp. 169-182. L i l l e s a n d , T.M. and K i e f e r , R.W., 1979. Remote S e n s i n g and Image I n t e r p r e t a t i o n . John Wiley & Sons, New York: 612 pp. 1976. Remote S e n s i n g of Environment, AddisonL i n t z , J.Jr. and S i m o n e t t , D.S., Wesley Publ. Cy., Reading, M a s s a c h u s e t t s : 694 pp. P r e i s s n e r , J., 1978. The I n f l u e n c e of t h e Atmosphere on P a s s i v e R a d i o m e t r i c Measurements. AGARD C o n f e r e n c e Proc. No 245: pp. 48.1 - 48.14. P r i n s , J.A., 1955. G r o n d b e g i n s e l e n van d e hedendaagse Natuurkunde. \ J o l t e r s , Groningen, Nederland: 320 pp. R e e v e s , R.G., 1975. G l o s s a r y i n Manual of Remote S e n s i n g Vol. 11.. Amer. SOC. of Photogrammetry, F a l l s Church, V i r g i n i a ; pp. 2061-2210. Robinson, N. ( e d . ) , 1966. S o l a r R a d i a t i o n . E l s e v i e r Publ. Cy., Amsterdam: 347 pp. Schawlow, A.L., 1968. Laser L i g h t . S c i e n t i f i c American. Vol. 219, n r . 3: pp.

120-136. 1972. Humic S u b s t a n c e s i n t h e Environment. S c h m i t z e r , M. and Khan, S.U., Marcel Dekker, New York: 327 pp. 1980. Grootheden e n Eenheden i n de Landbouw e n S c h u r e r , K. and Rigg, J . C . , B i o l o g i e . Pudoc, Wageningen, The N e t h e r l a n d s : 121 pp. S e l l e r s , W.D., 1965. P h y s i c a l C l i m a t o l o g y . Univ. of Chicago P r e s s , Chicago. S i e g a l , B.S. and G i l l e s p i e , A.K., 1980. Remote S e n s i n g i n Geology. John Wiley & Sons, N e w York: 702 pp. Ulaby, F.T., Moore, R.K., Fung, A.K., 1981-1982. Microwave Remote S e n s i n g Vol. I and I1 Addison-Wesley P u b l . Cy., London: 1064 pp. Weast, R.C. (ed.), 1974. Handbook of Chemistry and P h y s i c s . CRC P r e s s , C l e v e l a n d , Ohio. W e i s s k o p f , V.F., 1968. How l i g h t i n t e r a c t s w i t h Matter. S c i e n t i f i c American, Vol. 219, n r . 3: pp. 60-71. Y o s t , E. and Wenderoth, S., 1969. E c o l o g i c a l A p p l i c a t i o n s of M u l t i s p e c t r a l C o l o r Aerial Photography. In: Remote S e n s i n g i n Ecology e d . by P.L. Johnson, Athens, Univ. of G e o r g i a P r e s s : pp. 46-62. 2.13.Additional

reading

1964. Thermodynamics. Pergamon P r e s s , London: 287 pp. Bazarov, I.P., R.I.P.M., 1977. The I n t e r n a t i o n a l System of U n i t s (S.1.). 3rd edn. H.M.S.O. London. I.S.B.N. 0-11-480045-6: 54 pp. C o l w e l l , R.N., 1963. Report of Subcomm. I. B a s i c M a t t e r and Energy R e l a t i o n s h i p s I n v o l v e d i n Remote S e n s i n g Reconnaissance. American S o c i e t y of Photogrammetry: pp. 761-809. D i t c h b u r n , R.W., 1976. L i g h t . 3rd edn. Vol. 1 and 2. Academic P r e s s , London 775 pp. Feynman, R.P., L e i g h t o n , R.B. and Sands, M., 1970. The Feynman L e c t u r e s on P h y s i c s . Mainly Mechanics, R a d i a t i o n and Heat. 5 t h edn. Adison Wesky Publ. Cy, Menlo P a r k , C a l i f o r n i a .

54

Heel, A.C.S. van and Velzel, C.H.F., 1967. Wat is licht? Wereldakademie, W. de Haan/J.M. Meulenhof: 245 pp. Goody, R.M., 1964. Atmospheric Radiation. Oxford, Clarendon Press. Holz, R.K. (ed.), 1973. The Surveillant Science. Remote Sensing of the Environment. Houghton Mifflin Cy, Boston: 391 pp. Kronig, R. (red.), 1962. Leerboek der Natuurkunde. Scheltema & Holkema N.V., Amsterdam: 891 pp. Longhurst, R.S., 1962. Geometrical and Physical Optics. Longmans, Green and Co. Ltd London: 551 pp. LOOK, G.P., de, 1983. The Dieletric Properties of Wet Materials. IEEE Trans. on Geoscce and Remote Sensing, Vol. GE-21, No. 3: pp. 364-369. Meyer-Arendt, J.R., 1972. Introduction to Classical and Modern Optics. Prentice-Hall International Inc., London: 558 pp. Monteith, J.L., 1973. Principles of Environmental Physics. Edward Arnold (publ.) Ltd, London: 241 pp. Peake, W.H. and Oliver, T.L., 1971. The Response of Terrestrial Surfaces at Microwave Frequences. Ohio State Univ. Electroscience Lab., Tech Rep. AFAL-TR-70- 301. Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. American Society of Photogrammetry. Falls Church, Virginia. Vol. I: 867 pp. 1974. Remote Sensing. A better View. Duxbury Press, North Rudd, R.D., Scituate, Masachusetts: 135 pp. Wade, F.A. and Mattox, R.B., 1960. Elements of CKystallOgKaphy and Mineralogy. Harper & Brothers Publ., New York: 332 pp. Wahlstrom, E.E., 1954. Optical Crystallography. 2nd edn., New York, John Wiley & Sons Inc.: 247 pp. White, D.C.S., 1974. Biological Physics. Halsted Press. New York: 293 pp.

55

DATA ON INTERACTION OF SHORT WAVE ELECTROMAGNETIC RADIATION WITH NATURAL

3.

OBJECTS.

In

this

chapter,

emphasis

is

given

to

the

results

of

laboratory

measurements on reflectance and thermal parameters. The ranges of the EMS covered are those between 0.4-2.5

urn and

8-14

um

, which form important

portions of the spectra of solar irradiance and earth emittance. In par. 3.1,

minerals as constituents of rocks and soils are discussed. Later

on in par. 3.2,

being

the reflectance and thermal properties of soils are dealt with,

highly

influenced

by

moisture

condition,

organic

matter

content,

structure and texture. A summary on the properties of plants and plant canopies is given in par. 3.3. Laboratory

measurements

combinations

of

these

normally

concentrate on

representing part

of

the

individual components

or

natural variation.

The

laboratory details have to be transformed to the assemblage of components as depicted by remote sensing aids (par.

3.4).

This chapter, therefore, is a

transition between interaction theories (chapter 2)

and remote sensing data

such as given in the chapters 9-11. 3.1.

Interaction of short wave radiation with minerals and rocks.

sF!ectELrerlect2_nce Minerals occur in cemented granular form in duricrusts and hard rocks or in loose granular form in unconsolidated sediments, rotten rock and soils. A comprehensive text on the Visible and Near Infrared spectral features of minerals is given by Hunt, Salisbury et al., (1970-1976).

A summary of part of

their work is provided by Fitzgerald (1974). Below a brief treatise is given on the spectral properties in the Visible and Near Infrared of dominant minerals such as:

-

quartz and feldspar; amphibole and pyroxene; mica and layer-silicates; limonite; carbonate and gypsum. Quartz shows a very high reflectance and the spectrum in the Visible and

near Infrared

is almost devoid of spectral features (such as absorption maxima

denoted as bands), unless impurities occur. The same is true for feldspar.

56

Only, water-bearing fluid inclusions and contamination by iron result in spectral features. Amphibole shows a band near 1 urn,

indicating that it contains ferrous

ions. It displays a very sharp hydroxyl band at 1.4 um and less sharp bands between 2.0 um and 2.5 urn. The latter are due to overtone and combination tones of

the OH stretch. The bands mentioned are characteristic for the variety

Tremolite. Another variety, Actinolite, shows in addition a broad band near 0.7

wn due to

the presence of ferric ions (see fig. 3.1.a). Pyroxenes do not show the hydroxyl bands unless some alteration has taken place. The relatively high content of

iron is expressed by a broad band at

0.9 um, and in the variety Hypersthene by an additional broad band at 1.8

rn

which is probably due to ferrous ions in a highly disordered octahedral site (see fig. 3.1.b). Amphibole, v a r . A c t i n o l i t e

Pyroxene, v a r . Hypersthene

8

v

a, S V

rn +

50-

7

le E a,

0

,

I

I

1

I

A Fig.

3.1

I

I

I

h

A i n pm

i n pm

(a) (b) Reflectance (relative to MgO) of Amphibole, var. Actinolite, and Pyroxene, var. Hypersthene; grain size 74-250 prn (after Hunt and Salisbury, 1970).

The mica var. Muscovite displays hydroxyl bands at 1.4 pm as well as between 2.2

um and 2.6 um.

Biotite may show a much broader hydroxyl band and in

addition shows a very broad band in the 0.6

to 1.5 urn region, due to ferrous

and ferric ions. Layer-silicates are characterized by hydroxyl bands centered near 1.4

~rm

and 2.2 D m. Absence of appreciable amounts of bound water is typical for Kaolinite. Therefore, it shows only a weak band at 1.9 u m (fig. 3.2.a).

On

the contrary

57

Montmorillonite is capable of holding much water and may show very strong bands at 1.9 um as well as at 1.4 u m (see fig. 3.2.b). also a waterband, where as the bands at 0.9

u m is u m are due to the

The band near 1.15

u m and 0.5

Kaolinite

Montmorilloni te

1

0.5

1.0

1.5

2.0

2.5

1

I

I

0.5

1.0

1.5

I

2.0

A in p m

Fig. 3.2

I

I

2.5

A in prr

Reflectance (a) (relative to MgO) of Kaolinite ( b ) and Montmorillonite; resp. with grainsize 0.1-5 u m and 0.1-74 u m (after Hunt and Salisbury, 1970)

presence of ferrous ions. Limonite is often used to indicate hydrated ferric oxide material while goethite is synonymous for the ferric oxide hematite. The water content of limonite is variable. The band at 0.9

u m typical of the ferric oxides and

hydration bands near 1.4 u m and 1.9 u m may show up in the spectra. Calcite exhibits carbonate bands between 1.8 u m and 2.5 display a very weak hand of ferric ion

at

0.8

LI

m, and may

u m. The latter may be due to

iron contamination in often very small amounts. Fine grained calcite has a very high reflectance as is shown in fig. 3.3. 2.35

Note the strong absorption band at

u m.

Gypsum shows bands at 1.8 LI m and at 2.3

LI

m, due to overtones and combination

of OH stretching in molecular water. If we consider rocks, we mostly have to deal with an assemblage of minerals, and various spectral features will occur e.g.

limestones may display

carbonate bands as well as water and hydroxyl features, being dependent on the admixture of constituents such as layer-silicates. Features due to the presence of ferrous ions (intrinsic to the presence of clay) and ferric ions (coatings)

58 may also

OCCUK.

emissivity -Spectral ----------------The spectra of emitted thermal radiation from minerals are generally characterized by emissivity minima in the 7-15

!J

m region. These minima are

known as the "reststrahlen" bands and are due to vibrational transitions of the

m

c,

u W

+ 7

Fig.

50-

Reflectance (relative to MgO) of Calcite of grain size 74-250 m (after Hunt and Salisbury, 1971).

3.3

main anion of the mineral.

In silicates, the fundamental frequency of the Si-0 stretching mode occurs near 10

!J

m and the 0-Si-0 bending or deformed ion mode is found near 20 IJ m.

The fundamental Si-0 vibration near 10 rock.

!J

m shifts with the type of igneous

Quartz shows an emissivity minimum at 9

!J

m, which is the shortest

wavelength of any emissivity minimum of silicates. The spectral emissivity of a number of igneous rocks is given in fig. 3.4.

From

this figure, we can read that the examples given of acid-igneous rocks have emissivity minima from 8.8 to 9.6

u m (e.g.

granite near 8.80 p m), while

those of basic and ultrabasic igneous rocks have emissivity minima higher than 10.1 !Jm (e.g.

Limburgite 10.53 IJ m).

The intermediate igneous rocks show minima

between 9.2 and 10.0 u m. To discriminate silicates from non-silicates, the spectral emissivity may be used.

For example, carbonates show, much contrast with silicates in having

strong absorption at 7.0

iI

m.

The diurnal variation in surface temperature changes of rock formations is

59 the most significant short term variation in rock properties that can be used in remote sensing. The difference in the amplitude of the diurnal variation in temperature between rocks is due to their differences in thermal inertia. The thermal inertia (2-29)

is a function of the thermal capacity and conductivity

as influenced by porosity, texture, structure, chemical composition and

>

c, .I-

>

Andesi t e Nepheline Syenite

.I-

In In .I-

E

W

INTERMEDIATE ROCKS

7

m L

Hypersthene Andesi t e

c,

u

~

W

n

Quartz D i o r i t e Augite D i o r i t e

Ln

L 1.1

1

D i or it e - - --e Aug - -it -

I

BASIC ROCKS

Basalt

- - - - - - - - -1- -

%

Perid o t i t e Serpentine

___-------I

Fig. 3 . 4

1

1

8

9

I

I

,

1

,

10 11 1 2 1 3 pm

Spectral emissivities of Lyon, 1965)

i

ULTRABASIC ROCKS Limburg it e

10.53

igneous rocks from 8-13 m (modified from

60 moisture content. The day-night temperature difference can be used to calculate the thermal inertia of surface materials. 3.2

Interaction of short wave radiation with soils. The interaction of solar radiation with soils plays an important part in

soil forming processes and more specific in the heat balance of soil. The dry/wet soil colour designations are actually observations on spectral reflectance, which may indicate the presence of organic matter and of oxidized OK

reduced iron compounds. Although

soils are composed of granular mineral materials which are

generally mixed in their surface layers with organic matter, their reflectant and emittant properties are greatly influenced by moisture condition, texture and structural arrangement of the constituents which often predominate over the effects of chemical composition. Spectral reflectance _____-------__-----Several authors have provided spectral reflectance data of soil materials which have been obtained under laboratory conditions (Orlov, 1966; 1969-1970;

Skidmore

et

al.,

1975;

Gold

and Asher,

1976).

Planet,

I will first

concentrate on spectral features which are due to chemical soil composition: Obukhov and Orlov (1964) present some curves in the spectral zone from 0.40 to 0.75

um, of which the results are given in fig. 3.5. Three types of curves are distinguished in this wavelength range:

a) monotonously rising curves, from short to longer wavelengths; the slope of the curves becomes somewhat weaker at the longer wavelength end (fig. 3.5 nrs 1, 3 and 6);

b) a curve with minor slope and low reflectance values (fig. 3.5

nr. 4 ) ; the

low reflectance values apparently are due to the high content of organic matter; c) the type of curve represented by nr. 5 in fig. 3.5; increases at a moderate rate up to about 0.53

LI

the slope of the curve

m and then rises sharply to

about 0.58 u m, where a definite decrease of slope occurs; this type of curve is typical for samples rich in ferric ion, which show absorptance in the shorter wavelength range and high reflection in the orange and red. For further discussion on types of curves, one is referred also to Condit (1972),

who gives special reference to American soils.

61

3.5

Fig.

Spectral reflectance data of Russian soils (modified sketch after Obukhov and Orlov, 1964). 1. 2. 3.

4.

5. 6.

* Valuable

Sod-podzolic soil, A1 0-10 cm; OM* 1.6 %; clay loam. Grey Forest soil, A1 15-26 cm; OM* 3.8 %; silty clay loam. Light Chestnut soil, A1 0-10 cm; OM* 2.7 %; clay loam. Chernozem, Asod 0-5 cm; OM* 10.3 %; silty clay loam. Red coloured soil on limestone, A1 4-11 cm; OM* 3.2 %; clay. Light coloured Sierozem, A1 0-10 cm; OM* 1.1 %; clay loam. OM or organic matter content.

information about

the composition of

soils may

be

obtained by

extending our view into the near Infrared. Soil reflectance spectra including the near Infrared (as well as the Visible) are reported by several authors: Bowers and Hanks (1965), (1975),

Mathews et al., (1973),

Janse and Bunnik (1974), Damen

Janse et al., (1976) and Girard (1977).

Numerous reflectance measurements of American soils in the 0.52-2.32 wavelength range have been presented by Stoner et al.,

(1980).

pm

It has been

pointed out that soils rich in organic matter (Histosols, Mollisols) frequently have a concave shaped reflectance curve between 0.5 soils low in organic matter (e.g.

Alfisols)

P m and 1.3

P m, whereas

frequently show convex shaped

curves over the same wavelength region. Ultisols often resemble the curves of Alfisols but they additionally show weak absorption bands at 0.7 0.9

P

and near

m caused by the presence of iron.

Besides the chemical composition, other soil properties such as moisture content, texture, structure and roughness of the soil surface have a marked influence on reflectance and thus have to be evaluated. The influence of soil moisture content on the reflectance of silt-loam as

measured by Bowers and Hanks (1965) is often cited in literature. I present

62

the curves in fig.

3.6.

The water absorption bands (1.4

clearly marked as well as a weak hydroxyl band (2.2 p m).

and 1.9

u m) are

Increase of soil

moisture content results in an overall decrease of reflectance in the Visible as well as in the near Infrared. Damen (1975)

states that soil moisture tension values are most suitable

for analysis of soil moisture, and presents spectral reflectance curves of soil material at different soil moisture tensions. The water absorption bands are clearly marked in the range of soil moisture tension form 0.005 bar up to 16 bar and the total reflectance, as can be expected, decreases with decrease of h

3

60

a, V

m

+J u

a,

G 40

20

0

V

I

U I

Fig.

3.6

1 obo

t h (nm) 2000 Wavelength

Spectral reflectance of Newtonia silt-loam at various moisture contents (moisture contents indicated directly above each curve) after Bowers and Hanks (1965).

soil moisture tension (fig. 3.7). the

I

macropores

of

soil

At low soil moisture tension, water fills up

(gravitational water)

and

strongly

reduces

the

reflectance. Cohesion and adhesion water, which can be held at high moisture tension in resp. micropores and at the surfaces of soil particles, have considerably less influence. In fig. 3.6

it is striking that the dips at 1.4 u m and 1.9

u m become deeper

and broader with increasing moisture content. Relatively sharp absorption bands are

characteristic of

low moisture contents and thus high soil moisture

tension. Another remark may complete the discussion about these interesting curves. The hydroxyl band at 2.2 um is most clear at low moisture contents (fig. 3.6);

at

high moisture contents, it becomes vague. Therefore, its use in the detection of layer-silicates may be restricted to relatively dry soils. Texture of soils has got attention in soil reflectance measurements, too.

63 h

d?

SMT

-

v

E60-

16

c

c m ,

u

a,

3,2 ....... ........... 0,5 / - - -

-

0,032

7

%

bar " " "

Fig. 3 . 7 Spectral reflectance in relation to soil moisture tension of a soil with a clay content of 9 . 3 X (after Damen, 1975).

Generally, fine textures show a higher reflectance than coarse textures. Leu (1977)

reports that the spectral response in the 0.43-0.47

!.I

m and 0 . 5 1 - 0 . 5 3 ~

channels is correlated with the grain size of beach sands having variable moisture contents. A means to determine the average size of particles may be found through application of high oblique illumination. The ratio of intenties at a forward angle to that at a back angle can be used for this purpose. For the same material (e.g.

quartz sand), the scattered light becomes more concentrated in the

forward direction with increasing particle size (Meijer-Arendt, 1972). Besides grain size, the reflectance of soils will also be influenced by aspects such as sphericity, roundness (Brewer, 1964) and the micro-roughness at the surface of the grains. Several authors report about

results of

reflectance measurements in

relation to aggregate size. Orlov ( 1 9 6 6 ) studied various soil samples with a range of aggregate diameters. In general, he found for small sized aggregates a decrease in reflectance with increasing diameter. Huwever, at large diameters (>

2.5 mm) there was only a slight or no decrease in reflectance.

Damen (1975) has also studied the influence of aggregate size on reflectance. Reflectance values of a loamy topsoil sample of Woudgrond with different

64

aggregate sizes are given in fig. 3.8. Furthermore, he studied soil roughness by creating fine and coarse rills on the surfaces of samples (fig. 3 . 9 )

and found the coarse rill pattern to show the

lowest reflectance.

It is evident, therefore, that the structural condition of the soil surface is of great influence on reflectance e.g.

soil surface crusts may cause high

reflectance values in the Visible (Cipra et al., 1971). Some authors report about the variation of reflectance with the angle at which the radiation is incident on the surface. Coulson (1966) gives a summary of previous research and presents results on directional reflectance of different mineral materials. Some of the curves are shown in fig. 3.10 (angle of incidence 0

-2 -Woudgrond 860S

cr u 1

.

u

............ .......

c

5 3 " ) . The reflectance is measured

( a i r dry)

0.3 m n ~

0.3-1 1 -2

Fig. 3.8

=

" "

Spectral reflectance at different aggregate diameters of Woudgrond (with 7.4 % C and 12.0 % clay) after Damen (1975).

hemispherically in the principal plane, that is the plane containing the source, the object and the measuring device. Materials with a low absorption like gypsum sand and beach sand (quartz) show a high reflectance and a strong forward maximum in scattering. Absorbent materials like clay, limonite, grey

limestone grit and loam show a back

scattering maximum (see also Fig. 2.10 with text). Note that the antisource point (the point just behind the source) is indicated in the figure by an arrow and by the break of data ( 8 factor

R

in the ordinate is a normalization factor.

of source is 53"). The

65 h

3 2 60C Q

CI

u

-

Woudgrond (air d r y )

small r i l l s medium r i l l s

-

a,

0 '

I

I

I

1000

I

2000 Wavelength (nm)

Fig. 3.9 Spectral reflectance of Woudgrond (with 7.4 %C and 12.0 X lutum) with fine and coarse rills after Damen (1975). The magnesium oxide surface which is used as a standard reflector is-assumed to

be a perfect Lambertian reflector. The reflectance of the standard surface, ( pst ) is independent of direction

and thus: Ist -1 I " The directional reflegtance p ( 8

I =

II

ISt and

p =

-=

,0)

is given by:

where p =

reflectance dependent on viewed nadir angle 0 of the reflectometer and position

0

of

the reflectometer with respect to the azimuth

0,

(principal plane) of the source; IO = intensity of the source; I and ISt are intensities of the radiation

=

180"

66

7

+

80

t

Red clay 60-

40-

D'

?

20-

Loam 80

40

0

40

@=OO Fig.

80 Nadir angle

(O)

4=180°

3.10 Directional

reflectance of various types of mineral surfaces 643 nm, 0 = 53" ) after Coulson (1966). (principal plane, h

Gypsum sand: Reach sand: Red clay: Limonite: Limestone: Loam:

translucent grains 0.1-0.5 mm translucent quartz grains 0.1-0.3 m 1 wn, aggregates 1-2 mm mean diameter 14 urn, range 3-40 um grey coloured rock crushed and graded to 1.2 cm size 1-5 pm, aggregates 50-1000 m.

reflected from the sample and from the standard surface respectively. Fig. 3.11 shows the directional reflectance of desert sand for radiation of different wavelengths and for different angles of incidence. There appears to be a strong increase of overall reflectance with increasing wavelength from 406 to 796 nm (fig. 3.11a),

which is in accord with the reddish COlOUK of

the

desert sand under consideration. The broad minimum reflectance near the nadir is a general characteristic of many surfaces. Apparently, the Lambert's cosine law (2-22),

which indicates a

hemispherical distribution is not valid for granular surfaces. Furthermore, the non-specular behaviour is evident at least in the forward direction, since the forward maximum is found at 0

> e0

( 0 =

e0

specular point).

The backscattering maximum will be due to surface reflection being composed of a diffuse component and a specular component. The latter component will be due

67 100

(a) ,

,

?

80

d

60

40

20

\'""

a, V

c fu

; 80

40

40

0

7

%

I

I

4J

80

80

I

I

I

0

40

80

0=l8Oo

O=O"

@=180"

I$=o"

I

40

CL

Nadir angle

I=

Fig. 3.11

("1

Nadir angle

Directional reflectance from desert sand after Coulson (1966): a) of five different wavelengths (principal plane, 0 = 53"); b) for three different angles of incidence (principa? plane, A nm)

.

to the presence of facets which are more

OK

=

("1

643

less oriented normal to the

direction of the incident radiation. The forward maximum for wavelengths between 492 nm and pronounced than the backscattering maximum (fig. 3.11a). for radiation with A presence

of

Fe

=

1025 nm is more

The opposite is true

405 nm. A possible explanation may be f o u n d in the

(III),

which

causes

absorption

and

strong

external

backscattering in this range. However, the same should apply to the radiation at 492 nm, which is not the case (for absorption, see Fig. 2.18).

Therefore,

the phenomenon is not completely understood. Both the total reflectance and the directional reflectance vary with the angle 0

at which the radiation is incident, as can be seen from fig. 3.11.b.

The variance is particularly pronounced at grazing angles.

In having the

highest reflectance at a grazing angle of 78,5", the surface acts in a non-

68

Lambertian way. The degree of

polarization of radiation reflected by desert sand in the

principal plane is shown in fig. 3.12. A maximum positive polarization (normal to

the principal plane)

was

found

120"

at

130"

to

from the antisource

direction, while vertical or negative polarization (parallel to the principal plane)

occurred

Furthermore,

a

in

the

region

considerable

surrounding

change

of

the

the

degree

antisource of

direction.

polarization with

wavelength is evident, the shorter wavelengths showing a higher degree (fig. 3.17.a).

40

(a)

(b)

30

20

10

0 -5

I

5

.r

+cc,

0

2

80

@=oO

I

1

40

0

40

80 @=180°

Nadir angle

Fig. 3.12

40

80

4.0"

("1

0

80

40 0=180°

Nadir angle ( " )

Degree of polarization of radiation reflected from desert sand after Coulson (1966) : a) for five different wavelengths (principal plane, 8 = 5 3 " ); b) for three different angles of incidente (principal plane, X = 492 nm) Degree of polarization = (Ih \/It, + $) X 100 ( % )

-

It appears that strongly reflected wavelengths are only weakly polarized, but high polarization is observed at wavelengths for which the reflectance is low

69 (compare

with

radiation

of

fig. a

3.11a).

Particles

particular

which

wavelength,

are

show

a

generally

high

reflectance

translucent

for

for that

r a d i a t i o n and c o n s e q u e n t l y have a h i g h c o n t r i b u t i o n of t h e i n t e r n a l component t o t h e t o t a l r e f l e c t a n c e . Thus any p r e f e r r e d o r i e n t a t i o n of t h e e l e c t r i c v e c t o r i s d e s t r o y e d by t h e i n t e r n a l ( m u l t i p l e ) r e f l e c t i o n .

On t h e c o n t r a r y , a b s o r b e n t

m a t e r i a l s have no o r only a s m a l l i n t e r n a l component and t h e r e f l e c t a n c e i s formed f o r t h e g r e a t e r p a r t by t h e c o n t r i b u t i o n of t h e e x t e r n a l component. Some f a c e t s a t t h e s u r f a c e w i l l produce t r u e s u r f a c e r e f l e c t i o n ,

which i s an

Consequently p o l a r i z a t i o n i s h i g h when a b s o r p t i o n

e f f i c i e n t polarizing agent. i s high ( s e e a l s o f i g . 2 . 7 ) .

In f i g . '3.12b, pattern

t h e e f f e c t of a n g l e of

shifts

with

source

i n c i d e n c e on p o l a r i z a t i o n i s shown. The

p o s i t i o n and

polarization i n the antisource-direction.

always

shows

vertical

or negative

Furthermore, t h e d e g r e e of p o l a r i z a -

t i o n i n c r e a s e s w i t h t h e a n g l e of i n c i d e n c e . Black loam s o i l ( w i t h a r e l a t i v e l y high c o n t e n t of o r g a n i c m a t t e r ) shows a low overall reflectance ( f i g . 3.13.a). in

Fig.

with

i n c r e a s i n g wavelength and a h a c k s c a t t e r i n g maximum

A c o m p l e t e l y o t h e r p a t t e r n a s conpared w i t h f i g .

3.13.h.

Although

b a c k s c a t t e r i n g maximum a t 8

the

total

=

53" and 8

reflectance =

78,5"

appears

'3.11h.

to

he

i s shown

lower,

i s f o r d e s e r t s a n d , w h i l e t h e forward maximum i s a l m o s t a b s e n t .

Fig.

shows

the

a

s t r o n g wavelength dependence and h i g h

wavelengths f o r b l a c k loam s o i l . 3.14.b.

The e f f e c t of

the

i s more pronounced t h a n i t

polarization changing 8

at

3.14.a shorter

i s shown i n f i g .

A s l i g h t s h i f t i n t h e n e u t r a l p o i n t s of p o l a r i z a t i o n toward t h e a n t i -

source-direction

may be noted f o r t h e b l a c k loam a s compared w i t h t h e d e s e r t

sand. It

will

be

evident

from

the

foregoing t e x t

that

there

o p p o r t u n i t i e s t o d i s c r i m i n a t e v a r i o u s s o i l s on t h e b a s i s of least

under

laboratory

conditions)

although

the

are excellent

reflectance (at

explanation

of

spectral

f e a t u r e s may be c o m p l i c a t e d .

---_------__

Thermal d a t a

The t e m p e r a t u r e of

a s o i l i s one of

i t s important p r o p e r t i e s i n c o n t r o l l i n g

Its

g e r m i n a t i o n of s e e d s , p l a n t growth and a number of s o i l forming p r o c e s s e s . importance

is

expressed

in

the

U.S.

Soil

Taxonomy

by

introducing

soil

t e m p e r a t u r e regimes i n t h e c l a s s i f i c a t i o n of s o i l s ( S o i l Survey S t a f f , 1975). The t r a n s f e r of h e a t i n t h e s o i l t a k e s p l a c e by c o n d u c t i o n through t h e s o l i d materials

and

across

the

pores

by

conduction,

convection

and

radiation

70

100

(b) 80

796ni

'I

60

't 40

L

m J 1

c,

-+ u al

80

1

1

1

40

0

40

I&$

ar

J

I

80 @=180°

80

I

I

I

I

40

0

40

80

Q=O"

@=180'

CL

Nadir angle

k

Fig. 3.13

('1

Nadir angle

('1

Directional reflectance of black loam soil after Coulson ( 1 9 6 6 ) : a) for four different wavelengths (principal plane, eo = 7 8 , 5 " ) ; b) for three different angles of incidence (principal plane, X = 6 4 3 nm)

together, as well as by latent heat transport (water vapour).

The effect of

soil mineralogical composition on the thermal behaviour may be evaluated from the emissivity values. In table 2.3, which,

in

the

8-14

carbonates, sulphates

a number of absorption bands are given,

pm region, are OK

due

to

the

presence

of

silicates,

phosphates. The effect of the composition of igneous

rocks on the emissivity

(E)

may be evaluated from Fig. 3.4.

composition may lead to difference in

E

of 0.15,

Difference in

while the emissivlty minimum

differs from the maximum by values of 0.15-0.3. E

values of soil materials for the spectra- region between 5 mn and 15 WI

are reported (by Idso e.a.,

1 9 6 9 ) to be from 0.95

for sand up to 0.97 for silty

clay and loam. Quartz sand shows a relatively low emissivity. Fuchs et al., ( 1 9 6 8 ) report fOt the socalled Plainfield sand the following values for three different moisture contents:

moisture content E

(emissivity)

0.7%

5.8%

8.4%

0.90

0.92

0.94

71

4[

I 0 '

3c

2c

10

0

-5

I

.l

I

I

I

I

I

I

I

0

40

1

80 @=180°

Q) 'r

Q)L

Nadir angle (")

s-m

Ez-,g

Nadir a n g l e (")

n a-

Fig. 3.14

Degree of polarization of radiation reflected from black loam soil after Coulson (1966) : a) for four different wavelengths (principal plane, 8 = 78,5"); b ) for three different angles of inciden2e (principal plane, b = 492 nm)

Monteith (1973) describes the thermal properties of soil as follows. If the volume fraction x of each component is expressed per unit volume of soil, one can write:

where s stands for solid, 1 for liquid and g for gaseous components of soil. The bulk density of a soil p ' is found by adding the weight of each component i.e.

p' =

where p x g g

pSxs + plxl + P x

g g

can be neglected.

( 3-3)

12

bulk specific heat C'.

It can be found by adding the specific heat (C) of the

soil components, as follows:

Van Wijk and de Vries (1963) present values on thermal properties of soils (which are also discussed by Monteith, 1973). They are given in table 3.1 (for definitions, the reader is referred to par. 2.7). The effect of soil composition on thermal properties can be evaluated to some Table 3.1

Thermal properties of soils and their components (after Van Wijk and De Vries, 1963) Density

Soil components Quartz Clay minerals Organic matter Water Air (20'C)

Specific Thermal heat conductivity

Therma 1 diffusivity

2.66 2.65 1.30 1 .oo 1.20~10-3

0.80 0.90 1.92 4.18 1.O 1

8.80 2.92 0.25 0.57 0.025

4.18 1.22

0.14 20.50

1.60 1.80 2.00 1.60 1.80 2.00 0.30 0.70 1.10

0.80 1.18 1.48 0.89 1.25 1.55 1.92 3.30 3.65

0.30 1.80 2.20 0.25 1.58 1.58 0.06 0.29 0.50

0.24 0.85 0.74 0. ia 0.53 0.51 0.10 0.13 0.12

1 .oo

Soils Water content g 0-3 Sandy soil (40% pore space) Clay soil (40% pore space) Peat soil (80% pore space)

0.0 0.2 0.4

0.0 0.2 0.4 0.0 0.4 0.8

extend from these data.

Quartz and clay minerals show similar density and

specific heat. Quartz sands tend to have larger thermal diffusivities than other soil types due to the high conductivity of quartz. Organic matter shows about half the density and more than twice the specific heat of quartz and clay.

Peat

soils

have

the

smallest

thermal

conductivity of organic matter is relatively small.

diffusivity,

because

the

73 Soil moisture is one of the most important factors influencing the thermal characteristics of soil. The thermal conductivity increases with increasing moisture content, but the increase becomes less marked with high moisture contents.

This

can be

components in table 3.1.

understood

if

one compares the data of the soil

The thermal conductivity of air is much lower than

that of water. Therefore, dry soils, in which air is filling the pores, have relatively low thermal conductivities. Raising moisture content will first result in much higher values due to the presence of thin waterfilms conducting the thermal energy. High moisture contents with a consequent almost complete filling of pores with water, only produces a slight increase in conductivity.

In dry soils, high porosity will lead to low thermal conductivity. The relation

! 40

!

20

30

I

I

50

60

! 70

80

Porosity

Fig. 3.15

(%I

Relation between soil porosity and thermal conductivity of dry soils after Chudnovski (1962).

Normally, the porosity of non-cultivated soils is at cultivated soils values of 40-60

30-40

%,

while in

% OK more are reached. Therefore, it may be

concluded that the increase of porosity by cultivation practices will lead to a decrease in thermal conductivity. The soil heat-flux shows seasonal and diurnal cyclic patterns. At mid latitudes, the greatest positive heat-flux the greatest negative heat-flux At

OCCUKS

OCCUKS

in spring and early summer;

in early winter.

low latitudes, the seasonal fluctuations are

relatively small.

Minor

74

fluctuations are illustrated in fig. 3.16 0,47"N

for Yangambi (Zaire) at a latitude of

and an altitude of 365 m above mean sea level. The curves show that the

60

2 50 W V

L a,

n

40

20

Fig. 3.16

Mean monthly soil temperature at a depth of 50 cm for the year 1952 at Yangambi, Zaire, and major climatic factors that affect it (Soil 1953). Survey Staff, 1975 after I.N.E.A.C.,

mean monthly soil temperature at a depth of 50 cm below the s o i l surface fluctuates with rainfall and amount of sunshine (dependent on cloud cover). Apart

form seasonal fluctuations, the diurnal fluctuations are of

importance for the process of heat exchange.

Fig.

3.17

great

shows temperature

profiles of s o i l and air near the ground for a clear midsummer day and night at mid-latitudes. Several features can be deduced in the diurnal temperature profiles of this figure, such as:

-

the

-

the diurnal amplitude of soil temperature oscillations is retarded with soil

the positive heat-flux with regard to the topsoil after sunrise; the strong positive heat-flux during the early afternoon; the negative heat-flux after sunset; there is an upward movement of heat; strong

negative

heat-flux

before

sunrise;

during

the

night

the

temperature of the subsoil is raised at the cost of the topsoil; depth.

15 Fig. 3.17 illustrates a specific case of radiation and soil profile; there are no general features as far as numerical values are concerned; the depths

indicated depend on thermal inertia.

h

E

140

U

v

U S

2 0 L 01

120 100

W

> 0 n

80

m

c,

r

01

60

.r

W

1

40 20

-

0

E V

v

-20

U S

2 0

L rn

x

0

-40 -60

7

a,

n r

c, P W

n

-80

-100 10

20

30

40 Temperature ("C)

Fig. 3.17

Temperature profiles of soil and air near the ground for a clear midsummer day and night at midlatitude (Fitzgerald, 1974 after Gates, 1970).

3.3.

Interaction of short wave radiation with plants Spectral reflectance .................... The reflectance characteristics and thermal emission of plants are

extensively discussed a.0. by Fitzgerald (1974). In this text only a summary is given. A cross section of a typical leaf is shown in fig. 3.18.

The upper and

76 lower

epidermis

have

a

mainly

protective

function with

regard

to

the

interaction with electromagnetic radiation, the mesophyll region i s the most important part. The mesophyll contains the plastid and vacuolar pigments. The plastid pigments are concentrated near the cell walls, while the vacuolar pigments are distributed uniformly throughout the cellular protoplasm. The most important plastids are the chloroplasts (disc-shaped, 5-8

Chloroplasts

Air cavity

Guard c e l l s

Air ca'vity Fig. 3.18

!J

m in

Upper epidermis

Lower epidermis

Scheme of morphological structure of a plant leaf after Fitzgerald (1974).

diameter and 1 chlorophyll diameter).

!J

is

m thick). Within the chloroplasts are grana, in which located

(these

grana

are

0.5

!J

m

long and

0.054

!J

m

in

Chlorophylls form about 65 X of the leaf pigments. The other most

common plastlds are the carotenoids, which are yellow to orange red in colour, and are the chief colourants in plant leaves in the absence of chlorophyll. The main vacuolar pigments are anthocyanines and anthoxanthlns, which are

normally red and b l u e In colour. The colour of leaves in autumn I s due to

71 carotenoids,

whether

OK

not

in

combination

with

anthocyanines

and

anthoxanthins. The upper portion of the mesophyll, the palisade layer, consists of closely packed elongated cells with their long axis perpendicular to the leaf surface.

It shows a concentration of chloroplasts, which strongly absorb the Visible radiation. The

lower mesophyll, the

arrangement and

spongy mesophyll, has a

less compact cellular

the intercellular spaces are larger as compared with the

palisade layer. This is the main transpiring tissue of the leaf, which shows a low concentration of chloroplasts and has a light green colour. Fig. 3.19 shows a typical reflectance spectrum of a normal healthy plant leaf together with the absorption spectrum of water.

Wavelength (pm) Fig.

3.19.Reflectance spectrum of a typical green leaf and the absorption spectrum of water in the spectral range of wavelengths 0.4-2.6 LI m after LARS (1968).

78

The spectrum of a plant leaf can be divided into the following ranges: the range between 0.4 !J m and 0.7 p m, which is characterized by

-

very low reflectance due to intense absorption of the incident

-

radiation by pigments in the plant; the range between 0.7 u m and 1.3 u m, which is characterized by

-

very little absorption and high reflectance; the range between 1.3 u m and 2.6 u m, which is characterized by pronounced minima.

The reflectance and absorptance of plant leaves is mainly determined by: the pigmentation; absorptions are caused by electron transitions

-

within

the pigment molecular

pigments absorb at 0.43 band at about 0.66

!J

-

0.44

complexes (Fitzgerald,

1974);

all

m, but chlorophyl has an additional

IJ

m; reflection of green radiation is produced by

the chloroplasts; the mesophyl structure, which causes multiple reflection of near Infrared radiation at cell walls; the water

content; the most

intense absorption bands occur at

1.4 IJ m and 1.9 IJ m;

the surface properties of the leaf; a matt surface approximates a perfect Lambertian diffuser more closely than a glossy surface does; the latter shows a prominent specular component in the reflected radiation. Normally, the energy absorbed is converted by photosynthesis into heat and stored energy. absorbed

energy

However, chlorophyll is capable of by

fluorescence.

There

are

two

releasing some of types

of

the

chlorophyll:

chlorophyll-a and -b. Chlorophyll-a shows strong absorption maxima at 0.43 IJ m and 0.66 IJ m. Chlorophyll-b shows a strong absorption maximum at 0.64

IJ m.

In

most plants the content of chlorophyll a : b is 3 : 1, so chlorophyll-a largely determines the absorption. Both types of chlorophyll show typical fluorescence spectra, namely: chlorophyll (a) with maxima at 6 6 8 nm and 723 nm; chlorophyll (b) with maxima at 648.5 nm, 672 nm and 7 0 5 nm. The spectral reflectance of leaves undergoes strong changes both early and late in the growing season. Gates ( 1 9 7 0 ) provides data on these changes for Quercus Alba (white oak). The data are presented in Fig. 3.20.

79

-2

100

aJ

I

I

V

E

m

c, V

60

40

20

I

0.4

r

h

J

I

0.5

0.6 I

1

I

0.7 I

1 0.8 I

! 0.9 I

I

1 .a

I 1.1 I

I

L

- 19 -- 20 - _ - _ _18 .......... 18

40

20

7

t

01 0.4

21 28

2

-.-

June July August September October October October November

I

I

0.5

0.6

,

I

0.7

I

I

I

0.8

0.9

I

1 .o

1.1

Wavelength (pm) Fig.

3.20 Changes in spectral reflectance throughout the growing season of leaves of Quercus Alba after Gates ( 1 9 7 0 ) .

The juvenile leaf has a dense covering of pubescence and shows a relatively high reflectance in yellow and red, and a very high reflectance in near Infrared. As the leaf grows and expands, the hairs spread out, the near

80

Infrared reflectance drops, some absorption takes place by chlorophyll and the green reflectance increases.

Later on a further increase in blue and red

absorption accompanies a slight reduction in green reflectance and a visible darkening of the leaf (May 11 and 18). surfaces

has

At this time, the number of reflecting

increased, resulting in an

increase of

the near

Infrared

reflectance. During the growing season from May 18 to October 21, curves remain nearly constant. On October 28,

the spectral reflectance

the end of the growing season

presents itself by a break-down of chlorophyll, as is illustrated by the shift of the green peak towards yellow and orange wavelengths (Anthocyanins are formed which absorb blue and green).

Furthermore, there is a reduction in

reflectance at 0.8 u m upon pronounced drying. However, the reflectance at 1.0

u m remains constant. The curves of fig. 3.20 give a good impression of

these changes in leaf reflectance throughout the growing season.

In remote sensing, however, we have to deal with the reflectance of a plant canopy,

which

is

determined

by

plant

variables

such

as

leaf

area

and

orientation of leaves and stems. It is obvious that there are often differences in spectral response between plant canopies. Fig. 3.21 illustrates this in showing spectra of grass, birch, pine and fir canopies. Murtha (1978)

describes the damaging agents which may be active in a forest,

and the manifestation of the damage itself. The following damaging agents are mentioned: insects, disease, fire, water deficits, flooding, air pollution, storms, activities of recreationists and beavers. The manifestation of damage may be: a change in morphology (e.g.

growth reduction, defoliation, loss of

branches, cellular collapse or wilted look);

-

a change in physiology (e.g.

-

OK

decrease in photosynthates, deterioration of

chloroplasts, interruption of translocates including water); both.

It can be concluded that the effects of damage on spectral reflectance will be one

OK

both of the following:

-

in case of a change in morphology, a decrease in overall reflectance of

-

in case of a change in physiology (chronic damage over a l o n g period),

the plant especially in the near Infrared; a

shift of the green peak towards yellow wavelengths due to a deteroriation of chloroplasts and finally a shift towards red wavelengths.

81

Grass

Birch

100

Fig.

3.21

Coulson

600

800 Wavelength (nm)

Reflectance spectra of four types of plant canopies after Krinov (1953; also given by H o l z , 1973).

(1966) has studied the directional reflectance of grass; a brief

discussion is given below. The directional reflectance of green grass is shown in fig. 3.22.a.

One of the

features is the low reflectance of radiation with wavelengths of 492 nm and 643 nm, which is in accord with the data presented above (fig. 3.19-3.21).

The

broad minimum reflectance of 796 nm and 1025 nm radiation near the nadir and the asymmetric shape due to forward scattering are further characteristics. Note that the asymmetry is much less than for a number of soil materials e.g. gypsum (fig. 3.11). Fig. 3.22.b

shows the directional reflectance of green grass at different

angles of incidence of light at a wavelength of 643 nm. At Bo backscattering maximum

=

78.5",

a

is observed, which is in accord with the absorbent

nature of plant leaves for radiation of this particular wavelength. Curves of the polarization of radiation reflected from green grass are given in fig. 3.23. The radiation that is strongly reflected by the cell walls of the

82

100

(b)

(a) 80 -

60 -

,? i

40 -

$,,=78.5

O

c

t

I

,

f 0'

20 -

40

80

0

40

@=OO Nadir angle (")

k

Fig. 3.22

80 @=180°

Nadir angle

("1

Directional reflectance of green grass (grass stands thick, height of grass 4-5 cm) after Coulson (1966): a) at four different wavelengths (principal plane, 0, = 53"); b) at three different angles of incidence (principal plane, A = 643 nm). Note: for explanation see par. 3.2.

palisade tissue (A

=

796 nm and A = 1025 nm)

but the radiation reflected by

shows little polarization,

the chlorophyll (A

=

492 nm and A

=

643 nm)

shows a high degree of polarization. Radiation with a horizontal polarization is not absorbed so strongly by the chlorophyll as radiation with a vertical polarization. Thus owing to preferential absorption, the reflected radiation is polarized. Fig. 3.23.b

shows the degree of polarization at different angles of incidence.

The pattern shifts with the position of the source and shows a negative or a

vertical polarization in the antisource direction. The degree of polarization increases with the angle of incidence. An anomalously high polarization appears at O o = 78.5"

. The maxima are located closer to the antisource direction than

in the curves of soil materials presented in fig. 3.12 and Fig. 3.14.

83

40

(b)

20

I 0

-5

'*. \

0'

-

1025nm

.

I

I

I

1

I

80

40

0

40

80 @=180°

@=O" N a d i r angle ( " )

Fig. 3.23

N a d i r angle

("1

Degree of polarization of radiation reflected from green grass after Coulson (1966) : a) at four different wavelengths (principal plane, 9 = 53"); b) at three different angles of incidence (principaf plane, X * 492 nm) Note: for explanation see par. 3.5.

Looking at objects from the source direction means a simplification i n canopy variables, since shadows are not visible. This direction is called the "hot spot". Bunnik (1978) points to the value of the "hot spot" for measurement of the canopy reflectance. Thermal properties _____-__-_____--__ Beyond 2 u m, the reflectance of plant leaves is very low. The leaves behave at longer wavelengths of the near Infrared almost as black bodies, the emissivity being about 0.97.

To prevent the plant from reaching high

84 temperatures, the leaves radiate efficiently at wavelengths longer than 2 u m. Healthy

plants

are

in energy

equilibrium with

their environment.

Their

temperature is adjusted when environmental parameters change s o that the loss of energy is equal to the gain of energy. In the formulae 2-31

and 2 - 3 2 ,

the

energy budget equations are given. Some environmental parameters that influence the energy budget are: the relative humidity of the air, the air temperature and the wind speed. The characteristics of the plant that are important in this connection are the width of leaf (or other characteristic dimensions) and the diffusion resistance (in s m-').

These parameters may be used to formulate the

exchange of energy by convection between the leaves and the air, and the transpiration rate of water from the leaves (see Gates, 1970).

The plant

moisture condition has a pronounced influence on the leaf temperature at a specified intensity of solar radiation. The moisture condition of the plants may be expressed in the relative turgidity (RT), which is defined by (Namken, 1 9 6 4 ) :

RT

= 100

(FW - DW/TW

-

DW)

(3-5)

where FW is the field condition weight of leaf samples, DW is the weight of the leaf samples after drying at 60°C and TW is the turgid weight achieved by floating the leaf samples on distilled water overnight under illumination. In fig. 3 . 2 4 ,

the air temperature at the time of the measurements ( 2 : 3 0 -

3.:00 pm) on the two dates differed by 3.5

K and the relative turgidity of the

cotton leaves equilibrated with a change in radiation intensity in about 45 sec. The data show that

the thermal response of the leaves to changing

radiation is linear; the standard errors of estimate (Sy.x)

indicate that leaf

temperatures could be estimated within 0.9 K, two thirds of the time. The variable plant moisture conditions in Fig. 3.25

were achieved by

timing of irrigation during a rainless period. At the mid-afternoon measuring time, the cotton-plant leaves exhibited wilting symptoms at about 70 percent RT; at 6 0 percent RT, the leaves were extremely flaccid. The data in Fig. 3.25 indicate that cotton-leaf temperature under the specified conditions can vary about 3.5 K from RT

=

6 0 X to RT = 8 2 X around the wilting point.

The difference between bare soils and plants is pronounced in the diurnal changes in temperature. In general, plants are cooler than soil during day time, and warmer during night time. A strong difference between plant and soil will occur around noon on a clear day.

85

I

V

O" 7

4(

k W

6/1/65 = 31.8k.4 C = 67.9*2.5% = 9.08 C(ly/min)-' = .898

TA

L

c 3 ,

RT

m L

g 3E

b

W

r2

+J

I

0 0

Ic 5 W J

36

34

32

b

6/1,2,3/64 = 28.3k1.3 = 77.7k1.7 = 9.9

r2

=

.go6

sy+

=

.91

TA RT

30

/ 0

28

Fig.

3.24

I

I

I

I

0.6

0.8

1 .o

1.2

I

1.4 1.6 S o l a r radiation, Rs(ly/min)

Influence of solar radiation on cotton-leaf temperature (Namken, 1 9 6 5 ) . (Permission Am. S O C . o f Agronomy, I n c . )

Some remarks are made in conclusion. Gates ( 1 9 6 4 ) reports about the difference between conifers and broad-leafed deciduous plants. Conifers are cooler than broad leaves during day time and warmer during night time under similar conditions. The reason is that the fine needle structure of conifers increases the

convection

efficiency

and

couples

the

conifers

tightly

to

the

air

temperature. At night, deciduous leaves will c o o l down to several degrees below the air temperature by radiation. Pronounced thermal contrasts occur between deciduous and evergreen trees in the autumn season. Seasonal variations in plant temperature have been found to depend largely

86

v

t.

41

1

I

I

A

aJ L

3rn

I

40

L

aJ

TA

= 33.9k.7

RS

=

1.32k.04 -.15

a

b

=

* aJ %

r2

=

E

.864

39

aJ -I

38

37

36 58

Fig. on

3.25

I

I

1

I

I

I

62

66

70

74

78

82

86

The effect of relative turgidity on leaf temperature (Namken, 1965)(Permission Am. SOC. of Agronomy, Inc.)

the seasonal variations in moisture availability. For a discussion on the variation in plant temperature with external

factors, the reader is referred to Fitzgerald (1974). temperature of

leaves and plant canopies and

Both

the absolute

the temperature differences

between leaves and the ambient air are of interest (Gates, 1970).

The former is

of interest for the rate of biochemical reaction and the moisture condition of plants, the latter may be used in comparing effects of treatment.

3.4.

Implications for remote sensing The reflectance data of minerals (par.

3.1.)

are essentially obtained

under laboratory conditions. In rocks and soils we are normally concerned with assemblages of minerals and consequently the discrimination potential with regard to mineralogy is lower. Therefore, only rough estimates may be obtained, but

this

can

be

sufficient

for

the

detection

of

concentrated

mineral

occurrences. The t e x t s on s o i l s and v e g e t a t i o n pay a t t e n t i o n t o p r o p e r t i e s such a s o r g a n i c m a t t e r c o n t e n t , a n o r g a n i c c o m p o s i t i o n , m o i s t u r e c o n t e n t , roughness of s o i l s and c o m p o s i t i o n a s w e l l a s s t r u c t u r e of

plant

leaves.

However,

remote s e n s i n g

p r o v i d e s d a t a on s o i l s and r o c k s a s a whole, and p l a n t s a s c o v e r t y p e s , r a t h e r than the individual constituents.

From remote d i s t a n c e s one c a n n o t e x p e c t t o

obtain

individual

detailed

information

on

constituents,

although

laser-

t e c h n i q u e s o p e r a t i n g w i t h c o h e r e n t h i g h i n t e n s i t y EMR may form a n e x c e p t i o n t o t h i s s t a t e m e n t . The rough remote s e n s i n g d a t a , .however, have t h e a d v a n t a g e t h a t they o f f e r a v e r a g e f i g u r e s f o r a n assemblage of a s p e c t s o v e r a r e l a t i v e l y l a r g e surface area.

These f i g u r e s a r e d i f f i c u l t t o o b t a i n on t h e ground s i n c e t h e y

r e q u i r e a tremendous amount of o b s e r v a t i o n s and samples. An example of a rough

is

estimate

the

so-called

albedo,

which

represents

the

total

radiant

- r e f l e c t a n c e of n a t u r a l o b j e c t s . R a r r e t t and C u r t i s p r e s e n t s e v e r a l v a l u e s ; some of t h e s e a r e g i v e n i n t a b l e 3.2.

T a b l e 3.2

Albedo v a l u e s of v a r i o u s n a t u r a l s u r f a c e s ( R a r r e t t and C u r t i s , 1976).

~~t y p e of s u r f a c e

albedo, r e f l e c t e d r a d i a t i o n a s X of i n c i d e n t r a d i a t i o n

soils

37 14 14 8 86-95 20-29 16-23 18 17 14 12-13 10-14 10

snow vegetation

f i n e sand dry black s o i l moist ploughed f i e l d moist black s o i l dense c l e a n snow d e s e r t shrub land w i n t e r wheat oaks deciduous f o r e s t pine f o r e s t prairie swamp v e g e t a t i o n heather

Conclusions

3.5.

The

spectral

vibrational origin.

reflectance

features

An example of

The l a t t e r i s r e p r e s e n t e d by a band a t 1.4 and 2.5 Soils

u may

m f o r C03". show t h e s e

are

either

of

electronic

IJ

m f o r OH',

characteristics,

but

of

u

in

m and 1.9 addition

m.

u

bands hetween 1.6

and t h e w a t e r a b s o r p t i o n hands a t 1.4 reflectance

or

t h e former i s a broad i r o n hand a t 1.1

m

m. present

v a r i a b i l i t y due t o s u r f a c e roughness a s i n f l u e n c e d by s o i l t e x t u r e , s t r u c t u r e

88

and tillage. Furthermore, the organic matter content strongly influences the spectral reflectance e.g.

a high organic matter content results in an overall

low reflectance. Plants show a typical reflectance spectrum as influenced by canopy structure, pigmentation, mesophyll Structure, water content and surface properties of the leaf. A l l pigments absorb at 0.44

!J

absorption band at 0.66

Normally, green is reflected more strongly

IJ

m (red).

m (blue),

but chlorophyll also shows an

than blue and red. The palisade tissue of the mesophyll with its large area of cell walls is mainly responsible for the high reflectance of near Infrared by plant leaves. Furthermore, the surface properties of the leaf have great influence on the reflectance as is illustrated a.0. by white oak leaves in their juvenile stage (pubescence). The work of Coulson (1966)

with regard to the directional reflectance of

natural surfaces reveals interesting features, such as the following: highly absorbent materials (e.g.

plant leaves, and soils rich in organic matter)

deviate from low absorbent materials (which show a forward peak in scattering) in having a backscattering maximum. With

regard

to

emission,

emissivity minima between 9.0

!J

the

following can

m (acid rocks) and 10.5

be !J

stated:

rocks

show

m (ultrabasic rocks).

For rocks as well as for soils, the diurnal temperature change is the most significant short-term variation that is usable in remote sensing. The transfer of heat in the soil takes place by conduction, convection and radiation together, and by latent heat transport (water vapour).

Soil moisture

is one of the most important factors influencing the thermal hehaviour of soil. The difference between soils and plants is most pronounced in the diurnal changes in temperature. In general, plants are cooler than soil during day time and warmer during night time. Seasonal variations in plant temperature largely depend on the seasonal variation in moisture availability. 3.6.

References

Barrett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and H a l l : 336 pp. Bowers, S.A. and Hanks, R.J., 1965. Reflection of Radiant Energy from Soils. Soil Science, Vol. 100, No 2. The Williams & Wilkins Co, U.S.A.: pp. 130-1 38.

Bunnik, N.J.J., 1978. The multispectral Reflectance of Shortwave Radiation by Agricultural Crops in relation with their Morphological and Optical Properties. Thesis Agric. Univ., Wageningen, The Netherlands: 176 pp.

89

Chudnovski, A.F., 1962. Heat Transfer in the Soil. Israel Program for Scient. Transl. (Transl. from Russian), Oldbourne Press, London. 1971. Cipra, J.E., Baumgardner, M.F., Stoner, E.R. and MacDonald, R.B., Measuring Radiance Characteristics of Soil with a Field Spectroradiometer. Soil Sci. SOC. Amer. Proc., vol 35: pp. 10141017.

Condit, H.R., 1972. Application of Characteristic Vector Analysis to the Spectral Energy Distribution of Daylight and the Spectral Reflectance of American Soils. Applied Optics, Vol. 11, No 1: pp. 74-86.

Coulson, K.L., 1966. Effects of Reflection Properties of Natural Surfaces in Aerial Reconnaissance. Applied Optics, Vol. 5, No 6: pp. 905-917. Damen, J.P.N., 1975. Poging tot verklaring van Reflectiespectra van een serie Bodemmonsters, gemeten met de Niwars-spectrometer. Niwars-publ. NK. 25: 56 pp. Fitzgerald, E., 1974. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Spectral Properties of Materials. ESRO CR-232, Neuilly, France: 231 pp. Fuchs, M. and Tanner, C.B., 1968. Surface Temperature Measurements of Bare Soils. Journal of Appl. Meteor., Vol. 7. Gates, D.M., 1964. Characteristics of Soil and Vegetated Surfaces to Reflected and Emitted Radiation. Proc. of the 3rd Int. Symp. on Remote Sensing of Environment, Univ. of Michigan, Ann Arbor: pp. 573-600. Gates, D.M., 1970. Physical and Physiological Properties of Plants. Chapter 5 , Remote Sensing, pp. 224-252; produced by the Committee on Remote Sensing for Agricultural Purposes. Publ. Nat. Acad. of Scces. Girard, M.C. and Girard, C.M., 1977. T616d6tection de la Surface du S o l . ler Colloque P6dologie T616d6tection, Rome: pp. 55-64. Gold, A. and Asher, J.B., 1976. Soil Reflectance Measurement using a Photographic Method. Soil Sci SOC of Amer. Journal, Vol. 40, No 3: pp. 337-34 1.

Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology ESRO (European Space Research Organisation): 186 pp.

R.K(ed), 1973. The Surveillant Science. Remote Sensing of the Environment. Houghton Mifflin Cy, Boston: 391 pp. Hunt, G.R., Salisbury, J.W. e.a., 1970-1976. Visible and Near Infrared Spectra of Minerals and Rocks I/XII. Modern Geology, Gordon and Breach, Science Publ. Ltd. Belfast, N-Ireland. Idso, S.B. and Jackson, R., 1969. Comparison of Two Methods for Determining Infrared Emittances of Bare Soils. Journal of Appl. Meteor., Vol. 8. Institut National pour l'Etude Agronomique du Congo Belge et du Ruanda-Urundi, Ann6e 1952. Bur. Climatol. Commun. 7: 144 pp. Janse, A.R.P., Bunnik, N.J.J., 1974. Reflectiespectra van enige Nederlandse Bodemmonsters bepaald met de Niwars-veldspectrometer. Niwars publ. No 18: 3 1 pp. Janse, A.R.P., Bunnik, N.J.J. en Damen, J.P., 1976. Reflectiespectra van enige Nederlandse Bodemoppervlakken. Landbk. Tijdschr. Jg 88, NK. 8: pp. Holz,

254-260.

Krinov, E.L., 1953. Spectral Reflectance Properties of Natural Formations. Acad. of Scces, USSR. Nat Res. Council of Canada. Techn. Transl., TT-439. Lars, Laboratory for Agricultural Remote Sensing, 1968. Remote Multispectral Sensing in Agriculture. Purdue Univ, Agric. Exp. Stat., Res. Bull., Vol. No 3: 175 pp.

90

Lyon, R.J.P., 1965. Analysis of Rocks by Spectral Infrared Emission (8-25 u m) Economic Geology, Vol. 60: pp. 715-736. Mathews, H.L., Cunningham, R.L. and Petersen, G.W., 1973. Spectral Reflectance of Selected Pennsylvania Soils. Soil Sci SOC. her. Proc., Vol. 37: pp. 421-424. Meyer-Arendt, J.R., 1972. Introduction to Classical and Modern Optics. Prentice-Hall Inc., Englewood Cliffs, N.J.: 558 pp. 1973. Principles of Environmental Physics. Contemporary Monteith, J.L., Biology. Edward Arnold (publ.) Ltd London: 241 pp. 19781. Remote Sensing and Vegetation Damage: A Theory for Murtha, P.A., Detection and Assesment. Symp. on Remote Sensing for Vegetation Damage Assessment 1978. Publ. by Amer. SOC. of Photogrammetry: 32 PP. Namken, L.N., 1964. 'Ihe influence of crop environment on the internal water balance of cotton. Soil Sci. SOC. Amer. Proc. 28: pp. 12-15. Namken, L.N., 1965. Relative turgidity technique for scheduling cotton irrigation. Agron. J. 47: pp. 38-41. Obukhov, A.I. and Orlov, D.S., 1964. Spectral Reflectivity of the Major Soil Groups and Possibility of using Diffuse Reflection in Soil Investigations. Soviet Soil Sci. 1964: pp. 174-184. Orlov, D.S., 1966. Quantitative Patterns of Light Reflection by Soils. I. Influence of Particle (aggregate) Size on Reflectivity. Soviet Soil Sci. 1966: pp. 1495-1498. Planet, W.G., 1969-1970. Some Comments on Reflectance Measurements of Wet Soils. Remote Sensing of Environment 1, Elsevier N-Holland: pp. 127129.

Skidmore, E.L., Dickerson, J.D. and Schimmelpfennig, H., 1975. Evaluating Surface-Soil Water Content by measuring Reflectance. Soil Sci. SOC. Amer. Proc., Vol 39: pp. 238-242. Soil Survey Staff, 1975. Soil Taxonomy. A Basic System of Soil Classification for making and interpreting Soil Surveys. U . S . Dept of Agric. Handbook No 436: 754 pp. Stoner, E.R., Baumgardner, M.F., Biehl, L.L. and Robinson, B.F., 1980. Atlas of Soil Reflectance Properties. Agric. Exp. Stat. Purdue Univ., West Lafayette, Indiana, Res. Bull. 962: 74 pp. Wijk, W.R. van, Vries, D.A. de, 1963. Periodic Temperature Variations. In: Physics of Plant Environment, ed. van Wijk, North Holland Publ. Co., Amsterdam. 3.7.

Additional Reading

Bunnik, N.J.J. and Verhoef, W., 1974. The Spectral Directional Reflectance of Agricultural Crops. Niwars Publ. No 23. Colwell, J.E., 1974. Vegetation Canopy Reflectance. her. Elsevier Publ. Cy. Remote Sensing of Environment 3: pp. 175-183. Gausman, H.W. and Cardenas, R., 1968. Effect of Pubescence on Reflectance of Light. Proc. of 5th Symp. on Remote Sensing of Environment. Univ. of Michigan, Ann Arbor: pp. 291-297. Hoffer, R.M., Johannsen, C.J., 1969. Ecological Potentials in Spectral Signature Analysis. In: Remote Sensing in Ecology. Unlv. of Georgia Press, Athens: pp. 1-16. Karmanov, I.I., Rozhkov, V.A., 1972. Experimental Determination of Quantitative Relationships between the Color Characteristics of Soils and Soil Constituents. Soviet Soil Sci. 1972: pp. 666-674. Knipling, E.B., 1970. Physical and Physiological Basis for the Reflectance of Visible and Near Infrared Radiation from Vegetation. her. Elsevier

91 Publ. Cy, Remote Sensing of Environment 1: pp. 155-159. Koolen, A.J., 1979. Temperatuurbeelden van Onbegroeide Grond op weg naar Landbouwpraktijk? Landbk. Tijdschr. pt. 91, Nr 9: pp. 258-264. Leu, D.J., 1977. Visible and Near Infrared Reflectance of Beach Sands: A Study on the Spectral Reflectance/Grain Size Relationship. Remote Sensing of Environment 6 , Elsevier N-Holland: pp. 169-182. Scharringa, M., 1976. Temperatuurklimaat van de Bodem. Landbk. Tijdschr. pt. 88, Nr. 8: pp. 261-264. Suits, G.H., 1972. The Calculation of the Directional Reflectance of a Vegetative Canopy. her. Elsevier Publ. Cy, Remote Sensing of Environment 2: pp. 117-125. Suits, G.H., 1972. The Cause of Azimuthal Variations in Directional Reflectance of Vegetative Canopies. Amer. Elsevier Publ. Cy, Remote Sensing of Environment 2: pp. 175-182. Torres, 1973. La Thermographie Questions Techniques et Problemes de 1'InterprGtation. Revue Photo-InterprGtation 1973-2: pp. 48-73. Verhoef, W. and Bunnik, N.J.J., 1974. Spectral Reflectance Measurements on Agricultural Field Crops during the growing season. Niwars publ. No 31: 7 2 pp. 1975. A Model Study on the Relations between Verhoef, W. and Bunnik, N.J.J., Crop Characteristics and Canopy Spectral Reflectance. Niwars publ. No 33: 89 pp. Verhoef, W. and Bunnik, N.J.J., 1976. The Spectral Directional Reflectance of Row Crops. Niwars publ. No 35: 134 pp. Vincent, R.K., Rowan, L.C., Gillespie, R.E. and Knapp, C., 1975. Thermal Infrared Spectra and Chemical Analysis of Twenty-six Igneous Rock Samples. Remote Sensing of Environment. Amer. Elsevier Publ. Cy: pp. 199- 209.

Watson, R.D., 1972. Spectral Reflectance and Photometric Properties of Selected Rocks. Remote Sensing of Environment 2: pp. 95-100.

This Page Intentionally Left Blank

93

4.

DETECTION OF ELECTROMAGNETIC RADIATION

Life

earth is dependent

on

on

solar radiation and has developed systems

that use solar radiation as an energy source (e.g.

plants) and as a means of

visual perception (man and a great number of animals).

Two of our five senses

are capable to detect EMR these being the eye and the nerve endings. The latter sense heat. The eye enables vision and is of primary interest to our purpose, since

it

is

difficult

to

think about methods

for remote inventory and

monitoring of the natural environment that do not depend some phase

of

on

the human eye in

the processing or interpretation. The only alternative is

braille! Some methods of image interpretation require a certain ability of human vision. One

of these, the ability to get a stereoscopic impression of overlapping

images is normally present. Another requirement connected with the study of coloured images is correct colour vision. The different aspects of human vision are discussed in par. 4.1.

To expand o u r view, that is to make visible, radiation to which the eye is not

sensitive, may

be

done by

photographic

as well

as non-photographic

techniques with detection capability in the zones of the EM spectrum outside the Visible (see par. 4.2 and 4 . 3 ) . After this first subdivision in photographic and non-photographic methods of detection, attention is given in par.

4.4.

to the different types of

platforms on which detectors may be mounted. Finally in par. 4.5, a discussion is presented on ground-investigations. The latter have to be directed to the remote

sensing

tool

and

therefore

deviate

partly

from

conventional

investigations. 4.1.Human vision The eye is capable of sensing radiation of wavelengths between 0.4 and 0.7

m (or more precisely 380-760 nm),

the so-called Visible zone of the EMS.

As is stated above, human vision has to be used in one or more steps of processing or interpretation, so that some understanding of it is necessary. There are a number of aspects connected with vision that have to be dealt with in this context, namely:

-

colour perception; stereopsis or depth perception,

94

-

resolving power. The construction of

the eye is to some extent comparable with

the

photographic camera, since one as well as the other possess a diaphragm, a lens and a sensitive layer. The light enters the eye through the cornea, which is separated from the l e n s by fluid; the maximum light refraction occurs at the cornea. The iris is the pigmented part of the eye that controls the aperture (pupil), which can be varied over a ratio 16:l. The lens is active in accomodating or focusing for near and far vision. For this, the shape of the l e n s can be modified by varying the tension on the membrane attached to its margin. For nearby vision, the tension is released and the lens gets a more convex shape as compared with its shape for far vision. The image is focused on the retina, which contains the light receptors, the so called rods and cones. The rods and cones differ in threshold as is indicated in Fig. 4.1

and serve under low illumination (e.g.

twilight) and under high

illumination (e.g. daylight) respectively.

000

\ \

I

400

Fig. 4.1

500

600

700 Wavelength (nm)

Threshold responses of retinal receptors (after Land, 1977)

95

The spectral sensitivities of rods and cones are presented in Fig. 4.2. The curve that peaks at about 500 rn corresponds to the sensitivity of rod pigment. The other three curves correspond to the cone pigments and show peaks respectively at 435 nm, 520-550 nm and 550-595 nm. The latter extends into the long wavelengths up to about 6 5 0 nm, thus enclosing orange as a whole. Note that the sensitivity ranges of the cones are overlapping each other. The maximum concentration of receptor cells is found in the fovea. Close to the fovea is the so-called blind spot. At this place, the optic nerve joins the eye and there are no receptor cells. h

100-

N W .r 7

m

E

80-

0 E

v

4> 2,

60

-

.r v)

2

I-’

40-

.r E

%

.r

20-

c,

m

7

a W

0 400

Fig.

500

600 700 Wave1 ength (nm)

4.2 Normalized spectral sensitivities of four visual pigments (after Land, 1 9 7 7 ; adapted from work of Brown and Wald of Harvard Univ.)

The so-called retinex theory (Land, 1 9 7 7 ) helps to explain COlOUK vision. Retinex is used for the ensemble of biological mechanisms that convert flux into a pattern of lightnesses. The experiments of Land show that objects are observed in the same colour even under a great variation of illumination intensity. Therefore, flux does not appear to be the defining factor. In human vision, the COlOUK sensation is made less dependent

OK

even independent on

flux, since a comparison is made in the retinex system of lightness of a specific area with respect to the lightnesses of its surroundings. Although the activation of two retinex systems has been found to be sufficient for COlOUK sensation, normally three retinex systems will be active. A t

96 daylight, the three cone pigments act and determine individually the lightness of an object or area. The colour of the object or area is a result of the report on the three specific lightnesses and as stated above of the comparison of these with the lightnesses of its surroundings. The visual pathways (see Kaufman, 1 9 7 4 ) , that is the pathways from the eyes to the central nervous systems, are given in fig.

4.3.

The fibers

comprising the optic nerve may be thought of as divided into two intermixed bundles. One bundle of the optic nerve contains fibers originating from cells at

the temporal side of

the eye, and the other bundle contains fibers

originating at the nasal side of the eye. The fibers that originate from the temporal sides go to the hemisphere of the brains at the same side of the head as the eye in which the fibers originate. The nasal fibers cross over, that is they go to the opposite hemisphere of the brains.

left

right

object

RH

brains

/ \ / I

LH Fig. 4 . 3

Pathways from the optic nerves to the central nervous system.

L E , RE = resp. left and right eye LH, RH = resp. left and right cerebral hemisphere

The eye produces, images that are upside down. The left side of an object will be at the right side of the image on the retina, and the right side of an object at the left side of that image. In other words: the left side of an object is projected nasal for the left eye and temporal for the right eye. Consequently, points to the left of the scene produce signals in the right cerebral hemisphere and those of the right side of the scene in the left cerebral hemisphere (see fig. 4 . 3 ) . The crossing of signals to contralateral hemispheres plays an important part in binocular depth perception, since i t enables fusion of double images in the binocular field of view. It has been known for many years, that fusion is not really a necessary

97

condition for stereopsis (Kaufman, 1974); called

pictorial

cues

involve

light

and

there are several cues. The soshade,

texture, interposition,

perspective and relative size. Others are:

-

kinetic cues, the motion parallax

OK

the difference in imaging between far-

away objects and nearby objects when the head is moved, and the kinetic depth effect that is the systematic transformation of retinal images by movement with respect to the object;

- physiological cues, being the accomodation of the lens and the convergence and divergence of the eye axes. For stereoscopic observation of airphotos using parallax differences of image objects, however, fusion is a must. The eye shows normal aberrations (Davson, 1962), namely:

-

spherical aberrations, that is the rays from an object-point entering the eye at different points of the cornea are not bent to converge at a unique point

on the retina;

-

chromatic aberrations, that is the focus for blue rays is before the retina, and for red rays behind it, while yellow rays are in focus.

Furthermore, there are the individual aberrations and deficiencies with respect to perception of

CO~OUK,

texture and pattern (see Julesz, 1975 and Young,

1964). The resolving power of the eye is determined by the largest diameter of its receptor cells (Sabins, 1978).

The maximum diameter, which mounts 3 u m,

has to be multiplied by the refractive index of the vitreous humor (n obtain the effective diameter as expressed by

a'

(=

= 1.3)

to

the angle or radian

measure of the outer rays in the eye that compose the retinal image).

The image

distance from the retina to the lens is about 20 nun. The effective width of the receptors therefore is approximately 4f20.000 or 1/5.000 of the image distance. Since

a'

is proportional to a ( = the angle between the outer rays coming from

the margins of the scene into the eye (Davson ed.,

1962), the effective width

can be placed upon 1f5.000 of the object distance as well. Therefore, adjacent objects must be separated by l/5.000 of the object distance in order to fall on alternate receptors. However, the detection capability of the eye is influenced not only by the size of the objects but also by their shape, contrast and orientation (Sabins, 1978). The fibers going from the retina to the brains have to carry information

98

about position, shape, size, texture, brightness and colour. This is only possible by unique codes. According to Kaufman (1977), the natures of

the codes are not conclusive

OK

the theories concerning even fully convincing.

Therefore, we will only discuss one of these sensations in a rather simple hut practical way, namely: colour vision. The colour sensations blue, green and red are called the primary colours. Combination of green and red light produces yellow; blue and red light produce magenta, while blue and green light produce cyan. Yellow, magenta and cyan are the so-called secondary colours. Considering the properties of secondary colour dyes: the observation of yellow (ye),

magenta (ma) and blue-green or cyan (cy) means specific absorption of

respectively blue (bl), green (gr) and red (re).; of respectively green

+

red, blue

+

red and blue

the dyes show transmittance

+

green. The properties are

expressed in the colour circle and can be used for the composition of colours (fig. 4 . 4 ) .

a

b

C

Fig. 4 . 4 The Colour circle: a) basic division (after Gerritsen, 1972); b) mixing of primary colours; c) mixing of secondary colours (b and c after Smith, 1968); For abbreviations: see text. (Used by permission of Am. SOC. for Photogrammetry and Remote Sensing.) White is produced by mixture of the three primary colours. The super-position of three secondary colour dyes produces grey to black, since blue, green and red are absorbed. Colour is a composite three-dimensional characteristic consisting of a lightness attribute and two chromatic attributes, being hue and saturation (Hunter, 1975).

Hue is the colour sensation associated with different parts of

the spectrum denoted by blue, green, red, cyan, yellow (,orange) and magenta.

99 Saturation or chroma is the colour sensation which corresponds to the degree of hue in a colour. The arrangement of colours in a hue and saturation surface is given in fig. 4.5a.

Full saturation and complete absorption by the secondary COlOUKS (as

meant in fig. 4.4~) is found on the outer circle.

WH!TE

BLACK

(a)

(b)

Fig. 4.5 Arrangement of colours (Hunter, 1975) a) Hue and saturation surface; b) Three-dimensional COlOUK space. (Reprinted by permission of John Wiley & Sons, Inc.) Lightness or value is equivalent to some member of the series of achromatic colour perceptions ranging for light diffusing objects from black to white, and for regularly transmitting objects from black to perfectly clear and colourless (Wyszecki e.a. fig. 4.5b.

1967).

A three-dimensional colour space is given in

The lightness dimension provides an achromatic center axis, on

which the hue circle can be positioned at varying lightness levels. Using the absorption characteristics of the secondary COlOUK dyes, that is

subtraction of

light of specific wavelength range, is known as the

subtractive way of colour formation (fig. 4.4.~).

this in contrast to the

additive way being the addition of light of specific wavelength (fig. 4.4.b). Actually, the eye can only operate on an additive way.

Suppose blue is

subtracted from white light by passing through a filter. Thus green and red light are transmitted, which produce the same effect as the addition of green and red light would do, that is they add to yellow. Often it is found difficult to understand colour formation both in a subtractive and an additive way. However, both ways are essential to the production of colours by photography. The

effect of different quantities of the secondary colours yellow,

magenta and cyan dotted over a white reflective surface is illustrated in the

100 ITC Colour Chart (plate 3 ) . The pigments dotted on the white paper surface subtract light from the incident radiation. Yellow pigments subtract blue light, magenta pigments subtract green light etc. The transmitted light is reflected by the paper surface. Representing this light by vectors, as is done in fig. 4.6,

enables a schematic

presentation of subsequent additive colour formation. For more information on Colour Science, one is referred to text books such as Judd and Nyszecki ( 1 9 6 3 ) and Wyszecki and Stiles ( 1 9 6 7 ) . 4.2.

Photographic techniques Photographic techniques may be used for detection of a portion of the

Ultraviolet (0.3-0.4

p

m), of Visible radiation (0.4-0.7

of the near Infrared range (0.7-0.9

I . !

m).

!J

m) and of a portion

Filters and specific films are used

to obtain information in broad wavelength zones or in relatively narrow bands. There are three categories of filters (Slater, 1 9 7 5 ) :

-

antivignetting filters;

-

polarization filters.

spectral filters; Antivignetting filters are usually produced by depositing a metal alloy

on glass in such a way that the central area of the filter is absorbent and the

circumferential

region

is

transmittent.

They

are

used

to

improve

uniformity of image-plane irradiance (Slater, 1 9 7 5 ) . Spectral filters are divided into absorption and interference filters. Absorption filters can be produced by cementing gelatin between planeparallel plates of optical quality glass. The gelatin has an admixture of organic dyes. Resides gelatin filters, filters of example, absorption curves of presented in fig. 4.7. 200-400

coloured glass are available.

the Kodak Wratten

filters 1A and

As an 2A are

The 2A filter is a complete absorber for radiation of

nm, while 1A shows 1 X transmittance over the 310-380 nm wavelength

zone. Furthermore, the large variety of Kodak Wratten filters is demonstrated in fig. 4.8. Interference filters comprise quarterwave optical-path- thickness layers of alternating high and low refractive-index materials. Unwanted radiation is to

be

reflected and

canceled, while

the

required

radiation is

to

be

transmitted. Polarization

filters consist

of

a

coating of

polarization film on

(optical quality) glass. The position of the filter can be such that only the

101

B1

Gr

I

I

Re

0

I

B1

\

\

\

\

\

\

\

\

Gr

\

i

/

I

; B?

/

I

I

I

/

I

uGr/

/

/

YeGr’

/

\

\

u d 1

=

/

/

/

\ Abbreviations :

/ \

/

\

/

unsaturated

= dark =

light

ye = yellow Ma = magenta Cy = cyan B1 = blue Gr = green Re = red e.g.

ReMa = reddish magenta.

Fig. 4 . 6

. I

Re/

/

’

\

I

cr

Additive Colour formation schematically.

I

102 component parallel to the principal plane is transmitted. The principal plane is the vertical plane containing the sun, the ground target and the observer straight ahead (plane of incidence; see also fig. 2.5).

Polarization filters

may be used to enhance image quality in the presence of haze. Haze produces multiple reflection at randomly oriented particulates. The

.I

100

1A

200

300

400

500

600

700 800 900 Wavelength (nm)

.I

2A

W U S

3 1 c, .r

E u)

5 L

10

k-

i100

300

400

500

600

700

800

900

Wavelength (nm) Fig. 4.7 Spectrophotometric transmittance curves of Wratten filters 1A and 2A (Eastman Kodak Cy, 1970).(Reprinted courtesy of Eastman Kodak Company.) scattered light shows polarization dominantly horizontal, that is perpendicular to the plane of incidence. By transmitting only the component parallel to the plane of incidence the effect of haze will be reduced and the image contrast will be enhanced. Filters require a correction on exposure time in order to compensate for the radiation removed by the filter. The factor, by which the exposure with filter has to be greater than the exposure without filter, is called the filter factor. The main photographic film-types are:

-

panchromatic or black and white films sensitive for the wavelength range

103 from 360 to 720 nm;

-

Infrared black and white films recording Visible and near Infrared radiation (up to 900 nm);

Fig. 4.8 Spectral-transmittance bar charts for Selected Kodak Wratten Filters courtesy of Eastman Kodak Company.) (Eastman Kodak Cy, 1970).(Reprinted

104

-

true colour films sensitive for blue, green and red light;

-

false colour films recording green, red and near Infrared radiation (up to

900 nm). All the films mentioned when applied from airborne or spaceborne platforms require filters to

remove unwanted

radiation and

to

improve image-plane

irradiance. In table 4.1 some film-filter combinations are given. To produce Infrared black-and-white photography, a large part of the Visible is often excluded from reaching the film. This may be done by application of light-red

OK

dark-red

filters. A yellow filter is applied to obtain false colour photography. Table 4.1 Examples of film-filter combinations Wratten filter no

Excluding wavelength (nm) below”

Film

Eliminating effect of

1A (sky light)

310-386

2A (pale yellow)

406-413

true colour film true colour film

G12 (yellow OK minus blue)

492-508

weak haze, flying altitude up to about 3000 m moderate to strong haze, flying altitude more than 3000 m strong haze

15G (dark yellow)

508-520

25A (light red) 89B (dark red)

580-590 680-703

*

panchromatic film and false colour film Infrared black strong haze and white film item item item item

first figure 0.1 %, second figure 10 % transmittance curves Eastman Kodak Cy (1970).

transmittance according to

Photographic films consist of a flexible transparent base (film base) coated with one or more emulsion layers of which each has a thickness of approximately 100

J !

m. The emulsion is a suspension of silver halide grains in

solidified gelatin. The

panchromatic

emulsion layer, while

and

Infrared

black-and-white-films

consist

of

the true colour and false colour-films have

one three

emulsion layers. The grains of the emulsions are a few micrometers in diameter (Sabins, 1978) and have an irregular shape. They have been processed to increase their sensitivity to light. On exposure, when a proton strikes one of the grains, an electron is trapped at an imperfection of a grain, it may

105 convert a silver ion into a neutral silver atom. If more than one photon is received by a silver halide grain within about a second, combinations of four atoms of silver are formed, which are stable. Thus by interaction of light with silver halide grains a latent silver image is formed. By the reduction process in developing panchromatic films, the exposed grains are converted into opaque grains and unexposed grains are removed leaving clear areas in the emulsion. The parts of the scene with low reflection will show up bright, the parts with high reflection dark and moderate reflecting areas grey; it is a negative image. When such a film is printed onto photographic paper, the signatures are reversed and a positive image is the result. Recently a new film type has been

introduced in which during the

developing process, silver is replaced by a black dye. The resultant product is less granular when compared with the silver image and enables therefore high enlargement factors. However, no application in aerial photography of this new type of film is known t o the author. The characteristics of the emulsion layers in true COlOUK and false colour-films are similar to those of panchromatic film with the following additions:

-

each layer has a maximum sensitivity, this being for true colour film in the blue, green and red bands, and for false colour film in the green, red and near Infrared bands,

-

during developing each emulsion layer forms a COlOUK dye, that is for true colour-film complementary to

the blue, green and red radiation that

exposed the layers being yellow, magenta and cyan, for false colour-film yellow in the green sensitive layer, magenta in the red sensitive layer and cyan in the near Infrared sensitive layer. The false COlOUK-fih is described in table 4.2 by comparing it with the true colour-film. In true colour-film, a yellow filter between the blue and green sensitive layers prevents blue from reaching the underlying layers, which are also sensitive to blue radiation. Blue is eliminated from the false colour-film by the use of a yellow filter on the camera. The blue sensitive (yellow forming) layer of the true colour film is replaced by a near Infrared sensitive layer in the false colour film, and the dyes to be produced are shifted one position, tnat is yellow for the green sensitive layer, magenta for the red sensitive layer and cyan for the near Infrared sensitive layer. So do the

106 Table 4.2 Comparison between true colour-film and false colour-film. layers

1st layer

--------2nd layer 3rd layer

true colour-film

false colour-film (with yellow filter on camera)

sensitive fOK

sensitive for

dye

resulting colour

near Infrared

cyan

red

green red

yellow magenta

blue green

dYe

blue yellow yellow filter green magenta red cyan

resulting colours in the false colour photograph, respectively blue for green, green for red and red for near Infrared reflecting objects. By developing a true colour film, a yellow image is formed at the exposed places in the blue sensitive layer, the green sensitive layer forms a magenta image etc. These images are negative images, because the original radiation intensity is transformed in dye. For instance, much blue results in much yellow dye, which transmits little blue. When the negative film i s projected onto photographic paper, a positive colour print is produced. In this example: the negative shows much yellow, which transmits little blue, producing little yellow on the positive, which transmits much blue (that is the original intensity).

In fig.

4.9,

a schematic presentation is given of the colour

negative process and the production of colour positives of true colour, as well as false colour-film. Grass is taken as an example; for the reflectance of grass, the reader is referred to fig. 3.21.

The incident radiation and the

radiation transmitted by the film positives are indicated by vectors. Since blue is not included in the false colour-film and replaced by near Infrared, which is not visible to the eye, false colours are produced. The amount of dye formed in the positive products is proportional to the incident radiation in such a way that much radiation produces little dye. Aerial colour films are often of the reversal type, since these films produce a high contrast. Therefore, some attention is given below to the processing of these films (Slater, 1975). The first step in processing of colour reversal film is the development in a black and white developer. A negative image is formed in each layer. Fogging exposes the remaining silver halide. This is normally accomplished

true colour f i l m

1

1

1

radiation

qrass

illum. with white 1i g h t

i11u m i n a t i on of f i l m

NIR 4 r.

bl

gr

re

dark green c o l o u r strong absorption

bl + re moderate a b s o r p t i o n g r

p o s i t i ve

false colour f i l m

7

BB

-

1 minus

bl

1

grass

NIR

1 gr

4

-

re

re

bl

magenta

gr

-

red colour

v e r y much r e

re

moderate a b s o r p t i o n b l strong absorption g r positive

Fig.4.9

bl

Schematic presentation of colour formation in true and false colour films using grass as an example

+

r e combine t o ma

108 The f o l l o w i n g s t e p is t h e development of

chemically i n r e v e r s a l processing.

t h e f i l m i n a c o l o u r d e v e l o p e r r e s u l t i n g i n t h e p r o d u c t i o n of dye i n t h e areas where t h e remaining s i l v e r h a l i d e i s reduced. A t t h i s s t a g e , a p o s i t i v e c o l o u r image and a n e g a t i v e s i l v e r image a r e produced. The f i l m i s t h e n bleached t o remove t h e s i l v e r images b u t l e a v i n g t h e dyes u n a f f e c t e d . A g r e e n s u b j e c t w i l l show up b l u e when viewed i n t r a n s m i t t e d l i g h t because magenta and cyan dyes

are formed, which a b s o r b g r e e n and r e d l i g h t . The s p e c t r a l s e n s i t i v i t y c u r v e s of two t y p e s of Aerochrome I n f r a r e d f i l m 4.10.

are g i v e n i n f i g .

It can be n o t e d t h a t t h e cyan-forming-layer

f i l m s is slower a s compared w i t h obtain

a

lower

sensitive layer s e n s i t i v i t y of Infrared

response

to

the other layers.

near

Infrared

i n the

This h a s been done t o

radiation.

The

near

Infrared

is t h e upper l a y e r i n t h e f a l s e c o l o u r f i l m and shows a 2 a b o u t 0 ( = 1 e r g / c m ) i n a r e l a t i v e l y broad zone of n e a r

radiation,

being

very

low

when

compared

to

the

green

and

red

s e n s i t i v e l a y e r s ( y e l l o w and magenta forming l a y e r s ) .

3

x

2.0

>

.r

2

1.0

ul

.r 4J

yellow forming layer

.r

w

2.0

.-

flj\

magenta forming layer

yellow forming layer

.r

cyan forming layer

c

W ul

a,

u l o

\

4J W

c

magenta forming layer

-1.0

#&

cyan forming layer

0

cn

,” -2.0

I

I

0.4

0.6

I

I

I

0

S -4.0

0.8 1.0 1.2 Wavelength (pm)

0.4

0.6

0.8 1.0 1.2 Wave1 ength (pm)

4.10 S p e c t r a l s e n s i t i v i t y c u r v e s f o r Aerochrome I n f r a r e d f i l m 2443 ( a ) and f o r High D e f i n i t i o n Aerochrome I n f r a r e d f i l m SO-127 ( b ) a f t e r S l a t e r ( 1 9 7 5 ) . The s e n s i t i v i t y is t h e r e c i p r o c a l of t h e energy i n ergs/cm2 ( 1 e r g = 100 n J) of monochromatic r a d i a t i o n t o produce i n t h e i n d i v i d u a l l a y e r an e q u i v a l e n t n e u t r a l d e n s i t y of 1.0 when t h e f i l m i s g i v e n n e g a t i v e processing. (Used by p e r m i s s i o n of Am. SOC. f o r Photogrammetry and Remote S e n s i n g . )

Fig.

The n e a r I n f a r e d l a y e r i s a l s o s e n s i t i v e t o V i s i b l e r a d i a t i o n .

However,

t h e q u a n t i t y of V i s i b l e r a d i a t i o n t h a t can be c a p t u r e d by t h i s f i r s t l a y e r i s ignorable

when

compared w i t h

the quantities

that

can be

absorbed

by

the

f o l l o w i n g l a y e r s of t h e f i l m , which show h i g h s e n s i t i v i t i e s t o g r e e n and r e d radiation.

S i n c e much of

the

green

i s c a p t u r e d by

the

second l a y e r ,

the

109 overlapping in sensitivity of the red sensitive (third) layer with the green sensitive (second) layer is of minor influence. ordering

of

the

layers

in

the

false

Therefore, owing to the

colour-film,

a

rather

accurate

registration of red radiation (in the magenta forming layer) can take place. The reduced effect of near Infrared radiation in the false colour-film results in a

better registration of natural objects, of which many are strong

reflectors of near Infrared, especially vegetation. At normal sensitivity, red would predominate in most cases over the whole photographic scene (objects with high near Infrared reflectance produce no or little cyan, therefore the film transmits much red). Because of strong scattering of Ultraviolet (UV)

by the atmosphere,

little application is found in remote sensing of W photography. However, a typical film-filter combination for UV photography may be mentioned, being the Kodak Plus-X Aerographic film 2402 with the Kodak Wratten 18A filter. The latter transmits the energy of the spectral range between 0.3

and 0.4

l~ m.

Special quartz lenses have to be used in order to transmit UV radiation also below the critical wavelength ( 0 . 3 5 4.3.

II

m) for glass of most cameralenses.

Non-photographic techniques Other remote sensing techniques than aerial photography are required for

detection in the wavelength range of the Infrared larger than 0.9

p

m. This

range covers solar radiation in the near and middle Infrared and earth emission in the middle and far Infrared (see fig. 2 . 2 ) .

Alternative ways of

detection are needed, because lens systems cannot be used for focusing the relatively broad spectral regions which are required for remote sensing in these low energy regions. An alternative way for detection of long wavelength radiation (as well as

for short wavelength radiation) was found in the so-called airborne line scanner. The

multispectral airborne

line-scanner

(fig.

4.11)

collects energy

in

distinct wavelength ranges (channels or bands) of a scene below in a series of scanlines each of which is perpendicular to the line of flight. The energy is received by a rotating mirror. The rotation of the mirror is adjusted to the velocity of the airplane in order to prohibit overlap or gaps between adjacent scanlines.

110 The mirror reflects the energy into a collector; the energy is divided into distinct bands and focused on a series of detectors. The scene is normally built up of objects that vary in reflection or emission properties and can be reconstructed when variations in signal strength get an address on the scan-

b ) Scanner schematic

a ) Scanning procedure during flight

Fig.

4.11 The

multispectral airborne optical Lillesand and Kiefer (1979). (Reprinted by permission of John Wiley

mechanical &

scanner

after

Sons, Inc.)

line. The signals can be stored on tape or displayed on a TV screen (or cathode ray tube)

as dark or

light tones. When a photographic film is

transported at the same speed as the repetitive lines pictured on the TV screen, a one-band photographic image can be derived as well (Rudd, 1974). The technique is called multispectral scanning,

OK

MSS.

Detectors can be classified according to Baker et al., (1975) into:

-

thermal detectors, based on increase of the temperature of heat-sensitive materials; the signal is a result of the absorption of radiation, which produces

a

variation

electrically;

in

the

detector

material

that

is

monitored

111

-

quantum-type detectors, based on the direct interaction of the incident photon with the electronic energy levels within the detector material.

The quantum-type detectors can further be classified into (Baker et al., 1975):

-

photoemissive detectors, in which the absorption of photons from incident radiation exites electrons within the sensitive material in such a way that they are emitted through a Surface barrier; these detectors operate in the Visible and Near Infrared up to about 1 u m wavelength;

-

photoconductive and photodiode detectors; incident photons with an energy greater than the energy gap of the detector material produce free-charge carriers, which cause the resistance of the photosensitive material to vary

in an inversely proportional ratio to the number of

incident

photons; these detectors are sensitive to wavelengths up to several 10's of micrometres; they may be composed of lead salts (PbS and PbSe).

Next to the airborne line-scanner some other non-photographic techniques have been developed. In image cameras

OK

TV-tubes like the Image Orthicon, the

scene is focused by a lens on a photoemissive cathode. This TV tube was developed in the late 1 9 3 0 ' s . The so-called Vidicon tube, based

on

photoconductivity, is the most

widely used camera tube today. It is relatively small, low in cost and has a long life-time. There are also modifications of Vidicon, such as: the Return Beam Vidicon (RBV),

Plumbicon and Silicon diode array camera tube. For more

information, one is referred to Baker et al. Recently, a new concept has been developed, by which sensing, storage and transfer can be done in a simple structure: the charge-coupled device (CCD) and more specific the charge-coupled imager (CCI).

A CCD consists of a linear

array of closely spaced MOS (= metal-oxide semi-conductor) capacitors formed by depositing metal electrodes over an oxidized silicon substrate. The CCD operates by storing information in the form of carrier charge packets, in the capacitors at the Si-Si02 interface. These charge packets, which are generated by absorption of the incident photon flux, are transferred serially to the output element by a multiphase clock. A serial output is produced representing the variation of the incident flux across a line (Baker et al.,

1975).

In

addition the CCI has an imaging device and seems to offer good prospects for use as a multispectral strip camera. Both the Vidicon and CCI are imaging sensors. A non-imaging sensor is the

112 radiometer, which measures the intensity of EMR emanating from objects within its field of view and sensitivity range. Radiometers operate in the Infrared spectrum at

wavelengths larger than

1 IJ m

(photometers operate at shorter wavelengths).

and

in the Microwave

region

The radiometer for measurement

of the Infrared requires a stable internal reference, since errors may result from the often variable radiation derived from components of the radiometer itself. The output of the detector in a radiometer is an electrical signal that

is

related to

the radiance difference between the target and

the

reference radiation. A so-called spectrometer is a radiometer which has a dispersing element that enables measurement as a function of wavelength. A n example is the NIWARSspectrometer. This spectrometer, designed for research and constructed by the Institute of Applied Physics (TNO, Delft, The Netherlands),

is based on the

simultaneous measurement of the radiant intensity of a standard reflector and of the object (Bunnik, 1978).

The spectral range of this spectrometer is

between 3 6 1 nm and 2360 nm. The bandwidth for the spectral ranges 361-753 nm, 629-1226

nm and 1165-2360 nm is resp. 17 nm, 25 nm and 42 nm. The detectors

are respectively Si for the first two intervals, and PbS for the last interval. A reflectance spectrum is determined by the object-reference ratio and by means of wavelength calibration of the three spectral intervals for all the grating positions. The final data are stored on magnetic tape and a hard copy of each spectrum is presented by a table and plot print. 4.4.

Remote sensing from various platforms Remote sensing can be done from different platforms, these being:

a)

ground-borne platforms, observation stations like towers and other high

b)

airborne platforms, being balloons, aircraft and rockets;

c)

space-borne platforms including satellites and other spacecraft.

buildings;

Ad. a) The groundborne platforms are generally used in specific studies that intend later application in airborne or space-borne missions. Ad. b) Free-floating balloons may be used that have an attractive stability. The balloon's

altitude can be controlled by using ballast drops and gas

valving, while a trajectory control can be fullfilled to some degree by knowledge of wind pattern.

113 Tethered balloons may be used for particular operations e.g. in archeology or in forestry. Different payloads can be applied that may be controlled by radio from the ground.Blimps, or observation balloons, are dirigable lighter-thanair craft, mainly used by the news media as aerial television camera platforms. Aircraft present a common type of remote sensing tool. Some convential aircraft used for remote sensing are: Cessna 337, Lockheed YO-3A

(see Colvocoresses et al.,

1975).

Beechcraft Bonanza A36 and But also unconvential types

may be used such as helicopters, drones (unmanned aircraft) and sail planes.

In the atmosphere, the aircraft are subject to vibration created by the engines or other parts of the aircraft, and distortions due to both the dynamics of the aircraft and the atmosphere. For this, corrections may be necessary in preprocessing the remote sensing data. Upwards the atmosphere becomes more stable, a high stability being reached at an altitude higher than about 150 km. Ad.

c)

The

history

(Colvocoresses et al.,

of

rockets

1975).

dates

back

as

far

The development of V-2

as

the year

1891

rockets in the Second

World War gave rise to a renewed interest, which resulted in the development of spacecraft. The launch of Sputnik in the year 1957 marked the definite start of remote sensing from space, although already in 1946 space pictures were taken by a photographic camera mounted on a V-2 rocket. Several NASA-missions into space have been performed:

-

unmanned spacecraft Nimbus program 1958 up to now, TIROS satellites 1960-1965, ERTS satellites (Landsat) 1972 up to now, ATS satellite 1974,

SMS satellite 1974;

-

manned spacecraft e.g. Skylab 1973.

Other programs of NASA e.g.

the Apollo flights were mainly directed to the

observation of other planets and the earth's moon. Remote sensing of the earth's

surface was

incidental in

these

programs,

yet

often

of

great

importance to the development of remote sensing. Specifications of a number of satellites are presented in table 4.3. specifications comprise the

The

name, country, operational period, altitude,

inclination, repetition period, wavelength bands, spatial resolution and the hour of daytime coverage.

114

m

m 3

m 3

01

m

T1

u 0

..I U

.I I

Y -.

E

a Y .4

0

I

Y .4

I

Y .A

1

E 3

Y

x

D m

'0

N

4

m m

B N

x

n .9 N

I 0 N

n 01

d

m

0

4 3

h

m

.

OI YI

d m

J

h

<

E E 2

0 N. O

m

--

E

m

- I 1 3 . m -c

m 0

m m I 0

J

m h .

3

1

U

115 Although photography of the earth is possible from space, it is normally limited to manned

space-missions.

Unmanned

satellites operate with MSS,

radiometric devices or radar. However, also RBV has been applied and future application of CCD is likely. The space programme of the USSR has to be mentioned. The Intercosmos

programme (1969-1976) (Vertical

1-5,

and

1970-1977)

the rocket programme were

directed

to

for geophysical research

research the solar UV.

The

Intercosmos programme has led to meteorological satellite programmes using the Infrared (5-25

!J

m)

.

Environmental research by remote sensing in the socialistic countries was stimulated in 1975 by the foundation of a working group. In 1976 the application of a multispectral camera (the MKF-6) in the manned space flight Sojus-22 forms a remarkable event. Three filmtypes were used in the MKF-6 together with filters covering six channels centred on: 480 nm, 540 nm, 600 nm, 660 nm, 740 nm and 840 nm. The first four channels obtain a ground resolution of 20 m; the last two channels show a ground resolution of 40-50 m. For more information, one is referred to Akademie der Wissenschaften der DDR et al. (1980). The problems encountered in achieving and maintaining the proper orbit and

providing the power for remote sensing, as well as the data transmission are considered to be beyond the scope of this book. An advantage of the use of spacecraft is that it operates outside the atmospheric influence and therefore forms a

relatively

stable platform.

However, onboard mechanisms provide

oscillations and there has to be a control on dampening of these oscillations and maintainance of the proper attitude. 4.5.

The nature of remote sensing data

The

EMR coming from the sun

atmosphere ( s e e section 2.8) section 2.5 up to 2.7).

OK

other remote source interacts with the

and the objects at the earth's surface (see

The radiation is modified by this interaction.

The signal derived from reflected solar radiation, which is received by the

detector, contains the following components:

-

radiation reflected by objects at the earth's surface minus radiation absorbed by the atmosphere between sensor and object;

-

radiation reflected and scattered by atmospheric constituents (the contribution of the atmosphere).

Factors which influence the interaction are:

116

-

the dielectric properties of the materials at the earth's surface;

-

the position of the surface (slope and direction of slope) in relation to

the roughness of the surface; the incident solar radiation.

The position of the sensor has to be defined in altitude above the earth's surface (h) and in other geometrical parameters such as radius (r),

grazing

angle ( 6 ) and azimuthal angle (0) (see Fig. 4.12).

source

/

\

5'\

/

platform \I

h

\

\

\

/ \ /

Fig. 4.12

/ '

-. .7"- --.

\ ' . \ ' '

..

'r

--. ----

r=radius \

\

1

Remote sensing scheme. h = altitude of platform r = radius, distance from the detector to the point of interest 0 = angle from the vertical or nadir measured from the platform B = grazing angle, complement of 0 0 = azimuthal angle, angle measured about the nadir from a reference axis (usually north)

The extent of the atmospheric influence in remote sensing is dependent on: a)

the density of the atmosphere and the dynamics of atmospheric conditions;

b)

the path length of rays between target and sensor;

c)

the wavelength of radiation to be sensed.

Ad. b ) With regard to path length, it will be clear that vertical transmission will suffer the fewest losses from atmospheric interaction. Furthermore, if spacecraft and high-altitude aircraft are compared with lowaltitude aircraft, the former will show a more pronounced influence of the atmosphere owing to the greater path length. Ad. c) The transmission of short wavelength radiation ( < 0.3 u m) is largely obstructed by O2 and O3 in the atmosphere (fig. 2.14), wavelength

radiation is

strongly scattered by

while 0.3-0.5

molecules and

u m

other tiny

particles. Therefore, most satellites start their detection in the wavelength

117 zone beyond t h a t l i m i t (0.5

LI

m), a l t h o u g h a.0.

Nimbus 7 and Landsat 4 , form a n

exception t o t h i s statement ( s e e t a b l e 4 . 3 ) .

4 . 6 . Ground-investigations The s i g n a l s o b t a i n e d by a d e t e c t o r from a remote s e n s i n g p l a t f o r m can be compared f o r c a l i b r a t i o n w i t h s i g n a l s a c q u i r e d from r e f e r e n c e o b j e c t s . However, the

calibration

of

multispectral

scanning

signals

in

the

Visible

g e n e r a l l y done w h i l e t h e s c a n n e r i s r u n n i n g ( s e e Higham e t a l . ,

zone

is

1973).

The d a t a a c q u i r e d by a i r b o r n e o r spaceborne s e n s o r s can a l s o be compared with ground-measurements.

The ground equipment s h o u l d p r e f e r a b l y have t h e same

bandwidth a s t h e remote s e n s o r , and t h e a t m o s p h e r i c c o n d i t i o n s a t t h e t i m e of ground-measurements and remote measurements have t o be t a k e n i n t o a c c o u n t . Test-sites

a r e u s u a l l y r e q u i r e d and have t o be s e l e c t e d c a r e f u l l y i n o r d e r

t o obtain information v a l i d f o r

much

larger areas.

Fig.

4.13

indicates the

p r o c e d u r e s t h a t c a n be followed f o r t h e s e l e c t i o n of t e s t - s i t e s .

Study of e n v i r o n m e n t a l maps and r e p o r t s

t V i s u a l i n t e r p r e t a t i o n of mono- and m u l t i t e m p o r a l s a t e l l i t e MSS imagery

P r o c e s s i n g of d i g i t a l HSS d a t a i n s e l e c t e d a r e a s

Airphoto-interpretation

of s e l e c t e d a r e a s

S e l e c t i o n of t e s t - s i t e s f o r ground measurements

Fig. 4.13

P r o c e d u r e s f o r s e l e c t i o n of t e s t - s i t e s .

The l o c a t i o n and t h e number of t h e measurements depend on t h e v a r i a b i l i t y i n t h e t e s t - s i t e s a s d e t e c t e d by remote s e n s i n g and by f i e l d w o r k . Some q u e s t i o n s a r e : a)

What a r e t h e p a r a m e t e r s t h a t have a marked i n f l u e n c e on i n t e r a c t t o n w i t h

118 t h e EMR? b)

What

is

t h e s p a t i a l v a r i a b i l i t y of

t h e s e p a r a m e t e r s w i t h i n t h e mapping

unit? There a r e two s i t u a t i o n s i n t h e s e s t u d i e s :

-

t h e open s i t u a t i o n , when t h e remote s e n s o r s t i l l c a n be s e l e c t e d ; t h e c l o s e d s i t u a t i o n , when t h e remote s e n s o r h a s a l r e a d y been s e l e c t e d .

The s t e p s t h a t can be f o l l o w e d i n t h e open s i t u a t i o n a r e i n d i c a t e d below.

Phase

1:determine

differences

between mapping

units/list

soil-,

rock-

and

plant properties. Phase 2: d e t e r m i n e q u a n t i t a t i v e d i f f e r e n c e s between mapping u n i t s e.g.

COlOUK

(Munsell S o i l Colour C h a r t ) , a l b e d o , s p e c t r a l c h a r a c t e r i s t i c s . Phase 3: d e f i n e c o n t r a s t s between mapping u n i t s . Phase 4 : s e l e c t remote s e n s o r ( s ) . The measurements i n t h e f i e l d a r e p r e f e r a b l y c a r r i e d o u t on p l a c e s where much i n f o r m a t i o n of l a r g e r u n i t s can be e x p e c t e d . Repeated measurements a t d i f f e r e n t p l a c e s w i t h i n t h e same u n i t a r e c a r r i e d o u t t o d e f i n e s p a t i a l v a r i a b i l i t y . When d e v i a t i o n s of t h e mean a r e e s t a b l i s h e d t h e y have t o h e s t u d i e d and e v a l u a t e d for their significance. Statistical

processing

of

the

data

enables

the

definition

of

spectral

p r o p e r t i e s o v e r a r e a s e q u a l t o o r l a r g e r t h a n t h e r e s o l u t i o n element of

the

remote s e n s o r , and c o r r e l a t i o n of s p e c t r a l p r o p e r t i e s w i t h p a r t i c u l a r m a t e r i a l properties. G e n e r a l measurements, a p p l i c a b l e t o remote s e n s i n g i n t h e V i s i b l e ,

near

I n f r a r e d , f a r I n f r a r e d a s w e l l a s Radar may i n c l u d e t h e f o l l o w i n g :

-

t o p o g r a p h y / p o s i t i o n , s h a p e and e l e v a t i o n p l o t t e d t o s c a l e ;

-

particle size,

-

mineralogy of f i n e e a r t h ( < 2 mm) and c o a r s e f r a m e n t s ( > 2 mm); s h a p e and

s t r u c t u r e , s u r f a c e roughness

(by c o r d l e n g t h o r t e m p l a t e

and p h o t o g r a p h s ) ;

c o a t i n g s of p a r t i c l e s ;

-

s o i l m o i s t u r e c o n t e n t and o r pF v a l u e , p l a n t water c o n t e n t ;

-

leaf area;

-

c o n d i t i o n of f o l i a g e ( g r e e n , m o t t l e s , d i s c o l o u r e d a t edges).

s o i l c o v e r ( s t o n e s ; l i c h e n s , burned m a t e r i a l , dung, s t r a w ) ;

p l a n t h e i g h t and d e n s i t y (4: of c o v e r a g e ) ;

119 The photographs for application in surface roughness have to reveal shadows at oblique illumination. The photographs can be taken from a vertical position and by preference the sun should be relatively low in order to obtain shade. They appear to be useful in the determination of micro-roughness.

In addition, dielectric measurements can be carried out with an ellipsometer. which consists of a transmitter system that produces a polarized wave incident on a

sample. It has a rotatable linearly polarized receiver system. By

measurement of

the angle of rotation of the receiver system, the ratio of

maximum to minimum values of power reflected by the sample and the angle of observation, the dielectric properties can be evaluated (Lee, 1975). When the remote sensing aid is fixed, the measurements are generally more specific and may include: reflectance (in laboratory and field) of rocks, soils and plants by spectral photometers or filterband photometers (Visible and Near Infrared missions); insolation X = 0.3-3.0

pm (Visible

and

Infrared

missions)

including

azimuth and elevation of the sun, sunrise, sunset, duration of twilight (related to navigation aspects in thermal Infrared missions),

cloud

cover, quantitative measurements with a pyranometer involving continuous recording of

total

incident radiation 0.3-3.0 u

m

from

the

full

hemisphere above the instrument; ground

temperatures

(thermal

Infrared

missions),

including

surface

temperature, subsurface temperature, radiometric temperature (thermal Infrared radiometer); micrometeorological measurements (thermal Infrared missions),

including

air temperature, relative humidity, wind velocity and direction. The surface temperature can be measured with a so-called thermistor, a semiconductor which changes its electrical resistance as a function of

its

temperature. The data obtained in thermal Infrared missions are also of importance to passive microwave sensitometry. An

example

of

reflectance measurement

is

discussed

below

(Agricultural

University, 1980). Field measurements have been carried out with an EG&G spectro-radiometer (Type 550/585).

The speed of measurement is approx. 2 min. and the applied

aperture 20". When the measurements are carried out from a height of 2 m, a

120 surface-area of 0.4 m2 is measured on the ground. The apparatus can be fastened on a plate which is connected to a tube. The latter is mounted on top of a landrover (see fig. 4.14).

During transport the device has to be removed.

The spectral range of the EG&G spectrometer is 400-825 nm. A face-plate painted with Kodak white reflectance paint measured

at

regulat

intervals,

the

(Bas041 is used as a reference. When reference

enables

to

normalize

the

measurements thus making mutual comparison possible. Measurements were carried out around 09.30 a.m. to obtain illumination angles close to the Landsat crossing.

Fig.

4.14.EG&G spectrometer mounted on a landrover for measurement in the field.

For comparison with Landsat CCT, the field measurements on reflectance are converted to a linear scale 0-255 0.5-0.8

p

corresponding to the Landsat hands in the

m range. The sensitivity of the spectroradiometer as well as the

wavelength range sensitivity of the remote sensor have in this conversion.

to

be taken into account

121 Other spectrometers are often used in Dutch research such as the biomass meter operating 0.846

It

in

the

channels:

0.565-0.569

pm

,

0.615-0.675

~nn

and

0.834-

pm

is constructed by

TFDL

(Technical and

Physical Engineering Service,

blageningen, The Netherlands) and has a light-weight measuring unit connected to a tube. This enables to perform measurements from a height of 1 , 5 m above the surface in holding the tube and measuring unit by hand above the target. For large-scale airborne missions, reference objects larger than the ground resolution can be

placed

in the field to serve as a reference during

recording. In small-scale missions, this is not applicable, and natural or cultural objects of known reflectance have to be used for calibration of the remotely sensed data, instead of,

OK

together with internal references.

Mapping units which are relatively homogenous may be used, but also objects such as roads, houses and concrete dams. Much attention has to be paid in the field to the selection of such reference fields. If no reference fields are available other normalisation procedures are needed in comparing multitemporal data.

In the sequence laboratory-field-remote sensing data, the spectral resolution that

may

be

obtained

is

decreasing, and

the

atmospheric influence is

increasing. In other words, the study in laboratory and field may reveal aspects that cannot be studied from a great distance. Often, it will only be possible to study broad intervals from a great distance, and the effect of certain properties can only be shown to a limited extend. 4.7

Conclusions The eye is an instrument offering u s the capability for detection in the

Visible part of the EM spectrum. There are three cone pigments which show sensitivity peaks

at wavelengths of

435

nm, 520-550

nm and

550-595

nm

respectively. Colours can be produced by addition as well as by subtraction (or absorption) of light of specific wavelengths. The so-called c?Jour circle may be used for understanding these basic ways of colour composition. Furthermore, the ITC Colour Chart may be used as an aid in description of photographic colours. Detection of EMR may be done by photographic techniques which cover the wavelength range between 0.3 u m and 0.9 p m. Filters and special films are used for detection in specific wavelength ranges. The main photographic film

122 types are the panchromatic or black-and-white film, the true colour-film, the Infrared black-and-white film and the false colour-film. Non-photographic

techniques are required for detection in the longer

wavelength regions. The airborne line-scanner may be used for detection in the Visible

and

the

Infrared. A

special detector composed of heat-sensitive

material has to be used for far Infrared. Remote sensing may be done from different platforms e.g.

airborne and

space-borne platforms. The common airborne platforms are the conventional aircraft but also other types such as balloons, helicopters and drones may be used. Of all spacecraft, satellites are the most important aids for remote sensing. The ERTS-satellites or Landsats are available for land mapping on a small-scale basis. They employ four bands at 500-600 nm, 600-700 nm, 700-800 nm and 800-1100 nm respectively. Ground investigations may be a support in selecting remote sensors and in the processing of remote data; special measurements are often necessary. The spatial variability of soil, rock and plant parameters in the mapping units is essential. Therefore, a statistical approach is advised in obtaining reflectance measurements (as well as other measurements) in the field. The measurements should be applicable over an area equal to or larger than the resolution element of the remote sensor. Furthermore, reference fields have to be selected and defined according to significant properties. The ground investigations have to be correlated with the remote data in dependence of detector characteristics and have to be corrected or normalized for atmospheric influence. 4.8.

References

Agricultural University, Soil Science and Geology, 1980. Onderzoek naar de Methodiek van Visuele Interpretatie en Semi-automatische Verwerking van Satellietopnamen. L.H. Wageningen. Vakgroep Bodemkunde & Geologie, 5050048, The Netherlands: 43 pp. Akademie der Wissenschaften der DDR, VER Carl Zeiss Jena und Akademie der Wissenschaften der UdSSR, 1980. Sojus-22 erforscht die Erde. Akademie Verlag Berlin: 283 pp. Baker, L.R., MacDonald Scott 11, R. e.a., 1975. Electro-Optical Remote Sensors with related Optical Sensors. Chapter 7 in Manual of Remote Sensing (editor R.G. Reeves). her. SOC. of Photogrammetry, Falls Church, Virginia: pp. 325-366. Bunnik, N.J.J., 1978. The multispectral Reflectance of shortwave Radiation by Agricultural Crops in Relation with their Morphological and Optical Properties. Thesis Agricultural University, Wageningen, The Netherlands: 176 pp.

123 Bijleveld, J.H. and Rosema, A., 1980. A study of Satellite Remote Sensing Application and Mission Objectives in Developing Countries. EARS bv., Delft, The Netherlands: 164 pp. Colvocoresses, A.P. et al., 1975. Platforms for Remote Sensors. Chapter 10 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 539-588. Davson, H. (ed.), 1962. The Eye. Vol. 4. Visual Optics and the Optical Space Sense. Academic Press, New York and London: 432 pp. Eastman Kodak Cy, 1970. Kodak Filters. B-3. Gerritsen, F., 1972. Het Fenomeen Kleur. Cantecleer b.v. De Bilt, The Netherlands: pp. 5-80. Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Mulitspectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology. ESRO CR-231, Neuilly, France: 186 pp. Hunter, R.S., 1975. The measurement of Appearance, John Wiley & Sons, New York: 348 pp. Judd, D.B. and Wijszecki, G.W., 1963. Color in Business, Science and Industry. John Wiley and Sons, New York. Julesz, B., 1975. Experiments in the Visual Perception of Texture. Scientific American, April 1975: pp. 34-44. Karssen, A.J., 1975. The Production of a Cartographic Colour Chart. ITCJournal 1975-1: pp. 101-106. Kaufman, L., 1974. Sight and Mind. An Introduction to Visual Perception New York, Oxford University Press: 580 pp. Land, E.H., 1977. The Retinex Theory of Color Vision. Scientific Amer can, December 1977: D D . 108-129. Lee, K. et al., 1975. Ground Investigations in support of Remote Sensing. Chapter 13 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: p. 805-856. Lillesand, T.M. and Kiefer, A.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. Rudd, R.D., 1974. Remote Sensing: a better view. Duxbury Press, North Scituat Masachusetts: 135 pp. Sabins, F.F. Jr., 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Franisco: 426 pp. Slater, P.N., 1975. Photographic Systems for Remote Sensing. Chapter 6 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 235-323. Smith, J.T. (ed.), 1968. Manual of Color Aerial Photography. Amer. SOC. of Photogrammetry: 551 pp. U.S. Geological Survey. Eros Data Center, 1981. Landsat Data Users Notes Issue no. 18. Wijszecki, G. and Stiles, W.S., 1967. Color Science Concepts and Methods, Quantitative Data and Formulas. John Wiley & Sons, Inc., New York: 628 PP. Young, R., 1964. Bringing Chaos Out of Order. Life, December 1964. 4.9.

Additional reading

Bouma, P.J., 1971. Physical Aspects of Colour. Phillips Technical Library. MacMillan and Co. Ltd. London and Basingstoke: 280 pp. Boynton, R.M., 1979. Human Color Vision. Holt, Rinehart and Winston, New York: 438 pp. Feynman, R.P., Leighton, R.B., Sands, M., 1970. The Feynman Lectures on Physics. Chapter 35. Adison-Wesley Publ. Cy-Menlo Park, California.

124 Gregory, R.L., 1966. Visuele waarneming. De psychologie van het zien (original title: Eye and Brain). Wereldakademie, W. de Haan/J.M. Meulenhoff: 254 PP Heyse, P. en Craeybeckx, A.S.H. (ed.), 1959. Encyclopedie voor Fotografie en Cinematografie. Elsevier, Amsterdam: 897 pp. Werblin, S., 1973. The Control of Sensitivity in the Retina. Scientific American, Vol. 228, Nr. 1: p. 70-80.

.

125

5.PROCESSING OF REMOTE SENSING DATA AND AUTOMATED CLASSIFICATION

Remote sensing data may contain the following information: -signal strength in one or more wavelength bands, characterizing materials at the earth's surface; -parallax differences, characterizing the geometry of objects at the earth's surface ; -distance between target and source as acquired by active radar systems. The spectral information is recorded on photographic film or on magnetic tape. These records have to be processed to obtain imagery that can be used for interpretation. A number of aspects in photographic and digital processing are treated

in

this

chapter

(par.

5.1

and

5.2).

Pre-processing and

image-

restoration are discussed briefly, while interactive processing of digital data is

dealt

with

in more

detail.

information extraction (par. 5.3) analog data (par. 5 . 4 ) .

Furthermore, some

attention is

paid

to

and automated classification of digital and

For parallax differences, the reader is referred to

chapter 7 and for active systems to chapter 13. 5.1.

Technical aspects in the processing of photographic imagery Photographic processing

involves either black-and-white technology or

colour-technology. Interaction of

light with

the silver halide crystals of the emulsion is

described briefly in section 4.2. colour-films

is treated

Processing of black-and-white, true and false

in the same section to the extent necessary for

understanding the detection of EMR by photographic techniques. Some technical aspects of processing are discussed below. The light and dark spots or grey tones of an image are systematically related to the amount of exposure of a film. Measures of darkness or lightness at given points on a film are:

-

the opacity 0

-

the transmittance T where Ii

=

=

Ii/~ P; =

Ip/Ii

total incident radiation upon the film,

126 I P

-

=

radiation passing through the film;

the density D

=

log 0

Instruments designed

=

-

log T

( 5- 3)

to measure density on

transparent film are called

transmission densitometers. When they are able to measure density on paper prints, they are called reflectance densitometers (see a.0. Canadian Standards Association, 1964).

The densitometer may have a scanning-device to obtain

density values at regular intervals over the image area. The densitometry of 0

colour-films

is

complicated by

the fact that

the three dyes used have

absorption curves that overlap one another. There are two basically different measures of colour-film density, being: the integral or combined density of the three layers and the analytical or individual density of each layer. The

integral spectral densities are measured

corresponding to

the maximum absorptances of

with

narrow band

filters

the three dyes. Analytical

spectral densities are usually determined indirectly by computati.on from integral spectral densities, by using specifications of the film manufacturer. In photographic processing attention has to be given to aspects such as: characteristic curve, spectral sensitivity, modulation transfer function, dimensional

stability,

granularity,

silver

reduction and

printing-paper

(Barrett and Curtis, 1976). Most of these aspects are discussed below. The called characteristic curve, or D

-

so-

log E curve, of photographic film shows

density (D) as a function of log-exposure (Ext).

It has an S-shape and in the

central part, the density is nearly proportional to the l o g of the exposure. The ratio a/b is referred to as the film "y" (see fig. 5.1) Two other properties can be determined aided by the characteristic curve, being density resolution, which is the smallest measurable density range (dr), and radiometric resolution, or the smallest detectable exposure range (rr). For spectral sensitivity of the different film types, the reader is referred to section 4.2.

The film types mentioned are all sensitive to Visible

radiation and must therefore be developed in complete darkness. The

modulation

transfer

function

(MTF)

describes

the

accuracy

of

reproduction of test-objects in which the luminance varies sinusoidally with the distance (Thompson ed., 1966).

It is recorded as a function of spatial

frequency (cycles/mm). At each frequency (f) of sinusoidal intensity patterns

127

---+

Fig. 5.1

Log exposure

Characteristic curve for photographic film.

(white bars gradually passing into black bars),

the values of maximum and

minimum density are determined and converted to linear relative exposure values by means of the D

-

log E curve of the emulsion. The contrast, or

amplitude at each frequency (f), is expressed as image modulation (ME(f)) the following equation (Slama ed., 1980; Eastman Kodak Cy, 1972):

by

The so-called resolving power of a film is a visually determined measure of the number of line-space pairs per millimeter. The value of resolving power will

be

different

for different developers, and

will

change

with

the

development time (Thompson ed., 1966). Granularity of

a black-and-white

photograph or

the granular pattern of

discrete particles of metallic silver can be observed under a microscope or may

be

measured

by

a

microdensitometer.

impression of non-uniformity

Graininess

is

the

subjective

in the image by an observer e.g.

at

12 x

magnification. The so-called Root-Mean-Square Granularity (G) can be determined from the standard deviation of the density measurements

a K(D)

and from the diameter

of the scanning aperture (K) after Barrett and Curtis (1976):

G

=

K a K(D)

(5-5)

MTF's along with data on resolving power and granularity provide information on the imaging capabilities of emulsions. For example, an emulsion with good

128

MTF (high response to high spatial frequency), high resolving power and low granularity will record small details. In processing, it is usually necessary to control the density of the product. This may be done by a controlled removal of the silver from the negative (reduction) or by "dodging" to decrease the density range. Dodging may

be

done with the aid of automatic dodging-printers, or manually by

inserting tissuepaper or a mask (Barrett and Curtis, 1976). The dimensional stability of the film has to be high; that is, swelling and shrinkage have to be low, in order to limit distortion of the image. Polyester base material e.g.

ESTAR-base of Kodak aerial-film is superior to

cellulose ester film bases. Carman and Martin (1968) studied the dimensional changes in ESTAR-base aerialfilm used in a Wild RC8 camera and stated that the most serious dimensional changes are due to the low relative humidity in the camera compartment. In order to reduce swelling during processing and to improve the dimensional stability, aerial photographic paper consists of a photographic paper base coated on both sides with a cellulose ester lacquer (Thompson ed., 1966). The processing of colour-films requires special attention for dyeing, colour-balance and resolution. The basis for colour separation in the dyeforming layers is the added sensitivity by sensitizing dyes that provide sensitivity to another portion of the spectrum above the natural sensitivity to blue light. A colour-former, or dye-coupler in the emulsion layer reacts with a colour-developer agent to produce specific coloured dye. The resultant dye must have definite spectral characteristics and must be stable to provide permanency of the colour-image (Smith ed., 1968). The colour reversal process is described in section 4.2.

Unfortunately as

indicated in that section, the layers are not perfect absorbers. Of the three layers, the yellow forming layer most closely approaches an ideal absorber. However, the specific ordening of layers in false colour-film enables a rather good registration of respectively Near Infrared, green and red. The prime objective of true colour-photography is to reproduce the colours of the original scene. Colour-print materials, colour filtration and masking as well as colour printing exposure should be carefully chosen. Use can be made of analyzing/balancing printing systems. In determining the need of colour correction, the density to log E-exposure

129 curves of the cyan, magenta and yellow dye layers are very helpful. These curves should lie on top of (or very close to) each other. Resolution, or the ability of film or paper to record very fine detail, is important in determining the usefulness of the material. Lens properties, nature of emulsion (e.g.

granularity), film speed and exposure are only some

of

have

the

factors

characterized

by

that lower

impact.

spatial

Generally,

resolution

but

true

colour-films

higher

contrast

are than

panchromatic films.

In multispectral photography and scanning (MSP and

EISS),

there is a need

for techniques that enable combinations of the individual products. For this purpose, positive black-and-white

imagery representing the reflectance of

scenery in different wavelength hands can be projected superimposed and in different colours.

In this way, through

different imagery may be produced e.g.

the use

of appropriate filters

blue, green and red light projectors

are used for respectively blue, green and red band imagery to produce true colour, and the same series of projectors for respectively green, red and Near Infrared

band

imagery

to

produce

false

combinations may be produced as well.

colour.

Multitemporal

one-band

This way of combining is normally

described as the additive colour technique. Willems et al., (1977) discuss recording processes based on other lightsensitive compounds than silverhalides. One of these processes, the so-called diazo-process

is of importance for multispectral remote sensing, since it

offers the possibility to contact-print positive, or negative black-and-white imagery, in colour. The coloured images can be combined to colour-composites by subtractive colour techniques. A diazo-film consists of a transparent acetate base containing a slow reacting

Ultraviolet sensitive emulsion with diazonium salt. On exposure to Ultraviolet radiation, the diazonium salt desintegrates and reacts with a coupler, which prevents formation of dye at the exposed places. On the other places so-called azo-dye is formed; the reaction can be accelerated by ammomium vapour or liquid. The use of vapour is preferred since it does not involve serious dimensional changes of the acetate film. The diazo-materials possess a limited density range. Fig. 5.2 shows densityranges of yellow diazo-film obtained from a black-and-white positive with exposure times ranging from 1 min. to 6 min.

130

1.5-

0

0

0 n

0

1.0-

0 0

0

0

0

0

.

0

0

. X

0.50

0

y'

(L)u

x

0 X

i

A

A

A

+

BW

o

1 min. 2 min. 3 min. 4 min. 5 min. 6 min.

0

A

0 x A

0

I

1

I

5

10

15

Fig. 5.2. Density for grey scale of positive material and a series of yellow diazo-material exposed according to a time range from 1 min. up to 6 min. (constant development). Diazo colour-films are available in a number of colours a.0. and

cyan.

The

yellow, magenta

colours mentioned are used for the production of colour

composites. The variability between the diazo-materials of different orders and the density differences between the yellow, magenta and cyan diazomaterials offer special problems

in obtaining colour composites of good

quality. In spite of these problems, the low price of these materials causes a high application rate.

In

storage,

the

acetate

films

present

problems

with

regard

to

their

dimensional instability. However, diazo-film on a polyester base has come on

the market recently and shows an improved stability (Pinot de Moira, 1974; Venema, 1980) 5.2.

.

Processing of digital data The records of non-photographic sensors have to be converted into one of

the following forms:

-

photographic imagery

-

computer compatible (digital magnetic) tapes (CCT) and discs;

-

computer print-outs, plots, diagrams.

on

transparent film or paper;

Computers can interact with optical data, which makes it possible to store a picture in digital form or to produce a picture from digital data. The principal types of equipment of such computers are (Barret and Curtis, 1976) :

-

drum microdensitometer and recorder;

-

electron beam and laser recorders.

cathode-ray tube (CRT) readers, writers and displays; The so-called image-restoration process compensates for data errors,

noise and geometric distortions in the scanning and transmission processes.

In order to make the image resemble the original scene as much as possible, the process may include the following (Sabins, 1978):

-

correction for the drop-out of scanlines (e.g.

Landsat 1, data from one

of the six detectors were not recorded owing to a hardware" problem);

-

correction higher

-

OK

on

the detection level (with time, detectors may drift to

lower levels than the original one);

correction on horizontal offset of scanlines; correction for atmospheric scattering to improve image contrast; correction for geometric distortions which are due to variations in platform attitude, velocity and altitude (nonsystematic distortions)

OK

scan skew and distortions or variations in scanner mirror velocity (systematic distortions);

-

corrections

on

noise due to storage, transmission and ground reception of

data. The effect of scanner distortions is low in satellite scanners having a small

*

Hardware: mechanical and electronical part of computer. Software: programs for input of data, processing and output of computer.

132 scan angle (5.8"

for Landsat),

and high in airborne scanners that have scan

angles of 45" or 60" (Sabins, 1978). The two basic methods of data processing are batch processing and interactive processing. In batch processing, the desired processing programs are specified beforehand and the operator sees no results until the processing has been completed. Batch processing is useful a.0.

for image restoration and

enhancement.

In

interactive

processing,

the

operator

may

provide

instructions

and

information to the computersystem at various stages in the processing cycle. Special-purpose computers are needed for interactive image-processing-systems. They include units such as tape-reading devices, display devices and control panels. Sabins (1978)

listed a number of commerciable available interactive

systems (see table 5.1). Table 5 . 1 Commercial available interactive-processing systems. Processing system

Manufacturer

Address

Series 9

Bendix Aerospace Systems Division Comtal Corp.

IDIMS

ESL Inc.

IMAGE 100

General Electric Co., Space Division Stanford Technology Corp.

3621 South State Road, Ann Arbor, Mi. 48107 169 North Halstead, Pasadena, Ca. 91107 495 Java Drive, Sunnyvale, Ca. 94086 P.0 Box 2500, Daytone Beach, Fla. 32015 650 N. Mary Avenua, Sunnyvale, Ca. 94086

MDAS

System 101

As an example, an imteractive digital processing method is described below (Donker and Mulder, 1977).

The software has been written in Fortran IV.

Use is made of the PDP 11/45 computer, a grey-scale printer and CCTs of Landsat. A selected part of the CCT is reformated and stored on magnetic disc. Half of the disc is used for storage of calculation results. In this way, only 3.4

percent of the original Landsat frame can be stored that is 260.000

pixture elements (pixels). The following steps have been distinguished in the analysis of Landsat MSSdata:

133 a. Display of individual MSS bands (level by level display) and histogram equalisation. In histogram equalisation, the whole range of levels of radiance is subdivided into intervals that contain roughly the same amount of pixels. Images with enhanced contrast may be produced in this way. However, it may be necessary to shift certain levels in order to enhance the imaging of certain features. Level

by

level display,

followed by

ground

investigations enables

the

selection of radiance levels which are significant to the purpose of the study. This, together with histogram equalisation produces particular images of the individual spectral bands. b. Feature plane, At this stage a number of radiance levels per band are known to be significant for the purpose of the study. From each type, a number of pure pixels are sampled, that is the x-y coordinates are read from the image print-out. A feature plane plot of the selected sample-set of all combinations of two of the four spectral bands (six combinations for Landsat) is displayed. In fig.

5.3 the feature plane plot of bands 7 and 5 of the Roermond test-site is given as an example.

7

30

a r a b l e 1a n d

20

10

5

water

0

I

0

10

*

I

20

.

I

30

.

I

40

50

Fig. 5.3. Feature plane plot of bands 7 and 5 of the Roermond test-site after Donker and Mulder (1977).

134 The feature plane plots enable us to obtain insight in the structure of the spectral data. Contrast and intermixing of clusters can be evaluated. In Fig. 5.3 a low contrast of surface waters with towns, of scots pine forest cover with several other forest cover types, and the intermixing of arable land with villages, can be observed.

C.

Principal component transform (PCT).

The spectral vectors of the sample set can be transformed linearly to new variables (principal components or PCs) by digital processing. The first new variable (PC1) has to account for as much of the total variance as possible. The second new variable (PC2) has to account for as much of the total remaining variance, etc. In this example, the PC1 and PC2 together account for

98 X of the total variance of the sample-set. Therefore, there is no need for PC3 imagery and thus a significant reduction in the number of data is attained. The principal components of the Roermond test-site were as follows: Ipcl = (0.2 x 14)

+

(0.4 x Is)

+

(0.8 x

I6)

+

(0.5 x 17)

Ipc2 = (0.5 x 14)

+

(0.7 x Is)

-

(0.2 x Is)

-

(0.4 x I ) 7

The PC1 is a weighted summation of the 4 MSS channels; the PC2 offers a high contrast between vegetated and non-vegetated areas. Together, they provide for most of the information contained in 4 bands and data reduction is obtained. d.

Rotation of the principal axis.

One can judge from the PC1

-

PC2 plot, whether rotation of the axes over a

certain angle might be needed to obtain maximum distance between spectral clusters that are significant for the purpose of study. Fig. 5.4 illustrates the result of a 30'

rotation by digital processing; the elongated water

cluster after rotation is more OK less parallel to the rotated PC1 (PC1');

so

are a number of land use classes. The result is an improved contrast and a better display of spectral variability between several spectral classes. e.

Colour coded imaging.

The pcl

and pc2 of' pel' and PC2' images are printed together in different

colours e.g.

red and green.

Thus futher data reduction is obtained by

135 combining two images into one. There is no forced classification, the final evaluation is left to the interpreter.

60.

50-

20

10

I

30' Rotation

pc 2

pc2

30

40

50

60

Fig. 5.4.Feature plane formed by PC1 and PC2, and PClt and PC2' after 30" rotation (Donker and Mulder, 1977). 5.3

Information extraction process. Information extraction processes utilize the decision-making capability

of computers to identify and extract specific information (Sabins, 1978). It is possible to use ratios of the intensities in the different bands. A material

may

have

the

same

ratio

value

regardless

of

variations

in

illumination as occuring in hilly terrain. The shadow areas in hilly terrain do not receive direct sunlight but have a certain amount of diffuse light. Although intensity in these areas will be relatively low, the ratio can be diagnostic (see fig. 5 . 5 )

and may reveal material-properties.

However, it

eliminates the expression of topography. Change detection can be performed in studies of multitemporal data. The first step is geographic registration of corrections

with

the

aid

of

control

the images involving geometric points.

After

proper

geometric

registration and correction for atmospheric conditions, the intensities in one

136

\ I

I ___c

-t-

northwest

southeast

1)

Sandstone r e f l e c t a n c e band I band I r a t i o 4 5 4/5 0.5-0.6 urn 0.6-0.7 pm

I

sun1 i g h t

28

42

0.66

shadow

22

34

0.65

5.5.Ratio band 4 / band 5 (Landsat) of sandstone exposed to direct sunlight and in shadow after Sabins ( 1 9 7 8 ) .

Fig.

image may be subtracted from those of the corresponding image. Positive and negative values indicate change, zero means no change. For this purpose, colour-coded ratio-imagery is also very useful.

5.4

Automated classification Pixels can be classified during processing. The classes are defined

according to the statistical properties of the data, or according to the analysis of spectral signatures in training-sets. In section 5.2 an interactive method

is discussed to process the data in such a way that an image is

constructed which has a maximum capability for detection. The interpreter is expected to perform the final interpretation. Below, methods are discussed which can be used to arrive at a definite

137 automated classification of the objects (e.g.

vegetation, rock outcrops and

soil surface). Sabins (1978)

distinguishes two types of classification: the supervised and

unsupervised classification. Supervised

classification

uses

independent

information

e.g.

spectral

reflectance data to define training-data for establishing classification categories. Unsupervised classification only uses the statistical properties of the data for classification. Objects with high contrast e.g.

agricultural

land, forested land, as opposed to water bodies, can be classified according to the unsupervised classification method. However, to go more into detail in landscapes with a high variability, generally requires interactive processing methods, visual interpretation and ground-investigations to enable (supervised) classification. One

may use PC data or unmodified intensity values from three or more channels

for supervised classification. Training-sets and feature space plots are composed and classification is left to the computer. Software can be developed

in such a way, that for each point in the feature space, the distance to the centres of clusters formed by the different feature classes can be calculated. The minimum distance determines the class to which a point in the feature

space belongs. Of course, the training-set, the spatial variability of the land features and the discriminating capability of the remote sensor are of great importance for the quality of the final classification. Image features can be analysed according to their form and density with the aid of an image-analysing computer. With the Quantimet 720 (Imanco), the image is scanned at a low speed and detection is possible in more than thirty grey levels. Measurements can be obtained from: surface area, intercept, chord length distribution, perimeter, count or number and optical density of features

.

The intercept measurements involve the measurement of the number of chords

(both vertical and horizontal) formed by scanning-lines cutting the detected features. Feature measurements can be obtained by the operator interactive method (the features are selected by light pen) and by function computer methods. The latter

involves

classification.

feature-classification, The

features

are

often

that

is

identified

form-separation

and

beforehand,

the

and

Quantimet is used to obtain quantitative data about area, size, form, etc. of the

features.

However,

form

and

density

can

be

used

for

supervised

138 classification itself. The Quantimet has been applied in analysing images with high contrast. A reasonable result has been archieved in distinguishing and quantification of grasslands and forest areas on Landsat imagery. Other application in image analysis

for

remote

sensing

is

limited

e.g.

the

characterization and

quantification of different forest cover types as depicted on large-scale photographs, appeared to be impossible in cases where soil and tree-crowns could not be discriminated either on the basis of their density values or where tree crowns appeared to be interconnected on the transformed imagery (Mulders, 1977). 5.5.

Geometrical aspects The geometrical aspects include the form and position of objects as

depicted by a specific remote sensor. Any remote sensing instrument measuring reflected radiation in its angular field

of

view

is a

perspective sensor, since there exists an angular

relationship between the sensor and the object. Furthermore, the angular relationship between the incident radiation and the object may have impact on the radiation measurement. Therefore, the slope and position of the object in relation to the incident radiation and sensor determine the phenomena that can be measured by the sensor. Consequently, for a correct classification of objects in accidented terrain, the geometrical aspects have to be taken into account, which forms an extra complication. It is for this reason that most successful classifications have been carried out in flat terrain. 5.6.

Conclusions A remote sensor receives Em, which results either in a latent image of

Scenery upon interaction with (photographic techniques), OK

silver halide grains of

a

film emulsion

or is recorded in analog voltages on magnetic tape

disc (non-photographic techniques).

Both types of data have to be processed to produce imagery for interpretation. The photographic processing involves a relatively great number of variables. A proper set of processing conditions has to be chosen, which requires skill of the operator. Diazo-processes

deserve

special

emphasis

in

enabling

combinations

multispectral images OK multitemporal images in an inexpensive way.

of

139 If skill is required for photographic processing, this is certainly true for digital processing. Computer Science is a profession. Batch

processing

restoration

and

according

to

specified

image-enhancement.

programs

Generally,

is

useful

in

image-

interactive processing

is

performed in the production of imagery from digital data for environmental surveys, which involves various steps in decision making. PCT can be used for data-reduction and improvement of contrast. Information extraction of digital data may be done by the application of ratio values. Change detection is a technique for evaluation of multitemporal data, which, of course, can only be applied if the data are geographically registered. Generally, the operator intends to produce an image for interpretation, and fieldwork is felt necessary for final identification. However, automated classification reaches higher and is intended to come to a final classification. High-contrasting material objects may be classified succesfully, lowcontrasting natural objects, o r rapidly changing terrain conditions, often prevent correct automated classification. 5.7.

References

BaKKett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and Hall: 336 pp. Canadian Standards Association, 1964. Diffuse Transmission Density. CSA Standard 2 7.0.2.1.. Ottawa, Canada: 35 pp. Carman, P.D. and Martin, J.F., 1968. Causes of Dimensional Changes in Estar Base Aerial Film under Simulated Service Conditions. The Canadian Survey OK, Vol. XXII, No 2: pp. 238-246. Donker, N.H.W. and Mulder, N.J., 1977. Analysis of MSS Digital Imagery with the Aid of Principal Component Transform. ITC-Journal 1977-3: pp. 434-466 (presented in 1976 ISP Commission VII). Eastman Kodak Cy, 1972. Properties of Kodak Materials for Aerial Photographic Systems. Vol. I: Kodak Aerial Films and Photographic Plates. Mulders, M.A., 1977. Application of Teledetection in Pedology. Ier Colloque PCdologie TClCdCtection AISS ( I S S S ) , Rome: pp. 311-324. Pinot de Moira, P., 1974. Diazo Processes. The Journal of Photographic Science. Vol 22: pp. 187-193. Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. I. Theory, Instruments and Techniques. Amer. SOC. of Photogrammetry, Falls Church, Virginia: 867 pp. Sabins, F.F. JK., 1978. Remote Sensing. Principles and Interpretation. 1J.H. Freeman and Cy, San Francisco: 426 pp. Slama, C.C. (ed.), 1980. Manual of Photogrammetry. 4th edition. Amer. SOC. of Photogrammetry. Falls Church, Virginia: 1056 pp. Smith, J.T. JK. (ed.), 1968. Manual of Color Aerial Photography. her. SOC. of Photogrammetry, Falls Church, Virginia: 550 pp. 1966. Manual of Photogrammetry Vol. I.3t-d edition. Thompson, M.M. (ed.),

140 American SOC. of Photogrammetry: 536 pp. Venema, D., 1980. The Use of Diazo Colour Film in Remote Sensing Imagery Reproduction. ITC-Journal 1980-1: pp. 140-142. Brinckman, E., Delzenne, G. en Poot, A . , 1977. Alternatieven Willems, J.F., VOOK Zilver. IGT-nieuws 30, NK. 2: pp. 33-39. 5.8.

Additional reading

Agterberg, F.P., 1974. Geomathematics. Mathematical Background and Geo-Science Applications. Elsevier Scientific Publishing Cy, Amsterdam: 596 pp. Cutbill, J.L., 1971. Data Processing in Biology and Geology. Publ. for the Systematics Association. Academic Press, London: 346 pp. Hall, E.L., 1979. Computer Image Processing and Recognition. Academic Press, New York, London: 584 pp. Hammond, R. and McCullagh, P., 1974. Quantitative Techniques in Geography: An Introduction. Clarendon Press, Oxford: 318 pp. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. 1978. Digital Image Processing. John Wiley & Sons, New York: Pratt, W.K., 750 pp. Rietbergen, D. and Steijn, L., 1972. Computers. Moderne Slaven in een Nieuwe Tijd. Samson Uitg. N.V., Alphen aan den Rijn: 191 pp. Schllpfer, K., 1980. Kopierschichten: sensitometrische Eigenschaften und Anwendung. UGRA Auftrag 1/2, St. Gallen: 24 pp., 35 Beilage. 1976. Der Einsatz von Diazofilmen in der Druckformherstellung Wolf, H . , Deutscher Drucker, NK. 22: 2 pp. Wijzecki, G. and Stiles, W.G., 1967. Color Science. Concepts and Methods. Quantitative Data and Formulas. John Wiley & Sons, Inc. New York: 628 pp.

141 6.IMAGE CHARACTERISTICS

Most images jointly possess the property of being structures of grey or colour tones. However, it will be apparent from the previous chapters, that there are large differences between photographic imagery on one side and images derived from non-photographic

sensors on the other side. General

characteristics of imagery such as resolution and scale (par. 6.1),

tone and

contrast (par. 6.2) are defined in this chapter. Furthermore, examples are presented on different types of images, being a first introduction to the image products of remote sensing (par. 6 . 3 and 6.4). Image enhancement techniques are discussed in par 6.5. 6.1.Resolution

and scale

Resolution concerns the minimum separation between two objects, that is the distance at which the objects appear distinct and separate in an image. Objects that are spaced closer together than the resolution limit do not appear as single objects. Scale is the ratio of the distance between two points on an image to the corresponding distance on the ground. The image-scale is determined by the angular field of view and altitude of the remote sensing device, and the magnification factor in reproduction of the image. Without magnification, the scale (S)

of airphotos can be calculated as

follows:

where c

focal length in m and Z

=

=

camera height above the ground in m.

Ground resolution or spatial resolution, that is the ability to resolve features, can be calculated for aerial photography (Sabins, 1978) by: Rg

=

Rs.c/Z

where R g

=

Rs

=

(6-2) ground resolution in line pairs (one black and one white line) per m.

system resolution or resolving power in line pairs per mm,

142 Z

=

camera height above the ground in m,

c

=

camera focal length in mm.

Radians are used to describe the so-called angular resolving power (the radian or rad is the angle subtended by an arc of a circle having a length equal to the radius of the circle; since there are 2 is equal to 57.29').

rad in a circle, a rad

TI

The angular resolving power of a system may be calculated

by dividing the length in m of the subtended arc between the closest two lines on the ground (that can be depicted by the system) by the distance in m between the remote sensing system and the ground. In remote sensing with non-photographic sensors, another term is needed, being: the instantaneous field of view (IFOV), instrument's

which is determined by the

optical system and the size of the detector element. It is a

measure for the resolution of scanning devices; the time of recording for one scan is divided into small instants, so that at any one instant only EMR from a small part of the total scan area is being recorded. The IFOV or 6 of a system in rad is given by (Lillesand and Kiefer, 1979):

where D

=

length in m of subtended arc corresponding to the diameter of the circular ground area viewed,

Z = flying height in m above the terrain. The terrain characteristics may be such, that objects smaller than the ground resolution are depicted. This aspect is described by the detectability. The detectability is the ability of an imaging system to indicate the presence or absence of an object. When the contrast of an object with its surroundings is very high, it may be detected even when its dimensions are smaller than the ground resolution, since it influences to a great extent the reradiation of the resolution element. One has to distinguish imaging and non-imaging detectors. If one uses a photographic film as a detector, an image is formed from the field of view by interaction of radiation with silver halide grains. The radiation is composed of reflected radiation from different objects within the field of view, as well as from so-called airlight (the attribution of light from the atmosphere between object and sensor).

The radiation is directed

to

the photographic film

143

by a lens system. equation 6-2,

The spatial resolution can be calculated according to

where Rs

is amongst others dependent on the granularity and

sensitivity of the film. The non-imaging detectors measure the total radiation of their IFOV in one or more spectral bands. An image may be produced by an imaging device such as a TV system, through composition of the IFOV signals, which thus act as picture elements

(pixels).

The spatial resolution of

the non-imaging

determined by its IFOV and the speed of detection in relation

to

detector is the speed of

the remote sensing platform. For instance, a line-scanning device may show overlap between adjacent lines resulting in a smaller effective resolution element than its IFOV. When spatial resolution of a line-scanning device is given, the quality in relation to the number of pixels per mm that are shown on the image, and the scale of the imagery can be indicated (see table 6.1). Table 6.1.

Spatial resolution of line-scanning devices and image quality.

spatial resolution in m poor ( 4 pixels/ mm) but tolerable distance in m/mm 10 30 70

40 120 280

Image quality has

scale 1: 40,000 1:120,000 1 :280,000

to be

image quality fair ( 8 pixels/mm)

good ( 1 2 pixels/mm)

distance in m/mm

distance in m/mm

80 240 560

scale 1: 80,000 1:240,000 1:560,000

120 360 840

scale 1: 12,000 1:240,000 1:840,000

considered separately from recognizability,

detectability and resolvability of objects (oral communication Ir. Loedeman). An example may illustrate this: although the image quality may be good, a row

of poles is not directly recognizable as such on radar imagery; it has to he interpreted from the imaging properties of the system. The row is detectable but individual poles are not resolved separately. 6.2.

Grey tone, contrast and colour Brightness is a sensation of the eye related to the intensity of light.

The brightness variations of a Black and White image may be calibrated with a grey scale. In practice, a mental concept of such a scale is used: the socalled grey tone e.g. light, intermediate and dark tones. Image contrast may be defined as the ratio between the reflecting power

144 of the brightest (Bmx

in W) and darkest (Bmin in W) parts of the image, the

so-called contrast ratio (Cr):

Colour vision is dealt with in par 4.1.

For the processing of photographic

films, the reader is referred to par. 4.2.

The notations given by the colour-

chart (plate 3) if used as a COlOUK characteristic, provide a rough measure for the amount of dye in the film and illustrate the subtractive COlOUK formation. The use of a vector notation for the transmitted light enables to understand the observed COlOUKS on the imagery (see Fig. 4.6). 6 . 3 . Airphotos

Basically an airphoto presents a structure of grey (Bennema

and

Gelens

1969),

which

enables

the

OK

colour tones

recognition of

objects.

Particular tone features may he indicated, such as:

-

grey (or colour) tone and grey

(OK

colour) tone changes related to the

reflection of light from the surface of objects;

-

shadows of objects being helpful in recognition of high features such as trees and houses;

-

mottling

OK

spots in darker or lighter tone than the main surface,

usually with an irregular pattern, shape and size. Size and arrangement of objects can be described by structures, patterns and textures. Pattern is concerned with the spatial arrangement in repeated sequence

and/or

characteristic order

of

objects.

Texture

concerns

the

repetition of objects too small to be considered as individual elements (Bennema and Gelens, 1969). The boundary between structure and texture can he fixed at 1 mm. relation to scale, 1 mm means: 1: 5.000 -

5 m

1: 40.000

-

10 m

1:100.000

20 m

1:500.000

1:10.000 1:ZO.OOO

-

The following subdivision of textures may be used: fine

<

0.2

medium 0.2 coarse 0.5

mm

-

0.5 mm 1 mm

40 m

100 m 500 m

In

145 At 5/10,000 scales

CKOW~S

of trees, having a diameter of 5 m, give rise to

coarse textures, at a 20,000 scale to medium and at a 40,000 scale to fine textures. Structures are generally described according to both:

-

size (diameter

OK

-

width)

fine 1-3 mm medium 3-5 mm coarse

>

5

mm

shape and pattern arrangement

-

linear,

e.g.

parallel,

stripy,

feathery,

marbled, streaky pattern;

-

non-linear,

e.g.

grid-,

mosaic-,

spongy,

speckled, dot-, cloudy, patchy pattern. Example: Coarse patchy pattern with fine textured elements (scale 1:20,000). Since the size of the objects, as visible on the imagery, is connected to the image-scale, the scale has to be mentioned always!

If needed for the

purpose of description and distinction between different units, the shape of individual objects, and their arrangement in textures, may be given also. Fig.

6.1 provides a summary and illustration on textures and patterns. The effect of scale is illustrated in Fig. 6.2.

It shows a 1:33,000 scale

image, a 1:17,000 scale image, an enlargement of the 1:17,000 to a 1:10,000 scale image and an image recorded on a 1:10,000 scale. Part of the 1:33,000 image is enlarged 12 x to show graininess, resulting in a 1:2750 scale. The image quality of Fig.

6.2b

is very poor, which does not surprise the

observer due to the high enlargement factor. Also a comparison of Fig. 6.2d with 6.2e

illustrates the decreasing quality upon enlargement. However, the

quality of 6.2d

is still acceptable and enlargement factors of 4 x

OK

5 x are

normally considered feasible. The series of airphotos of Fig. 6.2 clearly indicate the importance of scale in relation to the variability of landscape. The 1:44,000 airphotos enable only a rough division in landscape-units based on relief and drainage pattern. The 1:13,000 airphotos present the opportunity to go into much more detail, and land components can be delineated, based on slope, site, land-use and tone-analysis. The 1:22,000 photos are intermediate in this respect, as they show tone patterns, but the land components are too small to be indicated on the map. Only land units can be distinguished at this scale. Therefore,

146 S i z e o f s t r u c t u r e - e l emen t s

Textures

fine

0,2

3 mm

mm

medium

0,5

5 mm

mm

S I o0oo

coarse

7 mm

1 mm

Exarnpl es shape o f e l e m e n t s

Arrangement o f s t r u c t u r e s

1i n b a r e l e m e n t s p l / p a r a 1 1e l

non-1 i n e a r e l e m e n t s

lo

lo

'1

' 0

sk/speckled

1i n e a r o r e l o n g a t e d straight

[c u r v e d

1

4

broken

non-1 i n e a r o circular

m

fl bean-shaped ,g e l l i p t i c a l

f e / f ea t h e r y

1

1

'

square

1

0 rectangular fi s t a r shaped

0

0 , 0 0 0 0

c l / c l oudy O & p

0 00

rn

sylstreaky

Fig.

6.1

T e x t u r e s , p a t t e r n s and examples of shapes

a

irregular

147

Fig.

6.2 Airphotos

of d i f f e r e n t s c a l e s of an area between Mundbrega Maluenda, Prov. Zaragoza, Spain. ( a ) 1:44,000 (1959) ( c ) 1:22,000 (May-June 1974) ( b ) 12 x ( d ) 1: 11,000 ( e n l a r g e d from ( e ) 1:13,000 (November 1980) 1:22,000)

and

148 landscape variability has to be evaluated in determining the proper scale for the purpose of the study. In this case, it concerns eroded land with high variability and consequently a large scale is necessary, if mapping of soil series is wanted. 6 . 4 . Images derived from line-scanning devices

The line-scanning devices produce images that consist of picture elements or pixels arranged in regular lines or columns. The pixels can be located by x and y coordinates and the brightness of each pixel, ranging from black to white, can be related to a grey-scale intensity value. The aspects dealt with in the sections 6.2

and 6.3

concerning grey

OK

colour-tones, size, shape and arrangement of objects are also applicable to imagery derived from non-photographic sensors. Some specific features of line-scanner imagery are discussed below. Landsat images are parallelogram-shaped, due to a correction for earth rotation during the 28 sec.

required to scan the earth over the image frame area. The

multispectral scanner of Landsat has four channels sensitive for green ( 4 ) , red ( 5 ) and Near Infrared ( 6 and 7) respectively. The spatial resolution of Landsat-imagery is determined by the 56 m by 79 m effective ground resolution cell, the atmospheric conditions, the play-back and reproduction of the imagery, as well as the contrast ratio of the scene. An

average for the spatial resolution is 200 m to 250 m, although much

smaller, but highly contrasting features such as highways, may be detected as well.

In contrast to imagery derived from airborne scanning, Landsat-images show little geometric distortion due to their narrow scan angle. Geometric distortions in airborne scanning are inherent to the large scan angles which are used. Since the scanner mirror rotates at a constant linear rate, the ground resolution cells at either end of the scan line are larger than the resolution cells in the center of the scan line directly beneath the aircraft. However, they are recorded at an equal size as compared to the center cells, which causes compression of the scenery at the edges of the image. This is illustrated in fig. 6.3. Aircraft motion distortions involve roll (rotation of the aircraft about the longitudinal axis) and the effect of cross-winds. Both distortions can be compensated during the flight.

149 Weather c o n d i t i o n s may have a g r e a t impact on t h e q u a l i t y of t h e imagery. This

is

especially

true

for

t h e r m a l imagery,

where s u r f a c e winds

lead

to

smears and s t r e a k s on t h e images.

F1 i g h t direction

b ) R e s u l t i n g image d i s t o r t i o n caused by r e c o r d i n g a t constant l i n e a r r a t e .

a ) T e r r a i n f e a t u r e s which a r e scanned a t c o n s t a n t angular r a t e . Fig. 6 . 3 An

Geometric d i s t o r t i o n of s c a n n e r images a f t e r S a b i n s (1978).

IRLS ( I n f r a r e d

Line

Scanning)

image

of

an

area

near

Wageningen

N e t h e r l a n d s ) i s g i v e n i n f i g . 6.4.

Fig. 6 . 4

IRLS image of a n area n e a r Wageningen (The N e t h e r l a n d s ) .

(The

The image r e v e a l s i t s s c a n n i n g n a t u r e i n showing l i n e s which a r e d e r i v e d from t h e image o u t p u t of a c a t h o d e r a y t u b e . Note a l s o t h e d i s t o r t i o n s a t t h e e d g e s of t h e image. A Landsat-image

of

t h e Konya Basin i n Turkey i s p r e s e n t e d i n Fig.

6.5.

S e v e r a l l a k e s a r e o u t s t a n d i n g i n t h e image a s w e l l a s a mountaneous a r e a . A t this

small s c a l e t h e scanning l i n e s a r e c l o s e

t o each

o t h e r and t h e image

r e s e m b l e s v e r y much a normal photograph, h u t upon enlargement t h e l i n e s w i l l a p p e a r more and more.

Fig.

6.5

Landsat-image of band 5 ( r e d ) approx. 1 :1.700 .000.

of

t h e Konya Basin i n Turkey:

scale

Another t y p e of imagery may be c o n s t r u c t e d by u s i n g symbols f o r i n t e n s i t y

classes or other combination of digital data. An example is given in fig. 6.6. The use of different densities in the symbols may give an impression of tone, but the main criterion for discrimination is the symbol itself.

Fig. 6.6 6.5

Symbols as an aid for image production.

Image-enhancement Image enhancement concerns the modification of an image to improve its

quality

as

pefceived

by

a viewer.

The

criterion is subjective and

the

enhancement is judged by the observer. Image restoration concerns improvement of image quality and is based on an

152 objective criterion which is mathematically defined. Image

enhancement

is

also

described under section 5.2.

performed

in

the

interactive processing

Digital as well as optical and photographic

methods may be used. Digital methods for image enhancement are described by H a l l ( 1 9 7 9 ) .

One

of the methods is the alteration of grey level values. The transformation may be linear, logarithmic or exponential. The logarithmic transformation enhances the low contrast detail, because logarithms provide much detail at low digital difference. There are also electro-optical, and photographic optical methods for image-enhancement. Film-density contouring may be performed by electro-optical density analyzers. In density

slicing each

density measurement

is portrayed

separately.

To

achieve density slicing, it is necessary to control the electronic equipment in such way that all signals lower than at a selected level will be rejected and the remainder will be printed (Boynton and Moxham, 1969). Fig. 6.7

shows

density slicing performed on an airphoto of the Calatayud area (Spain).

Fig. 6.7Density slicing on an image of the Calatayud area, Prov. Zaragoza (Spain) : (a) scene after slight modifications; (b) density slicing; the light grey levels are portrayed in black.

153 Electronic printing equipment may be used to enhance contrast in low contrast parts of the image. Photographic techniques for density slicing (Ranz und Schneider 1970; Daels en Antrop, 1970) are the Agfacontouring and the Kodak-Path6 Masking. By copying the original image on Agfacontour film, the resulting image shows only a certain density interval transparent, the other density levels are imaged dark (black).

The transparent density interval is determined by filtering and

exposure time. Colour codes can be used for each density interval and the resultant images can he combined. The Masking method of Kodak-Path6 uses copies on hard photographic material. Contrast-rich copies that depress intermediate grey tones are produced. By varying the exposure time, it is possible to cover the whole grey scale. Such a copy with a specific exposure time is called a mask. By copying this mask, an antimask is the result (together they form a homogeneous black image). Combination of a mask of a first tone level with an antimask of a second tone level produces an image with a transparent equal density interval etc. In this connection also

the

diazo process

offers possibilities. By

varying

the

exposure time, it is possible to produce a limited range of products that represent different tone or intensity levels of the original image. Additive

colour

viewers

may

be

used

for

projecting

transparent

photographic materials, each illuminated with different coloured light (blue, green and

red)

and arranged

in accurate position by

correction of

the

projections. The brightness and saturation of colour (and thus the tone levels) can be controlled. Images of different bands or dates may be combined and the combination may be enhanced to the judgement of the interpreter. 6.6.

Conclusions Images (aerial photographs and imagery derived from digital processing)

have certain aspects jointly, which are: resolution, scale, tone, contrast, pattern, texture, mottling and shadow. While photographic imagery consists of very fine irregular grains, the scanner produces so-called pixels arranged in regular lines or columns. Geometric distortions are inherent to large scan angles as used in airborne scanning. However, Landsat imagery is relatively free of geometric distortion due to the narrow scan angle used in acquisition. Thermal imagery in airborne scanning may present specific distortions due to effects of surface winds.

154 Image restoration is based on an objective criterion. Image enhancement, however, is subjective and intends modification of an image to improve its quality as perceived by an observer. Image enhancement may be performed by digital

electro-optical

and

optical

processing

as well

as

photographic

processing. 6.7.

References

Bennema, J. and Gelens, H.F., 1969. Aerial Photo-Interpretation for Soil Surveys. Lecture Notes ITC: 87 pp. Boynton, G.R. and Moxham, R.M., 1969. A Rapid Film-Density Analyzer. U.S. Geol. Survey. Prof. Paper 650-C: pp. 123-126. Buringh, P., 1960. The Application of Aerial Photography in Soil Surveys. Manual of Photographic Interpretation, Amer. SOC. of Photogrammetry: pp. 63 1-666.

Daels, L. en Antrop, M., 1973. Afstandswaarneming. Dee1 11: Interpretatiemogelijkheden. De Aardrijkskunde, Nr. 99-1973/ Nr. 4: pp. 337-353. Hall, E.L., 1979. Computer Image Processing and Recognition. Academic Press, New York, London: 584 pp. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. Ranz, E. und Schneider, S., 1970. Der Aquidensiteitenfilm Agfacontour als Hilfsmittel bei der Photointerpretation. Bildmessung und Luftbildwesen, 38 Jg: pp. 3-14. Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. 11, Interpretation and Applications. Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 869-2144. Sabins, F.F. Jr., 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Francisco: 426 pp. 6.8.

Additional reading

1976. Introduction to Environmental Remote Barret, E.C. and Curtis, L.F., Sensing. London, Chapman and Hall: 336 pp. Carman, P.D. and Brown, H., 1970. Resolution of Four Films in a Survey Camera. The Canadian Surveyor, Vol. 24, No 5: pp. 550-560.

155 7.AERIAL PHOTOGRAPHY

After Louis Daguerre announced his direct photographic process in 1839, it took only 10 years for the first experiment on aerial photography from kites and balloons to start. It is reported that topographic mapping using aerial photography was introduced for the first time in North America in 1886. The first successful1 flights with an airplane by the Wright Brothers in 1902 led in 1913 to the use of airplanes for obtaining airphotos (source: Wolf, 1974).

After that time enormous progress has been made both in instruments and

techniques.

In most soil Surveys, airphotos are used as a basic material. It is therefore of importance to have some knowledge on technical aspects. A number of technical aspects are discussed in par. 7.1. These are general aspects such as: vertical and oblique aerial photography, the structure of a frame aerial mapping camera, the arrangement of a block of airphotos, drift, crab and tilt, the shadow characteristics in the terrain and their projection on airphotos.

Stereoscopic devices, relief displacement and

parallax are

treated separately in par. 7.2. The subsequent sections contain the following subjects: aerial mapping cameras (par. 7.3),

photomosaics and othophotographs (par. 7.4),

requirements

for aerial survey (par. 7.5). Finally, some technical aspects of true colour aerial photography (par. 7.6),

Infrared aerial photography (par 7.7),

multispectral aerial photography

(par. 7.8) and Ultraviolet aerial photography (par. 7.9) are dealt with. For films, filters and photographic processing, the reader is referred to chapters 4 and 5, while image characteristics such as photo-scale, are dealt with in chapter 6.

One should be aware that the presented text gives only a

short impression of the science called photogrammetry; the references and additional reading include some textbooks on this subject. 7.1.General aspects Aerial photography can either be classified as vertical or oblique. Vertical aerial photographs are taken with a camera of

which the axis is

directed as nearly Vertical as possible. Oblique aerial photographs are taken with the camera axis inclined from the vertical. High obliques include the horizon, low obliques do not. Although obliques Offer a wide overview, they

156 are in general less suitable for a systematic survey since:

-

scale is only constant in lines parallel to the horizon; atmospheric haze causes low contrast in the background (see fig. 7.1); in hilly terrain, slopes facing away from the camera appear in a reduced

size.

Fig. 7.1

High oblique airphoto of Paramaribo (Suriname) with low contrast background (Note side friducial marks on the photograph). Courtesy: CBL Suriname.

I will restrict to the most commonly used vertical aerial photographs, which will be referred to as airphotos.

157 In practice, it is difficult to keep the camera axis perfectly vertical in aerial photography. It concerns only small deviations of the vertical position known as tilt (see fig. 7.5)

usually amounting to less than 1" and seldom more

than 3 " . Tilt is especially difficult to avoid in (large sca1e)'photography at a low altitude (lower than 1500 m) of hilly terrain or of areas in hot climates with irrigular thermal pattern. Under such conditions turbulent air causes sudden movements of the airplane. Displacement in vertical position will lead to differences in photoscale. In terrain with great height differences, the distance of the camera to the ground surface (flying height) is strongly variable and therefore also the resulting photoscale. The cameras used in aerial photography have a special construction. See the cross-section of a frame aerial mapping camera given in fig. 7.2.

Fig. 7.2

Generalized cross-section of a frame aerial mapping camera after Wolf ( 1 9 7 4 ) .

158 The main parts of a frame aerial mapping camera are: the camera-magazine, the camera-body and the lens-cone assembly. The camera-magazine contains the reels which hold exposed and unexposed film

and

also

the. film advancing

and

film

flattening mechanism.

Film

flattening is generally achieved by applying air pressure into the air-tight camera cone. The camera body usually houses the drive mechanism for advancing and flattening the film as well as for the operation of the shutter. The

lens-cone assembly

contains

lenses,

filter, shutter and

diaphragm.

Compound lenses bring the light rays into focus in the focal plane. The so-called

nodal points lie on the optical axis; they have the

property that any light ray directed toward the incident (or front) nodal point passes through the emergent (or rear) nodal point and emerges at the other side of the lens in a direction parallel to that of the incident ray (Wolf, 1974). The principal point, or centre, of a photograph can be defined as the point in the focal plane where a line from the rear nodal point, which is perpendicular to the focal plane, intersects. The vertical airphotos are taken along a series of lines, the flight strips. Each successive photograph along a flight strip overlaps part of the previous photograph; the overlap normally amounts to a figure between 5 5 and 65

percent.

A pair

of successive photos

is calles a stereopair, since

stereoscopic viewing is possible. Information on arrangement of airphotos is summarized in fig 7.3. flight line

is

photographs:

PI,

the

line

P2,

P3

connecting the principal etc.

Adjacent

flight

points

strips

of

show

The

successive a

lateral

overlapping, a so-called side lap which is normally held between 10 and 30 percent. The photographs of two or more adjacent flight strips are referred to as a block of airphotos. The photobase is equal to the distance between principal points of successive photographs in a flight line (see fig. photobase with the denominator of scale

1 2 ( D = - = ;; S

7.3).

Multiplying the

see section 6.1) gives

the air base, which is the actual distance between two exposure stations. The number of airphotos (N) covering a surface area ( A in n 2) can be calculated according to:

159

for Se see fig. 7 . 3 ; using these data A

N =

0.40 x 0.85 x 1

2

x D2

where Se (=gxhxD2 in m2), endlap =

1-i or 0,85 x 1) and 1

=

= 60%

(g

=

1-e or 0,40 x l), sidelap

=

15% (h

strip width. Generally one multiplies N with a

factor 1.2 in order to correct for deficits in coverage due to deviations in the lines of flight.

run 1

-

~-~ _ _ _ _ - -

direction of flight run 2

- - - - - -7 - - -

flight - line - 1

' c-

flight line 2

flight 1 ine 3 -

-

Fig. 7 . 3

The arrangement in a block of airphotos (straight course). P

principal point, intersection of diagonals (d) and lines joining opposite fiducial side marks (see fig. 7.1); d diagonal of airphoto (cm) which may be related to the angular field of view ( a ) and to c = focal distance of the lens system (cm) according d = 2 c tg + a ; 1 strip width (cm) = 4 d n ; ij distance between flight lines (cm); e overlap in cm (in % e/l x 100); i sidelap (cm) (in % i/l x 100); b distance between principal points of successive photographs or photobase (cm) = 1-e; g forward gain per photo (cm) = 1-e; n lateral gain per photo (cm) = 1-i; e' gain in surface areau (cm2) per photo = b x ij = h x g. The aircraft has to be kept at a constant altitude in a straight line

on

correct course. However, the aircraft may be blown off course by wind across

160 f l i g h t ( d r i f t ) or can be p o i n t e d a t a n a n g l e from t h e l i n e of

t h e l i n e of

f l i g h t ( c r a b ) a s is i l l u s t r a t e d i n f i g .

7.4.

R o l l i n v o l v e s a r o t a t i o n of t h e

a i r c r a f t a b o u t t h e l i n e of f l i g h t . I f photographs are t a k e n when t h e sun i s n e a r t o t h e h o r i z o n , much d e t a i l i s obscured i n l o n g dense shadows.

Conversely when t h e sun i s overhead,

its

r e f l e c t i o n may o b s c u r e t h e d e t a i l of a p o r t i o n of t h e photograph. North

of

23"27'

N

latitude,

the sun's

r a y s around noon are i n c l i n e d

toward t h e e a r t h from t h e s o u t h , s o u t h of 2 3 " 2 7 ' from t h e n o r t h .

l a t i t u d e s near

Between these

S l a t i t u d e they a r e i n c l i n e d

the equator,

the sun's

rays

around noon a r e d i r e c t e d n e a r l y v e r t i c a l toward t h e e a r t h ' s s u r f a c e .

s t r a i g h t course

crab Fig. 7.4

F l i g h t coverage showing s t r a i g h t c o u r s e , d r i f t and c r a b .

A t any p l a c e on t h e e a r t h ' s

surface,

the sun's

p r i o r t o noon and from t h e w e s t a f t e r t h a t

time.

r a y s are from t h e east

Thus i t is p o s s i b l e t o

p r e d i c t t h e shadow p a t t e r n when t i m e and p l a c e are s p e c i f i e d . I f t h e a n g l e w i t h t h e v e r t i c a l ( z e n i t h ) of t h e sun's r a y s is s m a l l e r t h a n

fa

( f a n g u l a r f i e l d of view) of t h e camera, t h e image of t h e s u n may be s e e n

161 on the photograph, the so-called solar reflection point. This situation occurs

throughout the year around noon in tropical areas and during summer in temperate regions also around noon, especially with cameras having a large angular field of view. However, the solar reflection point can be detected in the scene only if highly reflecting surfaces are present. The point just opposite the solar reflection point does not show shadow, since no rays behind that area can reach the camera (see fig. 7.5: opposite S, the solar reflection point).

point T

The sun and the aircraft are exactly

in line at this point. Therefore at low-altitude flights, the shadow of the aircraft may be registered at this place. The point is known as the no-shadow point or hot spot. Fig. 7.5 shows the shadow characteristics of the terrain. Note the effect of slope in shortening the shadow when projected on a slope facing toward the T \

,, ,,, , , ,’ N

\ \\

Ill

I I

p h o t o negative

/

perspective center

\

Fig. 7.5

//

/

I

Ill

\\

\\

Tilt and shadow characteristics on an airphoto P = principal point S = solar reflection point N = Nadir T = no-shadow point or hot spot

incident radiation and the reverse effect if slope is facing away from the incident radiation. The shadows are projected as lines in the one-dimensional presentation of the photo-negative in fig. 7 . 5 . The so-called Nadir-point (N), that is the point on the photograph where a vertical line (from the reference plane) through the perspective centre ( 0 ) of the cameralens pierces the plane of the photograph, is exactly halfway between the solar reflection point (S) and the no-shadow point (T).

The

distance and direction of N from the principal point may be used as a measure for the amount and direction of tilt. Below we consider the aspects of photographic printing materials. Positive prints can be made transparent or printed on paper. Diapositives made on glass show the least dimensional change and sharpest detail. A l s o positive transparencies on film base are superior to paper prints. However, for use in the field, paper prints are preferred, since they have advantages with regard to handling, writing and drawing when compared with the other materials. Furthermore, expenses for replacements are relatively low. The weight and surface of paper prints vary. One can distinguish:

-

single weight and double weight, glossy, semi-matte and matte paper prints.

Double weight paper is stiffer, more durable and less subject to dimensional change caused by varying humudity and temperature than single weight paper. Glossy prints are the sharpest type but reflect glare and may crack under intense use. A compromise between sharpness and durability in the field forms the semi-matte double weight paper. The format of airphotos is usually 23 x 2 3 cm; earlier, 18 x 18 cm was used. However, other formats, like the 6 x 6 cm, acquired by specific cameras, may be found as well. 7 . 2 . Stereoscopy

In section 4.1

the cues to depth for human vision have been discussed.

Fusion of double images enables depth perception. The aerial camera produces two images of the same scene (stereopairs) by successive exposure in the flight line. Optical devices are used for viewing stereopairs: lens (or pocket) stereoscopes, mirror stereoscopes (see fig. 7 . 6 ) and stereoscopic glasses.

163

Fig.

7.6

Stereoscopes ( a ) Zeiss pocket s t e r e o s c o p e ( b ) C a s e l l a pocket s t e r e o s c o p e ( c ) Topcon m i r r o r s t e r e o s c o p e ( d ) Wild m i r r o r s t e r e o s c o p e ( e ) Old D e l f t s c a n n i n g s t e r e o s c o p e

The most s i m p l e s t e r e o s c o p i c d e v i c e s a r e probably s t e r e o s c o p i c g l a s s e s . T h e i r l i m i t e d use w i l l be due t o t h e d i f f i c u l t y f o r t h e o b s e r v e r t o m a i n t a i n t h e d i s t a n c e between eyes and o b j e c t a p p r o x i m a t e l y e q u a l t o t h e f o c a l d h t a n c e of t h e l e n s e s .

I n t h e l e n s s t e r e o s c o p e s ( f i g . 7 . 6 a and b ) , a magnifying l e n s i s p l a c e d i n f r o n t of each e y e , and t h e photographs a r e viewed a t a d i s t a n c e e q u a l t o , o r s l i g h t l y less ( e . g .

8.9 cm) t h a n t h e f o c a l l e n g t h of t h e l e n s (e.g.

11.4

cm). The r e s u l t i s t h a t t h e o b j e c t s a r e a t o r n e a r o p t i c a l i n f i n i t y from t h e

164 eyes and the line of sight of the eyes will be parallel or nearly parallel. Lens stereocopes are inexpensive and easy manageable. A disadvantage is that the entire overlap of standard airphotos cannot be viewed at one time. The lens steroscope presented in fig. 7.6 a, differs from that in fig. 7.6 b, in not having an adjustable eye base. In mirror stereoscopes, the lines of sight of the eyes are separated by means of reflecting surfaces, two for each eye (fig. 7.6

c/e).

The entire

stereoscopic overlap of standard airphotos can be viewed at one time. To obtain

magnification, binocular viewers

(Topcon

3x

or

6x)

or

built-in

magnifiers (Topcon 1,8x) can be used. The Old Delft scanning stereoscope (fig. 7.6e) enables to move the field of view either horizontally or vertically by knobs which operate rotating mirrors and prisms in the instrument. Two magnifications 1.5

and 4.5

are

available and one views from an oblique angle. Through application of two Old Delft scanning stereoscopes placed across from one another, it is possible to view the same photographs with two persons simultaneously. The first step in the orientation of photographs is to nark the principal points and locate the principal points on adjoining photographs, the so-called conjugate principal points.

The line joining the principal and conjugate

principal points is the flight-line. The flight-line should be parallel to the instrument base and the line connecting the eyes of the observer. Furthermore, the photographs should always be oriented in such a way that the shadows fall as nearly as possible to the observer. Since the overlap area should be in the center, it will be apparent which is the right-hand print and which is the left. After adjustment of the interocular distance (e.g. 64 mm), the two photographs are located apart, parallel to the flight-line to the correct position for the possible stereoscopic vision. Relief displacement is the displacement in photographic position of an object due to its elevation above, or its depth below a reference level. The displacement is outward from the photocenter for points above the reference plane and inward for points below the reference plane. Near the nadir there is less displacement. The concept of relief displacement is illustrated in fig. 7.7. The projection through an optical center, the so-called perspective projection, involves a number of phenomena. When an object is in nadir, it is projected orthogonal (e.g. in photo 1). Out of n a d i r ( a s in photo 2 for AR) it

165

A r = N 1 A2 I

I

I

I

I

G1 F1 A1=B1

I ,

CID E ' \ \ \ N,

I ,

B ' N1 A '

/I

#

r = N 1 N2

t

ne g a t i v e

Fig. 7 . 7 Relief displacement

is projected as a line. Point A above the reference plane is projected as outward from N l t l and B below the reference plane is projected as B2' inward from N l l ' reference

(see also the projection of CDE). plane,

it

would

be

projected

If A was located higher above the more

outward

displacement Ar (in mm) can be calculated (see Fig.'7.7),

etc.

The

relief

since:

Another aspect connected with perspective projection is that of slope direction; slopes that are facing toward the optical center are imaged larger than slopes facing away from the optical center (compare B,'F,' with F,IG,I). Parallax is the displacement in the position of an object caused by a shift in the position of image acquisition. The change in position of a point

166 from one airphoto. to the next airphoto in a flight-line is called the stereoscopic parallax. Every point on successive airphotos has an absolute stereoscopic parallax (see fig. 7.8).

Fig. 7.8 Parallax and parallax-difference Absolute stereoscopic parallax of A and B (in nun): P = X -(-X )andP=X - X A A1 A2 B1 B2 Parallax difference (in nun) AP

AB

=

P A

- PR

= A A

1 2

-

B B 1 2

From the parallax difference between two points ( AP

in nun, fig. 7.8),

as measured on a stereopair in proper position, the height difference (h in m) between the points can be calculated as follows: h

=-

AP b+AP

where b

=

.'

(7-3)

photobase o r distance between principal points or two successive

photographs in

mm

and Z

=

flying-height in m.

The measurements are done with a so-called parallax bar. The stereoscopic effect may be roughly expressed by the base/height ratio. If in normal viewing the base is 6.4 cm (eye base),

the ratio amounts

to 0.2 at a distance of 30 cm and to 0.00064 at 100 m distance.

In aerial photography the base is the air base (photobase b, multiplied

167 by denominator of scale D). ( a = 90°,

f

=

152 mn,

For an air base of 2300 m and a height of 3800 m

format 23 x 23 cm, scale 1 : 2 5 . 0 0 0 ) ,

the base height

ratio (B/Z) is equal to 0.6; there is vertical exaggeration, when compared to normal vision.

In stereoscopic viewing of a stereopair of airphotos, the

vertical exaggeration can be calculated by multiplying the base/height ratio with Q/E where Q

=

distance from the eyes to the stereomodel in cm, and E

base in cm. An average value for Q

= 43.2

=

eye

cm and Q/E is approximately 6.8.

In stereoscopic viewing an approximation of the vertical exaggeration (V)

therefore can be given by the following expression: V = 7.3.

B

-Z x

6.8

(7-4)

Aerial mapping cameras The most common aerial mapping camera is the single lens frame camera,

OK

frame aerial mapping camera. The single lens frame cameras are normally classified according to their angular field of view into:

-

normal angle, up to 7 5 " , often 60" e.g. Wild RC8 Aviotar and Topar (Zeiss, W. Germany) ;

-

wide angle, 7 5 " - l o o " , often 90'

e.g. Wild RC8 Aviogon and Geocon IV (Bajer,

U. S .A.) ;

-

super-wide angle, greater than I O O ' ,

often 120" e.g. Wild RC9 Super Aviogon

and Russar (Russipov, U.S.S.R.). The focal length (c in cm), the angular field of view ( a ) and the photoformat (d

=

diagonal length in cm) are related according to (see fig. 7 . 9 ) :

tg fa

fd

= -OK

a

= 2

-

arctg fd

(7-5)

The focal length is related to the flying altitude (Z) as SScale = c/Z; (6-1). The relation between angular field of view ( a ), focal length (c) and flying altitude (2)

is illustrated in fig.

7.9.

A smaller angular field of view

involves a longer focal length and higher flying altitude to obtain the same photo-scale. The vertical exaggeration (V) can be expressed in b and c, using equations 6-1 and 7-4.

Since B

=

hxD (where B

=

air base, b

=

photobase and D

=

denominator

168

lc

4

A

Fig. 7.9

Relation between angular field of view ( a ), focal length (c) and flying altitude ( 2 ) .

of scale) and Z = cxD (for S =

61

=

2c

) the equation 7-4

can be written as

follows :

V

b =

-

x 6.8

(7-6)

In table 7.1 the vertical exaggeration for different camera types is given. Table 7.1

Vertical exaggeration for different camera types and b (photoformat 23 x 23 cm and 60% overlap)

Camera type

a

c (mm)

V

normal angle wide angle super wide angle

60"

90"

300 152 88

2.0 4.0 7.1

120"

=

92 mm

In table 7.2 the height difference h is given for parallax differences A p of respectively 0.02 mm, 2 mm and 5 mm (photoformat 23 x 23 cm, overlap 60%). Apparent i s the influence of the angular field a on the height difference at specified Ap

.

Besides these cameras, so-called narrow angle cameras may be used for large-scale photography to reach permissible flying heights.

169 Table 7.2.The h e i g h t d i f f e r e n c e s f o r d i f f e r e n t s c a l e s and camera t y p e s f o r photoformat 23 x 23 c m , o v e r l a p 60% and p a r a l l a x d i f f e r e n c e s of 0.02 mm, 2 mm and 5 nun. camera t y p e

a

c Z (mm) (m)

60" 305

normal a n g l e

90'

152

s u p e r wide a n g l e 120'

88

wide a n g l e

h at

S

Ap=

3050 15250 1520 7600 880 4400

1:lO.OOO i:5n.nno 1:10.000 1:50.000 1:lO.OOO 1:50.000

0.6 3.3 0.3 1.6 0.2 1.0

in

m

m m

m m

h at Ap=2mm

h at

63 318 32 158 18 92

150 748 75 373 43 216

A~=5mm

m m m m m

m

m

m m m m m

Super-wide a n g l e cameras may be a p p l i e d f o r s p e c i a l purpose f l i g h t s below c l o u d cover. nearly

A

series

complete

of

cameras

is

provided

by

Zeiss

(for

the

s t a n d a r d n e g a t i v e s i z e of 23 x 23 cm), a l s o i n c l u d i n g a s o - c a l l e d i n t e r m e d i a t e a n g l e camera ( t a b l e 7.3).

Z e i s s a e r i a l s u r v e y cameras.

Table 7.3.

c i n nun

angular f i e l d a

Type

Lens

Narrow a n g l e camera Normal a n g l e camera Intermediate angle camera Wide a n g l e camera Super-wide a n g l e

Telikon A Topar A Toparon A

610 30 5 210

30" 56" 75"

Pleogon A S-Pleogon A

153 85

93' 125"

Knowledge of f i l m speed is e s s e n t i a l f o r d e t e r m i n i n g t h e p r o p e r exposure times

during

the

flight,

but

also other

factors

are i m p o r t a n t .

For

this

r e a s o n , Kodak developed a n Aerial Exposure Computer e n a b l i n g t h e e s t i m a t i o n of l e n s opening and s h u t t e r speed i n r e l a t i o n t o f i l m speed, d a t a , t i m e of day, a l t i t u d e of f l i g h t , l a t i t u d e and haze c o n d i t i o n (Smith, 1968). The speed of

non-aerial

f i l m s is measured

Norm) o r ASA (American S t a n d a r d A s s o c i a t i o n ) e.g.

i n DIN (Deutsche I n d u s t r i e ASA = 200 means: a n exposure

t i m e of 1/200 sec a t a p e r t u r e f / 1 6 (Wolf, 1974). However,

f o r panchromatic

speed (AFS)

AFS =

Eo

aerial films,

is u s e d , which is e q u a l t o :

usually t h e so-called

aerial f i l m

170 where Eo is the exposure (in m cd s-l) at the point on the characteristic curve (see fig. 5.1)

where the density is 0.3

above Dmin under specified

processing conditions (Lillesand and Kiefer, 1979). Total exposure of photographic film is the product of illuminance and time of exposure. Illuminance is regulated by variations in the diameter of the diaphragm (d= opening of the lens or aperture) and may be expressed by the f-stop according: f-stop

=

(7-7)

d

The lens types of table 7.3

each have their f-stop setting at specified

film speed and image distortion characteristics. Other single-lens frame cameras may be used such as the small-sized Hasselblad with a photoformat of 6 x 6 cm. These cameras may be applied with focal lengths of 45 and 49 nun (wide angular field), field).

or 70 m (narrow angular

The 70 mm type permits photography from small planes at low altitudes.

When compared with wide and super-wide angle aerial mapping cameras, which are normally used at l o w altitudes, they may have a relatively narrow angular field and in consequence only slight edge distortion.

In addition to the single-lens frame cameras which are normally used, there are a number of other camera types. Some of these are discussed below. Multilens cameras have two or more lenses and expose two

OK

more pictures

simultaneously. The so-called trimetrogon camera has a three camera system. Two cameras expose high oblique photos, while a third camera simultaneously takes a vertical photo. Covergent cameras consist of two single lens cameras mounted together, one pointing forward and the other pointing backward in the flight line. In this way two low oblique photos with great overlap can be taken of ground

scenery.

Multilens

and

multicamera

systems may

be

applied

for

multispectral photography through the use of different filters and with respect to the latter also by using different film types. The so-called strip cameras expose a continuous photograph of a strip of terrain below the path of the aircraft. This is accomplished by passing the film over a narrow slit opening in the focal plane at a rate just equal to the speed of passage of ground images across the focal plane (Wolf, 1974). Panoramic cameras take pictures of strips of terrain transverse to the

171 direction of flight. The camera scans laterally from one side of the flight path

to

the other.

The

lateral scan may

be as great as

180"

enabling

photography from horizon to horizon. The scanning also makes it possible to obtain

a

stereoscopic overlap

area.

photography are indicated in fig. 7.10.

The

features

inherent

to

panoramic

The distortions are connected with the

large scan angles and the velocities of scanning and the aeroplane itself.

terra

image (c)

t

f l i g h t path f l i g h t path

/I /

scan no 1

stereoscopic overlap area

Fig. 7.10

Schematic representation of panoramic photography. (a) field of view in flight path (b) lateral scan (c) panoramic distortion and scan distortion (d) stereoscopic overlap two scans

172 7.4.

Photomosaics, orthophotographs and stereotriplets Aerial

photomosaics

are

assemblages

of

overlapping

airphotos.

Most

commonly, they are constructed from vertical airphotos by cutting and matching the individual parts of the photographs. Aerial photomosaics may be: controlled, semi-controlled or uncontrolled. A controlled mosaic is prepared from photographs which have been rectified for effects of tilt and flying-height variations, and brought to uniform scale by using control points. An uncontrolled mosaic is prepared by simply matching the adjacent photos; n o rectification or control points are used. Semi-controlled mosaics are prepared by using control points but without rectification or otherwise, and without a complete control. Furthermore, we know index mosaics or photo indexes, and strip mosaics for engineering projects e.g.

in road and railroad construction. Controlled mosaics

are valuable in soil survey projects in that they provide a broad view of the landscape and enable an accurate plotting of survey and sample points. Othophotographs are made by removing the effects of tilt and local relief (height or depth below a reference level)

as well as many of the lens

aberrations from standard perspective airphotos. The process of preparation of orthophotographs is usually referred to as differential rectification. ,For stereoscopic interpretation of orthophotographs a special photographic image has to be used, a so-called stereomate. The stereomate is a differentially rectified photograph,

on

which image shifts have been introduced in the x-

direction proportional to the elevation differences in the terrain and parallel to the base of the original stereoscopic model. For more information on orthophotography, the reader is referred to Slama (ed., 1980). Stereotriplets are produced by cutting successive airphotos of a strip and arranging the pieces in such a way that the central area can be viewed stereoscopically. This is shown in fig. 7.11.

The part at the right on photo 1

and the part at the left on photo 3 , both containing P2', together with the central part of photo 2 are used for the production of a stereotriplet. For use with a pocket stereoscope, the three parts can be fixed, so that the distance of equivalent points on successive imagery amounts to 6.4 cm.

173

photo 1

photo 2

photo 3

n

n

n

n

I

I

1

I

- -flight

Fig. 7.11

line

Production of stereotriplets. n = normal to flight-line from centre P, P2', P1', P2 etc.

7.5.

Requirements for aerial survey The data which have to be recorded on each photograph are:

-

the photonumber and line of flight; fiducial marks; acquisition data and time of day; flying altitude;

- focal length

OK

scale;

-

position related to horizontal (water-level mark).

-

the organization which carried out the aerial survey;

Other indications may be: grey scale for control on development. The decision to fly OK not to fly must be made daily. A n ideal day for

aerial photography is one free of clouds and atmospheric haze. A day with less than 10 percent cloud-cover, however, may be found satisfactory. Other factors that have

to

be

considered are:

smog, dust, smoke, high winds and air

turbulence (Wolf, 1974). The season determines the vegetation cover of the ground and the sun's altitude. For topographic mapping and soil mapping in the temperate zone, the photographs should preferably be taken when deciduous trees are bare.

For

vegetation studies and forestry on the other hand, it is desirable to take photographs when the deciduous trees are in full leaf and show much contrast, e.g.

during spring or autumn. For

detection of

differences in soil moisture

content

in semi-arid

regions, the period directly after the rainy season may be chosen for the aerial survey.

174 The sun's

altitude in connection with shadow is an other important

factor. Normally about 30" sun angle is considered the minimum acceptable in aerial photography. For the temperate zone this means that the airphotos should be taken in summer, around noon (10.00 a.m.

-

Howgver, in aequatorial zones the high sun's

14.00

p.m.).

altitude around noon is

normally avoided and airphotos are taken between R.00 a.m. between 14.00 p.m.

and 10.00 a.m.

OK

and 16.00 p.m.

In selecting the direction of flight-lines, one has to evaluate the following:

-

the physiography of the terrain; generally the flight-lines are chosen perpendicular to the main physiographic boundaries but great differences in topography are avoided;

-

the position of the sun; generally the flight-lines are roughly in eastwest

direction

in

temperate

zones

and

in

north-south

direction

in

equatorial areas to obtain shadows perpendicular to the flight lines (if time of day of aerial survey is such as indicated above). Of course, it may be necessary to find a compromise between physiography and shadow-effect in the selection of flight-lines. The scale of aerial photography depends of the purpose of the study and the geographic dimensions of the landscape units. The dimensions of the basic mapping unit have to be specified beforehand. Examples of purpose of study and usual airphoto scales are given below: Livestock, crop-disease

1 : 2,000 and larger scales

Tree crowns, vegetation damage in forests

1: 5,000 to 1:3,000

Dynamical phenomena of erosion processes

1: 5,000

Farm crop fields, urban details

1:10,000

Topographical mapping

1:33,000,

and larger scales 1:25,000

and

1 :17,000

Reconnaissance survey

1 :80,000

Photographic imagery may be enlarged as much as 4 or 5 times the origial format t o a scale suitable for the purpose of study. 7 . 6 . True colour aerial photography

True colour-films may be distinguished in:

175

-

direct colour positive films or reversal films

-

colour negative films. Colour negative films offer advantages over reversal films in having a

greater exposure latitude and more control in obtaining the desired colour balance during printing. In addition, a number of second-generation products can be easily obtained (Myers, 1 9 6 8 ) . Colour-films have a slightly lower resolution than black-and-white films. The reversal film, however, has a relatively high resolving power, since there is no necessity to produce any prints, which would cause a loss of resolution; laboratory work and expenses are greatly reduced (Vijlger, 1 9 5 7 ) and the film is therefore more regularly applied in aerial survey. The resolving power of multi-layer colour-film is not uniform for the three basic colours. AGFA established the following values for their CN 17 film in the laboratory (VSlger, 1 9 5 7 ) :

-

top layer (blue-sensitive)

-

centre layer (green-sensitive)

70 lines/mm

-

bottom layer (red-sensitive)

50 lines/mm

100 lines/mm

A number of colour-films for aerial survey are on the market.

In the U.S.A.:

Eastman Kodak Company with the reversal Ektachrome Aerofilm,

the negative Ektachrome Aerofilm 8442 and the AeKOCOlOUK Film 2445 (Estar base); General Analine and Film Corporation with positive Anscochrome film.

In Germany: Agfacolour negative film. In the U.S.S.R.:

the three layer colour film, TsN-1.

The external parameters that are of much importance in colour photography are: the sun's

angle, the time of day, the atmospheric condition, the flying

altitude and the angular field of view of the camera. The reflected light on its way from target to sensor is changed in composition, due to adsorption by atmospheric constituents and addition of diffuse light. On clear days, the latter has a higher content of blue as compared to direct sunlight. Consequently, in oblique photography the horizon appears bluish (Rayleigh scattering). longer

wavelengths

is

scattered

and

Under haze conditions also light of the

horizon

becomes

whitish

(Mie

scattering). Therefore, the edges of aerial COlOUK photographs generally show a loss in colour fidelity as compared to the central part of the photograph. Since

an

increasing flying-altitude

normally

results in a

greater

176 contamination of blue light, the best quality of aerial colour photography is reached at relatively low flying-altitudes. Meier ( 1 9 6 7 ) reports about colour photography of good quality of an area in Germany from a height of 2000 m, and of poor quality from a height of 4000 m. Furthermore, a small angular field of view will minimize the edge effect. Filters are used for acquisition of good imagery, e.g. filters

for uniform

radiation with

exposure

of

the

image-plane

wavelengths smaller than 380

and

antivignetting

filters excluding

nm, 400 nm or 420 nm

for

compensation of light, medium and heavy haze respectively (Smith ed., 1 9 6 8 ) . 7.7.

Infrared aerial photography The two common Infrared sensitive films are the black-and-white Infrared

film and the three-layer colour Infrared or false colour-film (see section 4.2).

A l s o the Russian spectrazonal film (SN-2M) must be mentioned. The latter

is a two-layer film. the layers being sensitive for green-yellow-orange, and for near Infrared radiation. Outstanding advantages of the near Infrared sensitive films are the additional information obtainable from the near Infrared and the relatively high haze penetrating capability. Under thin fog conditions, IR photography penetrates

slightly

further

than

normal

photography.

Under

dense

fog

conditions there is no benefit. Storage

of

the

films

requires

care:

they

have

to

be

stored at

temperatures of -23°C to -18°C. Several Infrared sensitive films are on the market. In the U.S.A., produces the Ektachrome

Infrared Aerofilm

type

8443

and

Infrared film 2443 (Estar base) and 3443 (Estar Thin Base).

bdak

the Aerochrome In the U.S.S.R.,

also black-and-white Infrared film is available besides the spectrazonal film. Since near Infrared rays ( 7 0 0 - 9 0 0 nm) are less refracted than Visible rays, the focusing of near Infrared rays has to be corrected. For black-andwhite Infrared photography this is relatively simple, but for the three-layer false colour photography, special glasses, o r Crystalline calciumfluoride and sometimes

plastic

material,

are

used

for

focus

correction

at

three

wavelengths. Such lens-systems are called apochromatic lenses (Gibson, 1 9 7 8 ) . Pease ( 1 9 7 0 ) has paid attention to processing of False COlOUK reversal film.

By a simple modification of processing, negative material can be

produced. subtle

The paper prints derived from this negative material show more

differentiation

than

prints

that

have

been

made

from

positive

177 transparencies (for routine processing, the reader is referred to the sections 4.2, 5.1 and to Smith, 1968). Another modification in processing may be used to improve the haze penetrating capability. Atmospheric haze results in a scattering of green and red, and consequently produces a blue-green veil on the false colour film. By the so-called EA-4 processing the cyan layer sensitivity can be increased in order to

obtain a near neutral balance.

High altitude Colour

Infrared

photography is improved in this way, and at the same time objects with a low near Infrared reflectance, such as most rocks and soils, can be discriminated better. 7.8.

Multispectral aerial photography The disadvantage of direct true colour aerial photography according to

Yost and Wenderoth (1967) are:

-

fixed spectral sensivity;

-

fixed relative exposure for each dye layer;

-

inadequate exposure range;

-

complexity of processing as compared with processing of black and white photography,

-

lack of true colour fidelity and inability to produce significant colour differences

between

objects

which

have

slight

spectral

reflectance

differences. Research has been done to evaluate the possibilities of multispectral photography in obtaining true colours of terrain features and in enhancement of

the imaging of objects, which have only

slight spectral reflectance

differences. The following requirements for multispectral photography can be indicated (Yost and Wenderoth, 1967) :

-

the spectral bands should be correctly chosen after measurement of the spectral distribution of the illumination and the spectral reflectance of the targets;

-

the camera system has

-

the photographic processing has to be controlled.

to

be spectrophotometrically calibrated;

By controlled exposure in each spectral band, the multispectral camera can

compensate

for

the

dynamic

variables:

illumination and

atmospheric

178 condition.

Furthermore,

by

controlled

processing

and

additive

COlOUK

projection, it is possible to obtain true colours of ground objects or to show slight spectral differences between objects. Stellingwerf (1968) and other authors report about the advantages of the relatively small 70 nun cameras (e.g.

Hasselblad).

Four of these 70 mm cameras

can be mounted, to one frame aerial mapping camera. The recording of the four images may be done on one piece of film

OK

on separate films. When recorded on

one piece of film, it is possible to study the images on the 1-011 with a pocket stereoscope. However, controlled processing of negatives for each spectral band is only possible when recorded on separate films. 7.9.

Ultraviolet aerial photography The incoming radiation at wavelengths shorter than 0.28 m is strongly

absorbed by ozone and molecular oxygen in the atmosphere, thus limiting the part of

the ultraviolet region that is of

practical interest to remote

sensing. Some quartz glasses, quartz crystal, the salts lithium fluoride and barium fluoride, are transparant for wavelengths as short as 0.12 lnn but for wavelengths larger than 0.28 um conventional lenses are quite satisfactory (Cronin et.al.,

1973).

If extremes of altitude and unfavourable atmospheric

conditions are avoided, Ultraviolet aerial photographs can be taken, although image contrast will be low due to strong scattering of UV by atmospheric particles. The Kodak P l u s - X Aerographic film 2402 in combination with the IJratten 18A filter may be used for this purpose.

7.10.

Conclusions One of the technical aspects in aerial photography is the position of the

camera axis enabling a first classification of airphotos in oblique and vertical photos. The latter have a more uniform photo-scale and are normally used in soil surveys. Deviations of the vertical (tilt) are avoided as much as possible in taking vertical airphotos. The photographs are taken in flight-lines and overlapping position in forward as well as in sideward direction. Deviations from the flight line direction are a.0. crab and drift..

If the angle of the sun's rays with the vertical is smaller than 4 of the angular field of view of the camera, a no-shadow point

OK

hot spot can be

179 indicated as well as a solar reflection point, the latter if strongly reflecting surfaces are present. Concerning the type of paper prints: a double weight semi-matte paper print is selected for heavy field use of airphotos, which is usual in soil survey. Photomosaics are very useful in soil survey projects. The requirements of aerial survey have to be formulated in the light of soil survey and other applications as well as the technical aspects involved. Some technical aspects of modern aerial photography are: resolution power of multi-layer colour film, the influence of atmospheric condition and flying altitude on colour rendition. Infrared aerial photography has a better penetrating capability when compared with

colour aerial photography.

Modification in

processing

of

Infrared false colour photographs may improve the haze penetrating capablility and the discrimination between objects with low near Infrared reflectance. Multispectral photography may be applied to obtain true colours of terrain features and to produce significant colour differences between objects with slight spectral reflectance differences. Controlled processing is one of the requirements. Ultraviolet photographs may be obtained from a low altitude at favourable atmospheric conditions with Kodak Plus-X Aerographic film 2402. 7.11.

References

1962. Interpretation of Aerial Photographs. Burgess Publ. Cy, Avery, T.E., Mineapolis: 192 pp. Cronin, J.F., ROoney, T.P. et al., 1973. Ultraviolet Radiation and the Terrestrial Surface. In the Surveillant Science ed. by Holz, R.K., Houghton Mifflin Cy, Boston: pp. 67-77. Gibson, H.L., 1978. Photography by Infrared. Its Principles and Applications. John Wiley & Sons, New York: 545 pp. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. Meier, H . K . , 1967. Farbtreue Luftbilder? Herbert Wichman Verlag, Karlsruhe, Bildmessung und Lufbildwesen, Heft 5/67: pp. 206-214. Myers, V.I. and Allen, W.A., 1968. Electro-optical Remote Sensing Methods as Nondestructive Testing and Measuring Techniques in Agriculture. Applied Optics Vol. 7, NO 9: pp. 1819-1838. Pease, R.W., 1970. More Information Relating to the High-Altitude Use of Color Infrared Film. Amer. Elsevier Publ. Cy, Remote Sensing of Environment Vol. 1, nr 2: pp. 123-125. Pease, R.W., 1970. Color Infrared Film as a Negative Material. her. Elsevier Publ. Cy, Remote Sensing of Environment, Vol. 1, nr 2: pp. 195-198. Slama, C.C. (ed), 1980. Manual of Photogrammetry; 4th edition. Amer. SOC. of Photogrammetry, Falls Church, Virginia: 1056 pp.

180 Thompson, M.M. (ed), 1966. Manual of Photogrammetry; 3rd edition. Amer. SOC. of Photogrammetry. Vol I and 11. George Banta Co, Menasha, Wisconsin: 1199 pp. Vijlger, K. 1957. Neue Versuche mit farbigen Luftaufnahmen. Herbert Wichman Verlag GmbH, Berlin, Bildmessung und Luftbildwesen, Heft 4: pp. 112116. 1974. 562 pp.

Wolf, P.R.

Eleme,nts of Photogrammetry, McGraw-Hill Book Cy, New York:

1967. Multispectral Color Aerial Photography. Yost, P.R. and Wenderoth, S., Photogrammetric Engineering, Sept. 1967: pp. 1020-1033. 7.12.

Additional reading

Albertz, J. and Krieling, W., 1972. Photogrammatric Guide. Herbert Wichman Verlag, Karlsruhe: 214 pp. Aldrich, R.C. Heller, R.C., 1969. Large-scale Color Photography Reflects Changes in a Forest Community During a Spruce Budworm Epidemic. Remote Sensing in Ecology. Univ. of Georgia Press, Athens: pp. 30-45. Breuck. W. de en Daels, L., 1967. Luchtfoto's en hun Toepassingen. Wetenschappelijke Uitgeverij. E. Story-Scientia, P.V.B.A. Gent: 176 pp. Corten, F.L., 1966. Physik des Luftbildes in "richtigen" und "falschen" Farben. Bildmessung und Luftbildwesen Bul. 4/1966: pp. 191-201. Fritz, N.L., 1967. Optimum Methods for Using Infrared Sensitive Color Films. Photogrammetric Engineering 33: pp. 1128-1138. Howard, J.A. 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Interdepartmental Committee on Air Surveys, 1970. Specifications for Air Survey Photography. National Research Council of Canada: 32 pp. Schuurmans, U.D., 1979. Infraroodfotografie. Focus-10: pp. 50-53. Smith, J.T. (ed), 1968. Manual of Color Aerial Photography. Amer. SOC. of Photogrammetry, Falls Church, Virginia: 550 pp. Spurr, S.H., 1960. Photogrammetry and Photo-interpretation. The Ronald Press Cy, New York: 472 pp. Stellingwerf, D.A., 1968. The usefulness of Kodak Ektachrome Infrared Aero Film for Forestry Purposes. 11th Congr. of the Int. SOC. for Photogrammetry, Lausanne 1968: 6 pp. Trorey, L.G., 1950. Handbook of Aerial Mapping and Photogrammetry. Cambridge, University Press: 178 pp. White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press, Oxford: 104 pp. Williams, J.C.C., 1969. Simple Photogrammetry. Academic Press, London and New York: 211 pp.

181

8. GENERAL DIRECTIONS FOR PHYSIOGRAPHIC INTERPRETATION OF REMOTE SENSING IMAGERY IN SOIL MAPPING.

Soils are defined as three-dimensional natural bodies with a unique morphology. They can be studied in the field by auger, trenches and profile pits. The field survey may be done according to the fixed grid method, the sample line and, strip methods or the spot and sample area methods. The fixed grid method is used in detailed

OK

semi-detailed surveys. Especially small scale surveys

require interpolation and even extrapolation, thus making the use of remote sensing tools inevitable. Present remote sensing techniques normally operate from the Visible up to

In case of bare surfaces reflectance data offer

the Microwave zone (radar).

direct information about the soil surface. Where surfaces are covered by natural vegetation

OK

crops, texture, pattern and tone of vegetation together

with slope and site are the main sources of information. The basic requirement for image-interpretation in Soil mapping therefore, is to indicate a number of different aspects which individually, or in combination with other aspects have a correlation with soil conditions. The areas thus indicated are supposed to show uniformity in their soil distribution pattern and are delineated on the images in order To

a

interpreted

to

show the geographical extension of soil bodies (polypedons).

certain from

extent, thermal

information on and

long

wave

subsurface radar

data.

conditions

can

Furthermore,

be the

morphographic position or site may offer strong indications about subsurface conditions. However, all these deductions mainly have a function in the planning of the field survey. In other words, the assumptions have to be verified. Below, interpretation is discussed with emphasis on methods offering information about superficial aspects only, and providing steroscopy. A

number of authors present the outcome of their work on airphoto-interpre-

tation.

In a general way the methods described by these authors are also

applicable to the interpretation of other remote sensing imagery. For details on airphoto-interpretation see a.0.

and Bennema and Gelens (1969).

Buringh ( 1960), Vink ( 1964),

Goosen (1967)

The different remote sensing techniques used in

identifying terrain features are treated in chapters 9 through 13.

182 8.1.

Methods of image-interpretation Image-interpretation may

be

done

for many

purposes

each

with

its

specified interest in the objects or the features on the imagery. The kind of objects or features on which a particular analysis is based, is called an aspect. The aspects of interest for soil survey can he divided (Bennema and Gelens, 1969) into:

-

basic aspects individually visible on the images, e.g.

slope and relief (if

stereoscopic observation can be applied), natural vegetation, crops, soil and rock surface (grey or colour tones);

-

compound aspects visible on the images through a combination of two or more of the basic aspects e.g.

land types, drainage ways and pattern, faults and

joints,

-

inferred aspects not directly visible on the images hut deduced from basic and/or compound aspects e.g.

soil depth, parent material, drainage and

erosion condition. Bennema and Gelens (1969) indicate three relationships between the aspects of image-interpretation and soil conditions:

-

the aspect has a direct relation to soil, e.g.

the colour or grey tone of

the topsoil, and the drainage condition;

-

the aspect indicates certain conditions of soil formation; changes in the aspect mean changing conditions of soil formation and most likely different soils, e.g.

differences in slope and relief, or in parent material;

- the aspect shows consequences of soil differences, e.g.

differences in

natural vegetation and in a number of cases, in land use. The methods of image-interpretation for soil science are:

-

the aspect analysis or element analysis acc. Buringh (1960);

- the physiographic analysis or physiognomic analysis acc.

(Bennema and

Gelens, 1969) ;

-

the morphogenetic analysis.

The aspect analysis is based on a systematic analysis of individual aspects in the image. For each aspect, an interpretation map is produced. Finally, the aspect interpretation maps are superposed on each other. As a first approximation to validity of the boundaries f o r soil survey, the boundaries due to repetition of two or more aspect boundaries are given more value than the

183 boundaries due to single aspects. However, although accurate, the pure form of the

aspect

analysis

is

time-consuming,

and

the more

experienced photo-

interpreter will directly use certain combinations of aspects for delineation of mapping units. He will choose those aspects which he supposes to have a close relation to soil conditions. Physiographic or physiognomic analysis (Bennema and Gelens, 1969)

restricts

itself to the external features as shown in the stereo-image. The same elements of the aspect analysis are used but in a different way. Those areas which have uniformity in appearance are delineated and characterized by the same symbol on the

images.

When

the

physiognomy

changes, a

different

unit

has

to

be

delineated. The physiographic analysis includes the analysis of basic and compound aspects, such as relief, slope as well as vegetation and land use, and aspects important for the description of the drainage system. A morphographic analysis resticts itself to those aspects of the physiography that can be used to describe the morphography of the land, namely: relief, slope, valley forms and drainage patterddensity. The morphogenetic analysis comprises the delineation of units not only on the basis of their appearance, but also on the basis of the processes which have shaped these units. Most important for the morphogenetic analysis is of course the geomorphology of the area, but also hydrology and other factors may play their parts. Specific knowledge is required of the morphogenetic processes and it is not likely that this analysis is the first step in the interpretation of airphotos of an unknown area. However, in image analysis some geomorphological terms may be applied with great certainty, such as: river levees, river basins, point bars, beach ridges. combination of

It will be understandable, that in practice a

the physiographic

and

morphogenetic analysis is generally

applied. Table 8.1 phases

in

summarizes the methods of image-interpretation. The different

interpretation

are

indicated,

being:

identification, combination, classification and derived

from

transformed

by

the

aspect analysis and

combination and

detection,

deduction.

recognition,

The information

the physiographic analysis can be

deduction

into morphogenetic

information,

revealing the cause of the soil conditions. Fig. 8.1 shows the different steps which may be taken in interpretation if there are no limitations in identification. (Limitations may exist due to lack of stereoscopv for relief and slope analysis).

The flow chart is

184 Table 8.1. Methods of image-interpretation. Phases in interpretation Detection

Recognition cation

Aspects ofinterpretat ion

Identification and Classification

basic aspects

Methods of analysis

Combination and Classification

Soil Deduction and formatClassifi- ion

compound aspects

inferred aspects symptoms and effects

aspect analysis physiographic analysis transformation + morphogenetic analysis

constructed in such a way

cause

that the landscape performance on the images

determines the steps to be taken. The occurrence of landtypes and drainage ways are considered basic for this purpose.

If drainage ways are present, the

drainage density, which may be influenced strongly by scale, offers a further key to interpretation procedures. The analysis of basic and other compound aspects forms the next phase in interpretation. Deduction is necessary for the analysis of

geological structures and inferred

aspects,

as well as for

morphogenetic processes. Some landscapes require a specific approach e . g .

parts of river basins with

very low drainage density (continue with analysis of natural vegetation etc.), dune areas without drainage ways (analyse relief and/or slope, and continue with analysis of natural vegetation and land u s e ) . For literature

on

terrain analysis, the reader is referred to Zuidam et al.

( 1978-1979).

After the image-interpretation, field observations are made to identify soils and to check the boundaries between the mapping units. Generally, a second and more final interpretation is made on the basis of the newly acquired knowledge from the field. The image-interpretation may also be done simultaneously with the fieldwork. At present, various remote sensing techniques are at our disposal. Of these techniques aerial photography is the most common tool in soil survey since it offers steroscopy that enables accurate-relief

and slope analysis.

Other remote sensing techniques, such as multispectral scanning may be used

185 Figure 8.1 Flow chart for image interpretation Two

One landtype"

OK

more landtypes*

t

delineation of permanent water courses and intermittent water courses I/

7 low to moderate high to very

very low drainage

drainage density

I

high drainage density

delineation of dry valleys

I

asseLsment of drainage pattern

t

assesment of slope and site

Lt

assessment of natural vegetation, land use, animal constructions, soil surface and rock outcrops

t

Deduction on geological structures, kind of parent material and inferred aspects such as soil depth, drainage and erosion conditions.

*

Designation in morphographic morphogenetic terms.

and

physiographic

but

preferably

for relatively high-standard identification of objects. However, except for

SPOT imagery, they do not offer a complete stereoscopic view and their main key to relief is shadow. In radar imagery, shadows together with high lights offer information about height,

slope and

orientation.

However, steroscopic observation is only

possible by viewing overlapping images. To obtain these for scanning or radar devices, a two-flight coverage is required which involves relatively high expenses. Therefore, the new remote sensing techniques are generally not used in stead of, but in conjunction with aerial photography.

Of the numerous aspects that can be studied in image-interpretation, only a selection of aspects which are most relevant for soil survey are discussed below. The obvious first step in image-interpretation is the delineation of units that internally have a great number of aspects in common, but externally deviate strongly from their surroundings. These units are called "landtypes".

8.2. Landtypes A landtype can be seen as an aspect of a very compound nature. The

criteria used for discrimination of landtypes depend

on

the variety in the

area under consideration. Relief, drainage pattern, natural vegetation, and sometimes land use may be criteria for the recognition of landtypes. The terms used for description of landtypes are a reproduction of the physiography or morphogenesis of the land and depend on the scale of the imagery as well as on the interpreter's reference level with regard to the landscape genesis, or in other words, the processes that shaped the units. In small and medium-scale surveys, often physiographic terms are applied. Pure physiographic terms may be based on relief features, drainage pattern and topography. The last aspect may

comprise indications such as mountains, hills (isolated, dissected,

elongated and rounded), plateaus, table mountains, plains, etc. The terms may have a genetic meaning in the sense of

-

relative position e.g.

interior or coastal lowland and upland;

geomorphological history e.g.

denudational plains, old and young coastal

plains; high, medium and low marine terraces or river terraces;

-

tectonical history

e.g.

land

with

folds, faults or

numerous

joints;

structural basins;

-

petrological composition (often deduced from drainage pattern and shape or pattern of hills) e.g.

volcano land, "kopjesland" (outcropping hard rock);

granite, schist or karst land, the last referring to chemical solution of gypsum or limestone;

-

depositional history and setting e.g.

alluvial plain or more specifically

fluvial, coastal or glacial plains; delta, lagoon, dune and beach ridge or rivervalley land;

-

human activity e.g.

-

repeated sequences of soils

nature reserve land; (recent or old)

arable land,

grazing or forested land; terraced or polder land; e.g.

land characterized in terms of steepest

slope (relief class) and dominant slope (example: steeply dissected, dominantly moderately steep).

187 Marshland is an example of a landscape in which the relative topographical position, the natural vegetation or land use and the drainage condition are expressed jointly. Further subdivision of land types depends on the scale of survey and may be done into land-units and/or analogous to the Australian system into land components. The Australian system shows the following mapping units (Gibbons and Downes, 1964):

-

Land-component, smallest mapping unit; climate, parent material, topography, soil and vegetation are uniform within

the

limits significant for a

particular form of land use;

-

Land-unit, basic sequence of land-components; Land-system, grouping of land units, which have in common, landforms, or structural forms of vegetation, or some other significant land characteristics;

- Land-zone, or an area in which a number of similar land-systems are present; the boundaries between land-zones will always coincide with significant differences in one or more major environmental features. Comparison shows that the landtypes mentioned above will often be in mediumscale surveys at the level of land-unit or landsystem in the Australian system.

On the level of land-unit, the above given summation of terms for landtype description also contains indications of landforms. Since it is a free system, this is allowed and, as has been said, the terms that will be applied depend on scale and reference level.

When the landform can be inferred and if it is large enough to be delineated,

landform

terms

are

generally

preferred

above

physiographic

indications at high levels in the legends of interpretation maps. This is mainly due to the high information potential of landforms for soil conditions. Then physiography may be used for the description of landforms on a lower level. At large- and medium- scale surveys, the landforms generally become more

important besides

the physiographic and broad morphogenetic terms.

Examples are given below:

-

Old

denudational forms, besides

mountains:

inselbergs, raiias

river- and marine

(Pliocene

alluvial fan

terraces and table remnants),

glacis

(Pleistocene) etc.;

-

Recent denudational forms: badlands, gullied land, land eroded by sheet- and

188 rill-erosion etc.;

-

Fluvial forms: levees, basins, flood plains (relatively high and low in case of occasional floods, summer and winter in case of

seasonal floods),

alluvial fans etc.;

-

Colluvial forms: colluvial footslopes etc.; Coastal forms: beach ridges, swamps, mud flats etc.; Aeolic forms: barchan dunes, longitudinal dunes, loess mantles etc.; Glacial forms: gletschers, moraines, ice-pushed ridges etc.; Karstic forms: gypsum or limestone karst, dolines, collapse sink etc.; Volcanic forms: dikes, volcano slopes and craters; lava flows, lahars, ash OK

-

lapilli mantles etc.;

Diapyric forms: salt d8mes etc.; Forms derived from tectonical action: anticlinal and synclinal structures, fault structures expressed in the landscape (cliffs).

For more information on landforms, the reader is referred to textbooks on geomorphology, such as Strahler (1969) and Cooke and Doornkamp ( 1 9 7 4 ) .

An

example of an area with different landtypes is given below (see fig. 8.2). The landtypes have the following characteristics: A. Elongated Hills: moderate drainage density; steeply dissected land with rolling footslopes. B.

Steeply dis-

high drainage density;

sected land

steeply dissected land with rolling footslopes.

C. "Kopjes" Land:

very low drainage density; hilly and steeply dissected land.

D. Plain:

moderate drainage density; undulating.

Further subdivision in land units and components may be done on the basis of drainage pattern, on the presence of rock outcrops or natural vegetation, including type, tone and surface density.

8.3. Relief, slope and site Relief and slope are discussed together, since relief can be considered as a complex (or a pattern) of slopes. The FAO-classes of relief are based on the occurrence of steepest slopes. The following classes are distinguished:

Fig. 8.2 Landtypes North-eastern part of Serengeti National Park (Tanzania). Date of flight aerial photograph : Jan. 1972 Landtypes: A. Elongated Hills C. Kopjes Land B. Steeply dissected Land D. (Undulating) Plain

190 relief classes

steepest slopes

<

flat and almost flat

between 8 and 16%

rolling hilly

range in elevation

steeply dissected

moderate

<

between 16 and 30%

> >

300 m*)

mountainous: great range in elevation ( > 300 m*)

*

2%

between 2 and 8%

undulating

30% 30%

note of the author

The range in elevation

(OK

local relief) of mountainous terrain has to be more

than 300 m. A further subdivison of mountainous terrain may be made into:

-

low mountainous terrain, local relief between 300 m and 1000 m;

- high mountainous terrain, local relief 1000 m

OK

more.

Local relief can be defined as the maximum difference in elevation within a mapping unit (e.g.

land type).

Relief features are highly visible in the airphotos and show a strong relation to soil conditions. Soil bodies are likely to

OCCUK

in repetitive sequences in

areas with a particular relief. Depending on the scale of the imagery and the characteristics of the area under consideration, it might be necessary to combine two relief classes in order to characterize a mapping unit. The relief units may be distinguished in more detail by the following properties: local relief or maximum height difference, steepness of dominant slopes and dominant orientation of slopes. Slope has a particular meaning for soil conditions, since it is:

-

a soil forming factor; the configuration of the surface; an expression of geogenesis; related to drainage conditon; an important element of land evaluation.

191 The FAO-classes of slope are: % -

class 1

flat or almost flat

0- 2

2

gently sloping

2- 6

3

sloping

4

moderately steep

13-25

5

steep

25-55

6

very steep

6-13

>

55

Other aspects of slope are:

-

shape

-

concave,

-

complex slopes;

single slopes

-

convex,

straight.

- changes of slope, abrupt (angular breaks) or gradual (smooth);

-

size, e.g.

long even slopes and short ones;

position in relation to direct solar radiation, dominant wind direction, or stratification of rocks. Mapping of the configuration of the surface or morphological mapping may

be done by the analysis of stereo-imagery (e.g. airphotos) and fieldwork. As a basis of this mapping, Cooke and Doornkamp ( 1 9 7 4 ) present the recognition of the following features:

-

breaks of slope; gradual changes of slope; angle (' or %) and shape of slope units.

Cliffs (40'

or 84% or more) are indicated separately from the other slope

units. Symbols, as well as an example are given in fig. 8.3. Site is concerned with the relative position of the mapping units. Through deduction on degree of slope, shape and arrangement of the mapping units, it is possible to indicate: plateaus, summits, tops, shoulders, slopes, footslopes, valley bottoms and other depressions. Landtypes, generally, are characterized by typical toposequences. The delineation of these site-units might be of major importance in mapping of soils due to differences in soil formation (age and process), etc.

soil texture, drainage condition, erodibility

192

slopes Angular convex break Angular concave break Smoothly concex change Smoothly concave change Angle of slope

(O)

II__

C l i f f s (bedrock, 3 40')

AAUUUU

Breaks of slope

-

Changes o f slope Convex slope u n i t Concave slope u n i t and concave * Convex too c l o s e together t o allow the use of separate symbols

Fig. 8 . 3 Symbols for morphological mapping after Cooke and Doornkamp (1974)

8.4.

Natural drainage patterns Streams and drainage patterns are visible through a number of basic

aspects which may be relief, slope, water, soil surface and/or vegetation (Bennema and Gelens, 1969). Rivers

OK

streams may be destructive

OK

constructive. respectively erosive Or

depositional. The latter may be accompanied by depositonal terraces, levees, back swamps and (lower) floodplains. Delineation of chese units is important for soil mapping, owing to the related differences in soil texture and soil development. The main types of rivers are:

-

wilded

OK

braided rivers with an irregular regime;

meandering rivers with a regular regime, their course being

193

-

well-developed, interrupted due to barriers related to geological structures (e.g. dykes and faults).

Various types of stream forms are given in fig. 8.4.

I meandering

lmeandering w i t h r a p i d s

I

Yazoo

Fig. 8.4 Stream forms and associated patterns. A so-called anastomotic drainage pattern develops when the river regime

has meandering as well as braided characteristics. Normally the river-channel i s capable of carrying its water and bedload, but sudden changes may alter the

streamcourse to a more braided pattern. Consequently, this type shows large floodplains with a network of diverging and joining channels with many oxbow lakes and cut-off channels of varying width. The deranged or disordered stream pattern is an immature type. The very irregular stream valleys are usually wide and many lakes and/or marshes can be found along the stream-courses. Another pattern is formed when the natural levees are high. The streams in the back swamps are forced to flow parallel with the main stream until a break in the levees is reached: the so-called Yazoo type. Near to the ocean coasts or near to borders of interior lakes or seas, the type of shoreline strongly influences the drainage pattern. Strahler (1969) gives five classes of shorelines:

194 1) shorelines of submergence, caused by a sinking down of the earth's crust or by the Holocene world-wide rise of sea-level (e.g.

ria shoreline) and

characterized by a highly irregular and inherited drainage pattern; 2) shorelines of emergence, caused by a rising of the earth's crust or fall in

water-level of interior seas; the waterline takes a position against what was

formerly a

slope of

the seafloor; most

seafloors have

received

stratified deposits derived from erosion of the land and distributed by currents; the new drainage pattern develops on a relatively smooth, gently sloping sediment surface; 3) neutral shorelines, being built out into the water by deposition of new

materials, e.g.

alluvial fans and

delta shorelines; also coral reef

shorelines belong to this group; 4 ) fault shorelines, produced by faulting of the earth's crust in such a way

that there is a dropping, down at the seaward side and a consequent rising, up at the landward side; usually, the formation of cliffs is the result;

5) compound shorelines are those that show forms of at least two of the previous classes. Some examples of drainage patterns at neutral shorelines are given in fig.

8.5.

Figure 8.5 Some drainage patterns at neutral shorelines and alluvial fans. The dichotomic pattern Is a distributary pattern, which occurs in

195 alluvial fans and deltas. The distributary streams are branching. The arcuate delta is the most common delta-type. Others are: the bird's foot and estuarine delta. The colinear pattern is found in areas with sand ridges. Stream courses and flowing surface waters may appear and disappear in the marshy interridge areas. The elongated bay type is found in deltas and coastal plains. The form shows a row of troughs, often lying along old beaches. The interlocking or reticular drainage pattern consists of small "snake-like" distributary streams, which usually drain into large channels. They are found along sea-coasts in tidal marshes. The direction of flow is reversed when the tide changes. The thermokarst stream patterns sometimes assume the shape of huge mudcrack patterns.

The

term thermokarst is used

to describe the thaw sinks and

associated features which dot arctic coastal plains. The drainage patterns of inland areas are often dense and complicated,

making it u s e f u l to apply additional systems for systematic analysis. Strahler

(1969) has presented a system to analyse the composition of the branching systems of

channels, treating

them as lines

on

a plain.

All fingertip

tributaries are designated as segments of the first order, two first-order segments produce a channel of the second order. At the joint of two secondorder segments arises a third order, etc. analysis of drainage patterns makes

(see

fig. 8 . 6 ) . This method for the

it possible to designate particular

patterns for groups of stream orders (the pattern of lower orders often differs from that of higher orders) and also makes a quantification of the drainage network possible. Another aspect of drainage pattern is surface density, which refers to the number and relative spacing of drainage courses per unit area in a drainage basin. In considering the density, it is usual to take into account all the drainage courses, even the dry valleys. It is possible to indicate the density of a drainage pattern by a numerical value. This value is calculated by measuring the total length of drainage courses per unit area and dividing the total length of the courses by the surface area of that unit (km/kmL). One may use a relative surface density: cm/cm2 at a particular scale. Five classes of surface density are suggested for this purpose:

196

basin

F i r s t order Second o r d e r Third order Fourth order

Larger stream o f higher order

Fig. 8.6 Stream orders after Strahler (1969) surface density class

length of drainage COUKSeS in cm per cm2

>

very high high moderate low very low

3.0

2.0 0.5

<

4.5 4.5

-

3.0 2.0 0.5

The various classes are demonstrated in fig. 8.7.

This figure may be used for

visual estimation of the relative density classes at a particular scale. The

drainage

patterns

of

the

inland

associated patterns, can be divided into:

- multi-basinal and radial patterns;

areas, excluding

stream

forms and

197

Very h i g h

Low

u

Moderate

Very low

High

Figure 8.7.

-

Relative surface density classes of drainage ways.

freely developed patterns; structurally controlled patterns.

Examples are given in fig. 8.8. The term multi-basinal pattern is used for areas in which a number of not well coordinated depressions are found. They may develop under fully different conditions. The shallow-hole pattern, which is accompanied by

dolines (solution)

and

collapse sink or sinkholes, is most common in limestone areas. The streams in those areas flow partly underground. The kettle-hole

pattern consists of

randomly

spaced depressions with

an

occasionally water-filled basin. The individual tributary systems may have a dendritic pattern. They occur in areas with a topography derived from glacial action. Radial patterns can be subdivided into centrifugal and centripetal patterns. In the first case the stream branches run away from the centre, in the latter the stream branches flow towards the centre (see fig. 8.8).

In the freely developed patterns the influence of geological structure is weak or negligible.

In this concept, areas with strong chemical solution

(shallow-hole pattern) and glacial areas with many depressions (kettle-hole pattern) as well as radial patterns (e.g. volcanoes) are excluded in preventing

198

M U L T I B A S I N A L AND R A D I A L PATTERNS

STRUCTURALLY CONTROLED JATTERNS

I

swallow-hole

kettle-hole

radial: centrifugal

radial : centripetal

.annular

FREELY DEVELOPED PATTERNS

angulate

dendri t i c

%

m

subdendri t i c

@

para1 1 e l

subpara1 l e l

rectangular

contorted

Fig. 8.8 Multibasinal, freely developed and structurally controlled drainage patterns.

199 a f r e e d e v e l o p i n g of d r a i n a g e ways upon e r o s i o n a l a c t i o n . The d e n d r i t i c t y p e 1s c h a r a c t e r i z e d by i r r e g u l a r b r a n c h i n g of join

the

next

subdendritic

higher

order

is

type

a

streams

tibutaries.

at

modification

Streams of a lower o r d e r

approximately t h e

which

may

be

same a n g l e .

slightly

The

StKUCtUKally

c o n t r o l l e d ( f i g . 8.8). The p i n n a t e p a t t e r n h a s a f e a t h e r l i k e appearance. The f i r s t a n d / o r second o r d e r s t r e a m s a r e o f t e n s h o r t and more o r less p a r a l l e l . The s t r e a m b r a n c h e s mostly j o i n t h e l a r g e r streams a t a n a c u t e a n g l e . The d i c h o t o m i c p a t t e r n , b e i n g c h a r a c t e r i s t i c f o r a l l u v i a l f a n s , a l s o b e l o n g s t o t h e f r e e l y developed p a t t e r n s ( s e e f i g . 8.5).

O t h e r t y p e s a r e t h e p a r a l l e l and

subparallel patterns. Examples of fig.

s t r u c t u r a l l y c o n t r o l l e d drainage p a t t e r n s a r e a l s o given i n

I n t h i s group a r e p l a c e d t o g e t h e r t h e d r a i n a g e p a t t e r n s which a r e

8.8.

s t r o n g l y i n f l u e n c e d by g e o l o g i c a l s t r u c t u r e . t h a t i s , t h e p r e s e n c e of beds w i t h different

resistance,

OK

f a u l t s and

joints

determine

largely

the drainage

pattern. The a n n u l a r p a t t e r n i s a m o d i f i c a t i o n of t h e r a d i a l p a t t e r n . The s t r e a m c o u r s e s a r e a d j u s t e d t o f l o w around domes w i t h r e s i s t a n t c o n c e n t r i c r o c k f o r m a t i o n s .

The t r e l l i s p a t t e r n i s c h a r a c t e r i s t i c of f o l d e d o r d i p p i n g s e d i m e n t a r y r o c k s . The

lowest

order

tributaries

may

join

the

next

higher

order

streams

at

a p p r o x i m a t e l y r i g h t a n g l e s and a r e o f t e n p a r a l l e l . Streams of h i g h e r o r d e r s a r e o f t e n l o n g and s t r a i g h t , and p a r a l l e l t o e a c h o t h e r . The

rectangular

pattern

develops

in

areas

i n which

j o i n t s and

f a u l t s are

p r e s e n t i n t h e bedrock a t r i g h t a n g l e s . The a n g u l a t e form i s a m o d i f i c a t i o n i n which j o i n t s and f a u l t s a r e o r i e n t e d a t o b l i q u e a n g l e s . T r i b u t a r i e s t e n d t o be parallel.

The c o n t o r t e d p a t t e r n i s a l s o s t r u c t u r a l l y c o n t r o l l e d . This form may

i n d i c a t e stream p i r a c y ,

so t h e d i r e c t i o n of

flow may be r e v e r s e d and s h a r p

bends come i n t o being.

I n s t u d y i n g d r a i n a g e systems, a t t e n t i o n s h o u l d be p a i d t o t h e i n d i v i d u a l gullies

OK

importance.

streams.

In p a r t i c u l a r , t h e s h a p e of t h e c r o s s s e c t i o n c a n be of

There are two main t y p e s :

can be d e s c r i b e d , v a l l e y bottom,

U- and V-shaped

valleys.

Other aspects

such a s form and s t e e p n e s s of v a l l e y s l o p e s , width of t h e

symmetry and d e p t h of

the valley.

The g r a d i e n t of

the valley

bottom i s a n o t h e r i m p o r t a n t a s p e c t . The w a t e r regime of stream c o u r s e s c a n b e evaluated

to

a

certain

extent

by

airphoto-interpretation.

Permanent

and

200

intermittent water courses as well as dry valleys are normally indicated (see fig. 8.9).

Criteria used for evaluation of the water rdgime are a.0.:

drainage

pattern, stream order, stream form, valley form and width, and natural vegetation.

Figure 8.9 Example of analysis of drainage patterns. A. Dendritic, first to third order, high density (second order angulate tendency). B. Subparallel, first to fourth order, moderate density. C. Main river, meandering, tributaries fourth order subparallel and low density D. Parallel, third order, very low density. E. Dendritic, first to third order, moderate density (third order parallel tendency) permanent water course intermittent water course _ _ _ _ _ -dry valleys

.

___

8.5.

Natural vegetation Natural vegetation often shows a close relation with relief, drainage

pattern and soil distribution. Therefore, in tropical forest areas and other

201 places where human interference is of minor influence, it is an important aid in soil mapping.

However in many places in these areas, burning, shifting

cultivation and ranging, affect the natural vegetation very much. Then the impact of these activities has to be understood to use this element in deducting soil conditions.

An identification of the type of vegetation cover on imagery may be based on:

-

grey or colour tone (reflection characteristic);

-

texture and/or pattern (see par. 6.3);

-

height and shadows of trees;

-

the site or topographic position.

shape of individual crowns; the distribution or surface density of individual tree or shrub cover types;

In fig. 8.10 a measure for surface density or cover scale (see Braun-Blanquet, .

1932) is given. The following coverage indications are suggested:

0- 5 very low

50- 75 high

5-25 low

75-100 very high

25-50 moderate

-

low

1ow

c-

-50 96

25 %

very--

moderate

75 96

high

__c

+very

high

Fig. 8.10 Examples of coverage percentages.

Some natural vegetation cover types are (see Fig.. 8.11

and Van Gils and

Zonneveld, 1982) :

-

forest (low, medium high, high);

- woodland -

savanna with almost closed canopy;

open woodland savanna (complex cover form);

- shrubland and dwarf-shrubland; - grassland (herb vegetation) with

scattered shrubs (complex cover form);

202

-

grassland (herb vegetation).

The so-called barren land, showing no or a scarce vegetation cover, can be subdivided (after Van Gils and Zonneveld, 1982) into: barren rock, badland, beach, mudflat, icecap and snow.

SHRUB

1 GRASSLAND WITH SCATTERED SHRUBS

Fig. 8.11 Natural vegetation cover types (originally drawn by W.A. Blokhuis).

More detailed analyses can be made if specific knowledge is available about the vegetation of the area under consideraton. Large-scale airphotos are often

203 used in v e g e t a t i o n s t u d i e s and make d e t a i l e d mapping of c o v e r t y p e s p o s s i b l e .

Also t h e t y p e of p h o t o g r a p h i c f i l m i s i m p o r t a n t .

Full c o l o u r photographs, i f

t a k e n under c l e a r weather c o n d i t i o n s , o f f e r good p e r s p e c t i v e s . However, f i l m s s e n s i t i v e t o t h e n e a r I n f r a r e d a r e a l s o promising, s i n c e v e g e t a t i o n c o v e r t y p e s with

different

reflectance.

structures

can

be

The f a l s e c o l o u r - f i l m

discriminated

by

their

near

Infrared

c a n be r e g a r d e d a s s u p e r i o r t o t h e hlack-

and w h i t e - i n f r a r e d f i l m , b u t i s more e x p e n s i v e t h a n t h e l a t t e r .

8.6.

Land u s e , c r o p s and p a r c e l l i n g By t h e t e r m l a n d u s e , w e do n o t mean a n i n d i c a t i o n of t h e t y p e s of c r o p s ,

but

a

general

forestry.

division

In t a b l e 8.2,

into

land

used

for

a.0.

agriculture,

rangeland o r

t h e r u r a l l a n d u s e c l a s s i f i c a t i o n proposed by Van Gils

and Zonneveld (1982) i s given.

The c o i n c i d e n c e of l a n d u s e b o u n d a r i e s w i t h s o i l b o u n d a r i e s is g e n e r a l l y low (Goosen, 1967), l a n d u s e b e i n g a complex f e a t u r e t h a t depends on p h y s i c a l a s w e l l a s on socio-economic f a c t o r s . However, cases

a s an indicator

f o r soil c o n d i t i o n s .

i t may be used i n a number of

Actually,

land use over longer

p e r i o d s may have g r e a t impact on soil: i n a c o n s t r u c t i v e s e n s e (e.g. soils w i t h a Plaggen epipedon) and i n a d e s t r u c t i v e s e n s e (e.g.

man-made

eroded and

t r u n c a t e d soils). I n p r i n c i p a l , c r o p s a r e i d e n t i f i e d on remote s e n s i n g imagery i n t h e same way as n a t u r a l v e g e t a t i o n .

However,

f o r proper i d e n t i f i c a t i o n , a r e l a t i v e l y

h i g h r e f e r e n c e l e v e l i s r e q u i r e d . H e i g h t , s i z e , p a t t e r n and t o n e a r e i m p o r t a n t a i d s f o r t h i s purpose. O t h e r t y p i c a l a s p e c t s of a g r i c u l t u r a l i n t e r p r e t a t i o n of remote s e n s i n g imagery a r e a.0.

t h e e s t i m a t i o n of p r o d u c t i n g a r a b l e a c r e a g e and non-producting a r a b l e

acreage,

and of a r e a s c o n t a i n i n g weeds.

Furthermore,

t h e soil c o n d i t i o n ,

the

r e f l e c t a n c e of c r o p s in s p e c t r a l bands and t h e d e t e c t i o n of c r o p d i s e a s e s may be s u b j e c t s of i n t e r e s t .

P a r c e l l i n g i s c l o s e l y connected w i t h l a n d use. Shape and s i z e of t h e i n d i v i d u a l parcels,

t h e i r arrangement and r e g u l a r i t y r e s u l t in a p a r t i c u l a r p a t t e r n .

h i s t o r y of l a n d u s e may be r e f l e c t e d i n p a r c e l l i n g , e.g. in

the

Netherlands

generally

shows

irregular

old

parcelling

arable and

land

small

The

204

Table 8 . 2 Rural land use classification proposed by Van Gils and Zonneveld (1982) SETTLEMENT AND INFRASTRUCTURE (a) residential (b) industrial, quarrying, mining (c) transport and communications (d) recreational AGRICULTURAL (a) annual herbaceous crops; irrigated or dryland (b) perennial herbaceous crops; e.g. alfalfa, grass mixtures, sugar cane, sisal (c) woody crops; including bananas, rubber; annually harvested for fruits, leaves etc. RANGELAND (a) ranching (b) pastoralism (c) hunting and gathering FORESTRY (a) timber (b) pulp-wood (c) wood; firewood, pitwood or pickets and other domestic uses (d) others; e.g. bark, terpentine, tannin, corck; periodically harvested NATURE RESERVE WATER (a)ishing (b) storage (c) aquaculture (d) other uses OTHER USES Water catchment, restauration of conservation, protection

soil fertility in shifting cultivation,

NOT USED COMPLEX LAND USE: Two or more land use categories on different fields but for cartographical reasons put in a single land mapping unit. MIXED LAND USE: Two or more land use sub-categories are found in the same field; for example intercropping: woody crops (olives) with annual crop (small grains). MULTIPLE LAND USE: Two or more main land use categories simultaneously or periodically same land; for example: dehesa: rangeland/forestry/agriculture shifting cultivation: agriculture/forestry or agriculture/rangeland.

on

the

205

size parcels in contrast with recent polder land, which normally has regular parcelling and large size parcels. The following indications may be used for description: shape e.g. square, rectangular, longitudinal; size e.g.

very small, small, large;

arrangement e.g. parallel, radial, random; regularity e.g.

regular, irregular.

8 . 7 . Drainage condition The drainage condition is an inferred aspect, which may be concluded from

features such as:

-

land use,

e.g.

non-irrigated pastures are usually located on sites with

poorly drained soils;

-

natural vegetation type; presence or absence of water-logged areas; presence or absence of artificial drainage (density and pattern); grey or colour tones of bare soil surfaces, e.g.

poorly drained s o i l s often

show dark tones on the images;

-

site. Drainage condition is a soil property and is therefore strongly related

to the condition of the soil. However, problems are often encountered in the interpretation and it can be stated that the visibility by means of remote sensing is only moderate, unless thermal imagery and multitemporal data are used. The FA0 classes for drainage condition are as follows:

-

very poorly drained; poorly drained; imperfectly drained;

- well -

drained;

somewhat excessively drained; excessively drained.

moderately well drained;

For explanation of the drainage classes, the reader is referred to FAO: Guidelines for soil profile description. In most cases it will only be possible to infer combinations of two classes. Special mention is made of

Infrared photography. Since moist bare soil

strongly absorbs the Infrared radiation, it appears in very dark tones on these airphotos and can be discriminated clearly from dry soil.

206 8.8. Other aspects A number of aspects that are important in interpretation of remote sensing

imagery for soil survey, but are not discussed in the preceding text, are:

-

of the basic aspects of the compound aspects of the inferred aspects

soil surface, rock outcrops and bare rock areas; geological structures,

-

animal constructions;

-

parent material,

- soil depth, - erosion condition. The soil surface may be bare or only partly covered with crops or natural

vegetation. Differences in soil surface in those cases may be visible through differences in grey tone or grey tone pattern e.g.

dark tones may correspond to

moist heavy soils or topsoils rich in organic matter. Gilgai relief in Vertisol bodies shows a pattern of depressions, with dark tones,

and

higher

places,

with

light

tones.

Besides

this,

gilgai

is

characterised by a typical cracking pattern. Ploughing activities on podzols may reveal a typical mottling in areas with bare soil, owing to the differences in colour between the material of the horizons exposed at the soil surface ( A 1 ,

A2, B2h or B2ir and C).

Rock outcrops and bare rock areas are visible on the airphotos by their deviating tone as compared with their environment, and often by their structure (e.g.

the occurrence of layers).

A number of geological structures may be identified, such as:

folds

-

characterized for

example by

rock

layers

sloping in (two) opposite directions; faults

-

shift

of

geological

strata

visible

by

lineaments on the images; joints

-

crack systems often affecting the drainage

pattern; intrusions

-

often hard rocks, offering more resistance to

weathering surroundings;

than

other

rocks

in

their

201

dikes

-

linear intrusions, e.g.

volcanoes and their products

-

dolerite dikes;

volcanoes are characterized by their relatively

high elevation and radial drainage patterns; lava streams can often be characterized by their relative age (due to a.0.

superposition and

weathering condition); efflata may form a mantle over older deposits and can give rise to alluvial fans and lahars. Some animal constructions belong to the basic elements, hut one of the most

important

constructions,

the

termitemound,

is

visible

through

a

combination of surface configuration, natural vegetation or soil surface, and is therefore a compound element. The termite mounds appear as white dots on the image. The large ones may have trees or bushes growing on them, while the rest of the area shows a sparse vegetation. Many

of

the

boundaries

drawn

on

the

interpretation map

are

also

boundaries between different parent materials. They may appear by differences in relief and drainage pattern, breaks of slope, etc. In most instances, fieldwork must decide on the type of parent material, but sometimes it is possible to identify this to a certain extent by image interpretation. The identification may be based on: a. drainage pattern, e.g. swallow-hole patterns in areas with limestone, knob and kettle patterns in areas with glacial deposits, or radial patterns of volcanoes; furthermore structurally controlled drainage patterns may offer strong indications; b. landform, e.g.

table mountains, dunes, alluvial fans, coastal plains and

rivervalleys; C.

site, e.g.

colluvial deposits are most likely at the foot of a slope;

d. soil surface (micro-relief and reflectance), e.g.

gilgai-pattern (micro-

relief) in Vertisol areas, and differences in reflectance, which are due to a different soil moisture condition or a different mineralogical and textural composition; e. observations at steep slopes with rock outcrops, e.g.

stratification.

To a certain extent, a hypothesis on the relative age of

the soil

formation may be built up during the interpretation. Suppose we have a terrain which has a configuration such as indicated in fig 8.11. At A the oldest soils are expected to be present and consequently, soils will show the strongest

208

development at this place. At B, the very steep slope accelerates erosion and soils will be shallow and of a young to moderate age. In the sequence, young

soils in colluvial deposits are expected at C and young soils formed in fluviatile deposits will be present at D.

A

Figure 8.12 Terrain profile ( s e e text for discussion).

As indicated above, conclusions about soil depth may be drawn from the degree of slope, but they may also be based on site (at C and D in fig. 8.12

soils

will nodually be deep) and the occurrence of rock outcrops (except tropical rain forest areas),

a large area of rock outcrops is often indicative .of the

occurrence of shallow soils. Three classes of soil depth can be used, being: a. shallow soils (e.g.

<

30 cm), most common in areas with many rock outcrops

and/or steep to very steep slopes; b. moderately deep s o i l s (e.g.

30-60

cm), most common i n areas with few or no

rock outcrops and moderately steep slopes; C.

deep soils (e.g.

>

60 cm),

most common in alluvial areas and other terrain

with slopes less than 13%. The classification of depths usually depends on the objectives of the soil survey. There is no forced classification. The erosion condition refers to accelerated erosion which may be visible

on the images. The main forms of erosion are: gully erosion, rill erosion and inter-rill or sheet erosion. Only the gully and rill erosion may be visible as such on the image, sheet erosion has to be concluded from differences in grey

or colour tones in relation to soils, land use, site and configuration of the terrain.

209

8.9. Conclusions Since soil has a complex nature, it is not possible to indicate a single phenomenon that causes its formation, the combination of the various aspects of interpretation together with deduction plays an important role in imageinterpretation.

Most

remote

sensing

techniques

are

capable

to

detect

superficial phenomena, and offer a synoptic view of the landscape. However, in the study of soils, which are three-dimensional natural bodies, field work is always a necessary complement. A number of aspects can be distinguished in image-interpretation for soil survey. They can be divided into basic

-,

compound

-

and inferred aspects. Most

aspects have to be regarded as symptoms of a complex cause, the soil formation. However, some aspects may be regarded as results of particular soil conditions. The three basic methods of image-interpretation are the aspect analysis, the morphographic and physiographic analysis, and the morphogenetic analysis. The third method requires not only a morphographic approach, but also knowledge of processes that shaped the different landscape units. We recognize three phases in the interpretation for soil survey, being: 1) analysis of landtypes and drainage ways; 2) analysis of basic and other compound aspects;

3) deduction on geological structures, parent material and inferred aspects

such as soil depth, erosion and drainage condition. The steps that may be applied in interpretation, depend on scale and type of remote sensing imagery. Aerial photography shows advantages above most other remote sensing techniques (except for SPOT stereoscopic imagery) in offering stereoscopy, which enables accurate analysis of

relief and

slope.

Other

remote sensing techniques,

however, may offer good opportunities for optimum identification of specific objects.

8.10.

References

Gelens, 1969. Aerial Photo-Interpretation for Soil Bennema, J. and H.F. Surveys. Lecture Notes ITC, Enschede, The Netherlands: pp. 1-87. Braun-Blanquet, J., 1932. Pflanzensoziologie, Springer, Berlin, Plant Sociology (transl.) by Fuller ti Conard, 1932. McGraw. Hill Book Cy, New YorkLondon. Buringh, P., 1960. The application of Aerial Photography in Soil Surveys. Manual of Photographic Interpretation: pp. 631-666. Cooke, R.U. and J.C. Doornkamp, 1974. Geomorphology in Environmental

210 Management. An Introduction. Clarendon Press. Oxford: pp. 1-413. FAO, Guidelines for Soil Profile Description, MI/70805: pp. 1-53. Gibbons, F.R. and R.G. Domes, 1964. A study of the Land in South-Western Victoria. Soil Conservation Authority. Victoria. Australia: pp. 13-289. Gils, H. van and I.S. Zonneveld, 1982. Vegetation and Rangeland. ITC Textbook, in press (The Netherlands, ITC Enschede). 1967. Aerial Photo-interpretation in Soil Survey. FA0 Soils Goosen, D., Bulletin no. 6: pp. 1-55. Strahler, A.N., 1969. Physical Geography. John Wiley & Sons, Inc.: pp. 1-733. Vink, A.P.A. 1964. Aerial Photographs and the Soil Sciences. Proc. of the Toulouse Conf. on Aerial Surveys and Integrated Studies: pp. 81-141. Zuidam, R.A. van, Zuidam-Cancelado, F.I. van, 1978-1979. Terrain Analysis and Classification using Aerial Photographs. A Geomorphological Approach. I.T.C. Textbook of Photo-Interpretation vol. VII, Chapter 6: 310 pp. 8.11. Additional reading. Barrett, E.C. and L.F. Curtis, 1976. Introduction to environmental remote sensing. Chapman and Hall, London: pp. 1-336. Howard, J.A., 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Lillesand, T.M. and R.W. Kiefer, 1979. Remote sensing and image interpretation. John Wiley & Sons, New York: pp. 1-612. Zonneveld, I.S., 1975. Methodology and Techniques of Survey of Natural and Semi-natural Vegetation using Aerial Photographs and Other Remote Sensing Means. Lecture Notes I.T.C. no 8: 136 pp. Verstappen, H.Th., 1977. Remote Sensing in Geomorphology. Elsevier Scientific Publ. Cy, Amsterdam: 214 pp. White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press. Oxford pp. 1-104.

211 9. INTERPRETATION OF AIRPHOTOS FOR SOIL MAPPING AND LAND EVALUATION

Airphoto-interpretation is the common aid for soil mapping.

In aerial

photography, there is no limitation for scale. Aerial photography not only offers information on relief and slope but also makes a lot of other applications possible.

However, because of changing weather conditions and cloud

cover, the number of flight days is usually limited, and a repetitive coverage throughout the year is generally n o t economic. The spectral resolution is limited to the range between 0.12

pm

and 0.9

pm,

which is Ultraviolet, Visible and Near Infrared. Aerial photography generally operates in the Visible zone, but more and more application is found of Near Infrared sensitive films e.g.

Black- and White-Infrared and False Colour. For

the different aspects on aerial photography and physiographic interpretation, the reader is also referred to the preceding chapters 4 up to and including 8. Plants are strong reflectors of Near Infrared, and different vegetation cover types often show a different reflectance. Good results can be mentioned with regard to the use of false colour-film in agricultural and ecological studies, in differentiating between vegetation cover types, and in locating vegetation areas affected by disease. Due to its successful application, airphoto-interpretation has become a

generally accepted aid for soil survey during the past thirty years.

An

evaluation of various remote sensing techniques in northern Canada, taking into account visual interpretation together with computerized classification of remotely sensed data, revealed that airphoto-interpretation provided the best cost and data-effective method for ecological land classification. Mapping of soils, landforms and landtypes was best accomplished with the aid of airphotos.

It was

suggested

complementary way

that (Thie,

other remote sensing means

1976).

However,

SPOT-data

should be are

used

in a

competitive with

airphotos for medium-scale mapping.

9.1. Interpretation of black- and- white airphotos. Black- and white-airphotos are the most common tools in soil survey and the soil surveyor should be trained in making deductions about soil conditions through physiographic and morphogenetic interpretation. Black- and white-

212 photography is normally cost-effective in soil survey projects, provided that there are no serious limitations in obtaining flight coverage. The general feature of aerial photography in offering low-cost stereoscopy, is one of its most important advantages. Another aspect is the grey tone structure that is more friendly to the Observer than colour tones are. Especially the red and magenta colours that dominate most of the false colour imagery may fatigue the observer. Examples of airphoto-interpretation of areas in Suriname and b n i a are given in figures 9.1 to 9.4.

It should be emphasized that in the examples a

selection of aspects has taken place. The Suriname and Kenia areas have a mean annual rainfall of 2250 and 1550 mm respectively, and are representative of tropical areas with land use of respectively low and high intensity. The Suriname area (Fig. 9.1), photographed

at

a scale of

landtype/relief, land

1:40,000,

use/parcelling

may be

-

initially

studied using the aspects

natural vegetation, and

condition. The pictured area is an example of

drainage

the Young Coastal Plain

landscape, which shows in most of the area natural vegetation, since land use is

of

low

intensity

(shifting

cultivation

is

almost

absent).

Drainage

condition is concluded from site, land use and natural vegetation. A soil map (Mulders, 1977) is given in Fig. 9.2 Legend Fig. 9.2 Soil Map Northern Suriname (original scale 1:100.000): YOUNG COASTAL PLAIN 4) Poorly drained half-ripe and ripe clay; 8) Well drained medium and fine sand; Imperfectly drained sandy loam OK medium and fine sand; 9) 11) Poorly and very poorly drained nearly ripe clay; 16) Very poorly drained half-ripe (peaty) clay; 17) (Formerly) artificially drained ripe clay; 19) Very poorly drained half-ripe and unripe mostly pyritic clay and peat; Three landtypes can be distinguished, these being: the Beach Ridge Complex (8, 9 and l l ) , the Swamp and Marsh ( 4 , 16 and 19) and the River Flat ( 1 7 ) .

The different units have specific characteristics on the photographs of which natural vegetation is the most important. The Beach ridges (8) are characterized by high trees outstanding above a canopy with moderately high trees. Often the ridges can be recognized by the linear arrangement of these high trees. Where the ridges are close to each other and relatively narrow, complexes are distinguished. Between

these,

depressions are

found

with

moderately

high

forest and

213 imperfectly drained soils (9).

On other places, where the canopy in the Beach

Ridge Complex shows grass and low trees, soils are poorly to very poorly drained (11).

The Swamp and Marsh shows a unit with grass and moderate to high

coverage by low trees which contains very poorly drained mostly pyritic clay and peat (19).

During a transgression, clays are deposited in the depressions

which now bear an extremely low tree coverage (4),

or low tree coverage in the

actual drainage ways (16). The River Flat (17) was formerly used for plantations. Some of these are now used again for agriculture, others are not, and have low to moderately high forest. The area in Kenia (Fig. 9.3)

is initially photographed at a scale of 1:12.500

and may be studied by using the aspects of landtype/relief (Fig. 9.4a), site and land use/natural vegetation (fig. 9.4b). subdivision in

landtypes-relief, and when

slope,

The present scale enables a

combined with

land

use/natural

vegetation a relation to soil condition is accomplished. The results of the interpretation can be compared with the soil map of the area (fig. 9.4). Legend Landtypes - Relief (Fig. 9.4a): A. Upland ridge complex, mainly elongated: steeply dissected (As) and hilly (Ah) B. Upland hills: rolling to hilly C. Undulating plain. Legend (Fig. 9.4b): Land use

Natural vegetation

A. Agricultural use: annual herbaceous crops, pastoralism, some woody crops. P. Pastoralism.

Extr. low cov. trees and scrubs; lowmod. COV. grass.

N. Nature reserve F. Timber, firewood. Abbreviations: extr.

=

Very low - low COV. trees and scrubs; high COV. grass. Very high COV. scrubs. Riverside forest; mod.

extremely; mod.

=

moderate;

Legend soil map (Fig. 9.4~): C Chromic Luvisols and Luvic Phaeozems G Gleyic Luvisols and Gleyic Phaeozems S Solodic Planosols E Eutric and Chromic Cambisols, Haplic Phaeozems R Eutric Regosol (lithic phase)

COV. =

COV.

trees.

coverage.

Fig. 9.1 Airphoto Stereotriplet of an area in the Young Coastal Plain near Groningen at the Saramacca river (Suriname).

215

Reconnaissance S o i l Map o f N o r t h e r n Suriname n o r t h o f t h e 5 t h degree o f l a t i t u d e

e 1 km Fig.

9.2

S o i l map of

t h e area n e a r Groningen (Suriname, Map s h e e t 13).

For

legend: s e e t e x t .

The a c t u a l s c a l e of t h e photographs i n Fig. relief,

9.3 o n l y e n a b l e s a s u b d i v i s i o n i n

t h e s l o p e and s i t e u n i t s b e i n g t o o small.

r a t h e r broad

s u b d i v i s i o n of

r e l i e f (Fig. 9.4a)

the land,

Although t h i s produces a

t h e i n t e r p r e t a t i o n on l a n d t y p e s and

shows a number of u n i t s which a l s o may be r e c o g n i z e d on t h e

s o i l map ( F i g . 9 . 4 ~ ) .

I n a number of

c a s e s , n a t u r a l v e g e t a t i o n and l a n d u s e p r o v i d e f o r f u r t h e r

e v i d e n c e on s o i l c o n d i t i o n s .

Compare F of Fig.

9.4b w i t h G of Fig.

n o t e t h a t R s o i l s a r e mainly used f o r p a s t o r a l i s m

9.4c,

and

(and n a t u r e r e s e r v e ) .

The comparison w i t h t h e s o i l maps shows t h a t a c l o s e r e l a t i o n between t h e combined a s p e c t i n t e r p r e t a t i o n maps and

t h e s o i l . map can be accomplished.

Normally t h e l a n d t y p e is t h e main c r i t e r i o n f o r d e s c r i p t i o n i n t h e legend of t h e i n t e r p r e t a t i o n map, and a f u r t h e r s u b d i v i s i o n may be made on t h e b a s i s of

Fig. 9.3

Airphoto Stereotriplet of an area near Rangwe (Kisii, Kenya).

217

In ? r p r e t a ion 1a n d t w e s and r i i i e f

N

e 1 km

Interpretation l a n d use and na t u r a 1 vegeta t ion

1 km

218

Soil Map

1 km

Fig. 9 . 4

Interpretation and soil map of the Rangwe area (Kisii, Kenya, Top. map 130/1) a. Interpretation landtypes and relief b. Interpretation landuse and natural vegetation C. Soil map (Breimer, 1976)

other aspects. Examples of legends are given in par. 9.2. Although qualitative methods are most relevant for soil surveys, quantitative methods may assist the interpretation and may optimize the use of the information content of the airphotos. One of the features to digitize is the tonal variation. Digitization of the density range on the film is done by using

a

computer, the output codes from the digitizer are recorded and stored for subsequent retrieval and analysis. By using a colour television monitor, colour

can

be

designated

to

certain

grey

levels

to

facilitate

the

interpretation of the images obtained. Benson et al. (1973) used computerized methods for a detailed study of a fallow field in South Dakota in order to separate eroded and non-eroded soils. In this study statistical analysis were used to determine the relationship between soil properties and the tonal variations on the airphotos. The results indicate that the tonal variation

219 evident on the photographs of the field is related to several soil properties. The eroded terrain shows light tones due to increased reflectivity of the surface soil after removal of the A horizon and exposure of the underlying calcareous parent material.

The computerized method may be valuable, for

instance, when multitemporal data have to be studied to detect the progress of erosion over a certain period of time.

9.2.

The legend of the airphoto-interpretation map

A grouping of airphoto-interpretation units may be done as follows: A, B , C, etc.

landtype in morphogenetic terms

OK

physiographic indicat-

ions such as relief classes and drainage density or pattern;

A1, A2, B1 etc. All,

A12, B l l ,

physiographic subdivision; etc.

phases, minor differences.

When the structure is very complex, additional codes may be applied for a.0. slope, natural vegetation, land use, phototone or mottling of bare surfaces. The following features may be indicated: grade

OK

density, type or shape,

size, regularity and site sequence. Slope classes provide examples of grade, e.g. classes 1-6.

For surface density

or coverage classes, the reader is referred to par. 8.5.

(see also par. 6 . 3 :

texture and structure).

These low-level codes can be read on the map. The

legend does not show the total number of mapping units as they are delineated on the map, but insight in the properties of the mapping units can be given separately. Examples I and I1 of airphoto-interpretation legends for reconnaissance survey are given below. The following remarks are made in connection with these examples. Different

landscapes may

need

different

approaches.

In

arid

areas

attention will be centred on relief, drainage pattern and phototone, while in areas with tropical rain forest (and low human activity) relief, drainage pattern and natural vegetation are diagnostic for the distribution of soils. Furthermore, each study has its own requirements, e.g.

erosion studies and

land evaluation need special emphasis on slope and land use. The level of detail is determined strongly by the scale of the airphotos

220

as well as by the physiognomy of the area. The examples are only meant as a basis

for discussion.

It is stressed that the legend of the airphoto-

interpretation map needs much emphasis, and that discussions with team members may improve it considerably. A s far as soil survey is concerned, the lowest level should clearly present the soil mapping unit, while the higher levels have their special value for land division. lowest

level in accidented

In semi-detailed surveys, the

terrain will most

often be

based

on slope

characteristics. While a number of aspects are presented in the legend on the map, a separate description is usually given of

other aspects which are not

used

for

discrimination between the mapping units. This description is given in columns (tables). The

following

requirements

are

suggested

for

legends

of

airphoto-

interpretation maps: a. the units should be ordered logically, e.g.

old to young, high to low

elevation, high to low percentage of slope; b. high

levels

generally

indicate

land

types

with

geographic

soil

associations; C.

low levels generally indicate soil series or toposequences of soils (soil catenas);

in other cases, the lowest level is a subdivison made up by

photo-technical

description

(grey

tone

or

mottling),

of

which

the

significance has to be studied in the field; d. since morphogenetic terms (e.g.

floodplains, levees or dunes) offer more

information about soil conditions, these terms are preferred to physiographic terms (based on features such as slope and relief). ad a. Proposal for arrangement of aspects and grade or density in the legends: morphography and landtype land system (or type) - land unit - land component or site, land system - relief - slope, drainage density/high to low, high to low elevation, relief/steeply dissected to flat, other aspects vegetation/forest - grass - bare, coverage/high to low, structure and texture/coarse to fine, land use/nature reserve - forestry - rangeland agricultural use - settlement and infrastructure - water, phototone/light to dark.

-

221 EXAMPLE I Legend of airphoto-interpretation map of the Kilifi-area (Kenya). Scale of panchromatic airphotos 1:50 000. A Relatively high interior upland Very low to low drainage intensity A1 Rolling land with dendritic drainage pattern All Open woodland savannah Open woodland savannah with up to 50% grazing A12 Open woodland savannah with 50-80% grazing A13 A2 "Kopjes" land (small isolated bare hills) A21 Open woodland savannah A3 Undulating land with dendritic drainage pattern A31 Open woodland savannah A32 Open woodland savannah with up to 50% grazing Open woodland savannah with 50-80% grazing A33 A4 Rivervalley land B Relatively low interior upland B1 Moderate drainage density B11 Hilly land with subparallel drainage pattern B12 Rolling land with dendritic drainage pattern Further subdivision on natural vegetation and land use R2 Low drainage density B21 Rolling land with dendritic drainage pattern B22 Undulating land with dendritic drainage pattern Further subdivision on natural vegetation and land use B3 Rivervalley land C Coastal upland C1 High drainage density C11 Rolling land with dendritic drainage pattern C12 Rolling land with pinnate drainage pattern C2 Moderate drainage density C21 Hilly land with subparallel drainage pattern C22 Rolling land with subparallel drainage pattern C23 Rolling land with dendritic drainage pattern C24 Undulating land with dendritic drainage pattern C3 Low drainage density Rolling land with subparallel drainage pattern C31 Undulating land with subparallel drainage pattern C32 Undulating land with dendritic drainage pattern C33 C4 Rivervalley land D Coastal plain and marine terraces Very low to low drainage density D1 Relatively high undulating land D11 High marine terrace D12 Medium marine terrace D13 Low marine terrace D2 Beach area D3 Estuarine land D4 Tidal creek land D41 Saline margin D42 Overflow area Note: The description in tables of other interpreted land characteristics followed by deduction on inferred aspects is not included.

222

EXAMPLE I1 Legend of airphoto-interpretation map of the Antelope (California). Scale of panchromatic airphotos 1 : 2 4 , 0 0 0 . Landtypes and subdivision

A

Area

Other aspects Drainage Drainage density pattern

Vegetation and land use

(Inferred) drainage condition

very low

dendritic

grass and herbs

well drained

A2 Steep slopes

high

parallel

A3 Hilly land

high

dendritic

A4 Rolling to hilly

moderate

dendritic

low

dendritic

moderate

parallel and

high

dendritic dichotomic

Low mountaneous land A1 High undulating

plateus

land A5 Low, undulating

to rolling land

B

Valley

Plains B1 Sloping footslopes B2 Gently sloping

alluvial fans B3 Flat to gently

very low dendritic

sloping plain B4 Flat to gently

sloping depressions

-

locally diffuse gully pattern

or bare trees, shrubs, grass and herbs trees and shrubs or bare

grass and herbs

excessively drained somewhat excessively drained well drained

or bare grass and herbs, well drained shrubs or bare grass and herbs

well drained

grass and herbs, well drained bare or arable land arable land, well drained grass and herbs or bare grass and herbs moderately or arable land well drained

223

9.3.

From airphoto-interpretation map to soil map

A soil survey comprises the delineation of soil bodies. This is done by the

study of soil profiles. A soil profile is a sample of a pedon, the smallest unit of soil. In practice, one uses polypedons, which comprise a number of pedons with a natural boundary. The polypedon, or natural soil body, may be homogeneous or composite with regard to soil classes or series. The units of the airphoto-interpretation map often correspond to natural and composite soil bodies. Morphogenetic units offer much information about soils, while

physiographic units

at

least offer information about soil-forming

factors or consequences of soil conditions. The airphoto-interpretation may be done before. fieldwork or interactively. In both cases, however, the airphotos have to be interpreted in order to plan the field survey. Bennema and Gelens

(1969) have treated the procedures for soil mapping with the aid of airphotos. These procedures are summarized below. The boundaries on the airphoto-interpretation map may be:

-

valid for soil survey; invalid for soil survey, since they present vegetation differences due to tillage, or envelop units which are too small for the scale of mapping;

- of questionable validity for soil survey; fieldwork is necessary to evaluate the validity. Fieldwork enables the compilation of a soil map.

It involves the following

activities: a. check on validity of boundaries; b. check on accuracy of boundaries; C.

detection of missed boundaries;

d. delineation of boundaries not visible on the airphoto; e. set-up of legend; f. profile observations for description and classification of soil. Skill is required to choose the right location of the field observations. Their position is related to soil genesis and physiography. One observation may lead to a hypothesis about the kind of soil to be expected at another place. The second or third observation may verify the hypothesis or disprove it. However, when work is getting

on,

the position of the various soils,

224

generally a repeated sequence in a landscape unit, is no longer a secret and consequently the density of the observation network generally decreases with time up to the standard minimum number of observations as guided by the publication scale. Procedures

of

fieldwork with

regard

to

validity

and

accuracy

of

boundaries are the following:

-

full check on validity and accuracy of boundaries; limited check, that is

check only on validity of questionable boundaries;

a

no check on validity and accuracy of boundaries.

The check on validity and accuracy is related to scale as follows:

-

large-scale

- medium-scale

-

small-scale

-

full check; full or limited check; limited or no check.

The total number of observations depends, apart from skill and knowledge of the surveyor, also on:

-

the scale and purpose of the survey;

- the scale and quality of the airphotos;

-

the kind of landscape. Often selected areas are studied in detail in order to obtain insight in

the kind and distribution of soil bodies. These areas are called key areas or sample areas. The study of sample areas is usually recommended, but their use is limited for:

a. relatively small areas; b. well-known landscapes; C.

detailed surveys;

d. very small scales (e.g.

1:250,000

and smaller).

The requirements for sample areas are: a. they should be samples of large areas with different mapping units, which means that they should include many soil units; b. they should be well accessible; C.

there is a need for more than one sample area for large units.

Procedures with sample areas:

-

selection of sample areas by

indication of

major

landscape units

airphoto-interpretation;

-

detailed airphoto-interpretation of sample areas (indication of land

in

225

components);

A

survey of sample areas; airphoto-interpretation of total area; check on validity and accuracy in total area. revision of

the airphoto-interpretation of

the total area is usually

necessary due to evidence from field observations. Tropical forests are almost inaccessible and consequently need specific methods for soil mapping. Field observations are done in transects and in sample areas which have a relative dense network of transects. Soil mapping boundaries

are

drawn

by

interpolation

between

the

extrapolation outward from the areas with transects.

transects

and

by

It is important to

realize that remote sensing images, including airphotos, are the only tools for mapping in tropical forests. Often the remote sensing tool determines the possible detail. That is, when the interpretation units have shown their validity as indicators of soil units, the soil surveyor often has only the opportunity to map and describe the contents of these interpretation units. This implies that the final map may comprise homogeneous units as well as heterogeneous units (soil complexes).

This statement is made, since the

delineation of boundaries not visible

the remote sensing imagery, generally

on

requires much field work and thus time and financial means, which may be out of the scope of the project. S o i l variability may be studied in the field by statistical methods (see:

Webster, 1977; Northcliff, 1978; Burrough and Kool, 1981). An example of a possible soil survey using modern techniques like the statis-

tical approach i n conjunction with airphoto-interpretation is the following. On

the basis of the airphoto-interpretation, mapping units are selected which

show a trend in geographical distribution; these units are studied in detail either by transects or by sample areas. The variability within the units and between the units is analysed statistically, in order to check the validity of the discriminating criteria used to delineate the boundaries between the mapping units as well as the variation within the units. This might give an indication of the validity of the mapping units and may offer an indication of the number

of

observations necessary to map

the units accurately. The

statistical approach is particularly useful in case of large mapping units, which appear on the interpretation map as homogeneous units

on

the basis of

226 the criteria used. In the field, sampling together with statistical analysis might reveal diagnostic soil characteristics, which can be used for a further subdivison into soil units as well as for description of soil complexes, and, as stated before, to direct the number of field observations needed for an accurate description of the mapping units. The legend of the airphoto-interpretation map has to be transformed into a legend for the soil map. This can be done by a translation of physiography and morphography into morphogenesis followed by indication of soil taxonomic units. There are two types of soil map legends: a.physiography

and morphogenesis at high level (e.g.

soils of the rolling uplands),

river levees soils,

followed by taxonomic units, such as soil

series (or higher levels) and phases, the latter generally pragmatic (land use directed) ; b.taxonomic

units, e.g.

orders, suborders, great groups, etc.;

associated

soils should be indicated too.

9.4.

Land evaluation and planning of field survey A fundamental approach to land evaluation has been defined in its initial

stage by Beek and Bennema in 1971, and on the Expert Consultation of Land Evaluation for Rural Puposes at Wageningen (The Netherlands) in October 1972 (Brinkman and Smyth ed.,

1973). The first draft of a framework by FA0 (1973)

was widely circulated with a request for comments. This resulted in 1976 in "A Framework for Land Evaluation". Land

evaluation involves the execution and

interpretation of basic

surveys of climate, soil, vegetation and other aspects of land in terms of the requirements of kinds of land use or LUTS. To be of value for planning, the LUTS to be considered have to be limited to those which are relevant within the physical, economic and social context of the area and its population. Interpretation of remote sensing imagery gives information on soils, vegetation, present land use, and to a limited degree on climatic conditions. Also the physical effects of economic and social factors may be visible to some extent. Their information content and synoptic view cause remote sensing data to be important aids in land evaluation. A preliminary evaluation based

221 on

interpretation results of remote sensing data may be considerably helpful

in the planning. Airphoto-interpretation is applicable for delineation of land

mapping units being characterized by basic, compound and inferred aspects. These aspects are in fact land characteristics. The ultimate estimation of the grade of land qualities is only possible after a proper weighing of the land characteristics that influence the land qualities.

In

using

such

interpreted

land

characteristics and

expected

land

qualities and suitability, it has to be kept in mind, that it is only an interpretation, being of value for the planning of field survey. The best score will be obtained in S 1 (highly suitable) and N (not suitable) classes. Field and laboratory data are decisive for the final suitability but the preliminary interpretation may direct the field survey to areas that are expected to be suitable for the intended use already at an early stage of the survey. Some land characteristics such as relief grade, slope grade, slope length, site and drainage density may well be estimated by aerial photointerpretation and may direct the field survey to the most promising areas. Inferred interpretation aspects are of considerable value. requires a

specific approach in deduction.

As

Each of them

an example, the erosion

condition is discussed. The

methodology

of

airphoto-interpretation

for

erosion

and

soil

conservation survey is comparable with that for soil survey. However, special emphasis is laid upon aspects, such as:

-

relief and slope (angle, shape, length and position); drainage pattern and density;

-

-

erosion features; location of severely eroded land

8.0.

badland;

grey tone pattern; microrelief and surface stoniness; site a.0.

relative position of accumulation and erosion surfaces;

land use and crops, parcelling; percentage of vegetation cover; percentage o f fallow land and abandoned arable land; cattle tracks; size-, shape- and position of man-made terraces and other conservation

228

measures. Examples of soil erosion-accumulation sequences based on grey tone pattern on airphotos from top- slope- valley bottom (Bergsma, 1974) are:

-

the common case dark

-

light

-

dark, where the A - horizon on the slopes

is largely eroded and a lighter s u b s o i l is exposed;

-

the reverse case light - dark

-

light, where a light textured surface

soil on the slopes is largely eroded and a heavier subsoil (e.g.

an

argillic horizon) is exposed. It will be clear, that the appearance of the area itself, and scale of the airphotos determine to a large extend the potential of the interpretation. Furthermore, the information level in the form of maps and reports on environmental conditions has also much impact. However, it is important that at the start of the interpretation procedures the final aim of the project is considered. The purpose of the survey determines a.0.:

-

the kind of environmental data to be collected;

-

the required survey scale.

the minimum area of planning interest;

The latter also depends on existing base maps and other environmental data.

For practical reasons, the working or survey scale is in general larger e.g. twice the scale intended for the final maps. For planning of the field survey, three land qualities are important, these being:

-

the size, distribution and arrangement of mapping units or the land complexity;

-

the trafficability expressed by

relief, drainage condition and the

presence of roads and tracks, navigable rivers and streams;

-

the accessibility of

the terrain expressed by

type and degree of

vegetation cover and the possibility of housing and/or campsites. The land complexity is scale dependent. Land may appear homogeneous at large

scales, but heterogeneous at small scales. A measure for land complexity is the size of the land component or the mapping unit at the lowest l e v e l (e.g.

All, A12). land

If the size of the components is dominantly smaller than 1 cm2, the

is considered to be heterogeneous at

the particular scale and an

229

observation density is suggested of at least 2 augerings per cm2 (final map). Table 9.1.

presents estimates of the daily number of auger observations (Nt),

and progress by soil augering in ideal terrain, which is homogeneous at scales larger than 1:100.000,

having slopes not steeper than 16 % and a tree and

shrub coverage of less than 25 %. This table is based on the following assumptions:

-

When there is a check on accuracy, the following reduction factors have to be applied i n order to calculate the number of augerings contributing to the daily progress, 0.75 for 1:5000 scale, full check; 0.70 for 1:10.000 scale, full check;

0.85 for 1:ZO.OOO scale, limited check; 0.80 for 1:50.000 scale, limited check;

-

the land is considered to be heterogeneous at scales of 1:lOO.OOO smaller (Np

-

=

and

Nt);

at scales of 1:lOO.OOO and smaller, no check on accuracy is performed, but more time is spent on transport and desk work.

The number of survey team days can be calculated by dividing the total surface area by the daily progress. In addition, the terrain characteristics have to be evaluated to obtain correct estimates for the land under consideration. The following classes of trafficability are suggested: a) well drained flat, undulating to rolling terrain; effective transport by vehicles is possible in the field; b) as for (a); no effective use of vehicles; main transport on foot; c) well drained, or excessively drained hilly to steeply dissected terrain; use of vehicles is moderately effective; d) as for (c), but no effective use of vehicles; transport on foot; e) excessively drained mountainous terrain

OL

effective use of vehicles; transport on foot.

poorly drained terrain; no

N 0

Table 9.1

Approximation of d a i l y p r o g r e s s i n i d e a l t e r r a i n u s i n g e s t i m a t e s of a u g e r i n g s / h r ( 6 f o r 1: 5.000 s c a l e , 5,9 f o r o t h e r s c a l e s ) .

Kind of s u r v e y

range of scales

scale

area survey method 1 cm2 map (S)

detailed

1:10,000 and larger

1:5,000 1:10,000

0.25 ha r e g u l a r g r i d 1/2 hr 1 ha or f r e e grid d i r e c t e d by physiography; interpolation and f u l l check on a c c u r a c y

semi-detailed

smaller t h a n 1 :10,000 up t o 1:25,000

1.20,OOO

4.0

reconnaissance

smaller t h a n 1:25,000 up t o 1:100,000

1:50,000 25.0 ha key a r e a s and 1 1 / 4 h r 1:100,000 1 km2 transects; 14 h r extra-polation, no check on accuracy

smaller t h a n 1:100,000 up t o 1: 250,000

1:200,000 4 km2

medium i n t e n s i t y

reconnaissance low i n t e n s i t y

-

ha

f r e e g r i d of transects d i r e c t e d by physiography; interpolation and l i m i t e d check on accuracy

as f o r 1: 100.000

N t = N t o t a l , N a = N a c c u r a c y check, Np = N p r o g r e s s = Nt

-

N,

average t i m e per day s p e n t at transport

1 hr

1 3/4 h r

daily transport,

d a i l y deskwork and

average time p e r day s p e n t a t desk work

average d a i l y number of auger o b s e r v a t i o n s (N) Nt Na Np

average daily progress surface area (P)

1 hr

39

10

29

7.25 ha

14 hr

32

5

27

108 ha

1 3/4 h r 2 1/4 h r

30 25

-

6

24 12

600 ha 12 km2

2 j hr

21

-

10

40 km2

231 The following classes of accessability are suggested, based on vegetation cover:

- 25 X, 25 - 75 X, 75 - 100 %.

A) tree and shrub coverage 0

B) tree and shrub coverage C) tree and shrub coverage

Reduction factors on the average daily number of auger observations have to be applied

for trafficability and accessibility in relation to

scale. The

following factors are suggested: for scales of 1:lO.OOO trafficability

and larger

c 0.90

accessibility

d 0.85 e

B 0.90

C 0.85

0.80

for scales smaller than 1:lO.OOO

same reduction factors, but in addition for

transportability or the use of vehicles in the field, these factors being: b 0.90 Table 9.2.

d

+e

0.85

gives a summary on terrain classes and reduction factors. Of

course, further testing on the reduction factors is necessary and ought to be done according to the specific conditions in land or country. Table 9.2 Terrain classes and reduction factors on average daily number of auger observations and average daily progress. terrain classes

1 2 3 4 5 6 7

8 9 10 11 12 13 14 15

trafficability average daily

accessibility

reduction factors on number of auger observations and daily progress 1 :10.000 smaller and than 1 :10.000 larger

A

-

-

B C

0.90 0.85

0.90

a a a b b b

A

-

0.85 0.90

B C

0.90

0.81

0.85

C C

A B

0.90

C

C

d d d

A

e e

A

0.77 0.90 0.81 0.77 0.72 0.65 0.61 0.68 0.61 0.58

e

B C

B C

0.81 0.77 0.85 0.76 0.77 0.80 0.72 0.68

Through application of the reduction factors it is then possible to calculate

232 the daily number of auger observations and the corresponding daily progress, which are both dependent on the terrain characteristics. The calculation suggested is based on ideal climatic conditions or in other words, a dry season. When the field work is carried out in a wet season, another reduction factor should be applied e.g.

0.7

or 0.8.

The following formula may be used to calculate Np for terrain class x (or Npx) : Npx

=

(9 - 1)

c.s.zx.Npl

where Npl is Np for ideal terrain class 1 (see table 9.1),

-

c

=

and

reduction factor land complexity (heterogeneous terrain 0.5, homogeneous terrain 1; in table 9.1, c is applied for 1:100.000 and 1:200.000);

-

s =reduction factor for climatic conditions, wet season 0.7

or 0.8, dry

season 1;

-

Zx= reduction factor for terrain class x (see table 9.2).

The average daily progress in ha or km2 ( P ) can be calculated from:

P

=

Npx

where S

.S =

(9

-

2)

area 1 cmL map (ha or kmL) at scale of publication.

Besides for auger observations, days have to be included for field work in connection with:

- preparation and detailed examination of soil pits (depth 1.5 - 2.0 m or to an impenetrable layer); average 2/day,

- deep borings ( 3

-

5 m or to an impenetrable layer) in a free grid or

preferably along transects in order to obtain insight in soil depth, parent material and in sedimentology. Soil

samples

for

laboratory

analysis

are

usually

taken

from

characteristic soil pits (typical soil profiles) throughout the area and if applicable from the key or sample areas. Sampling is done from soil horizons and/or stratifications or at regular intervals in the soil profile. In special cases, a relatively large number of samples is taken for limited laboratory analysis, often at fixed sampling depths e.g.

for estimation of salinity and/or alkalinity. Depending on the

type of survey and the information required, certain field experiments (like

233 measurements of permeability and infiltration rate and conductivity) are to be executed as well. The amount of time involved in laboratory analysis varies greatly with

the type of

analysis (soil chemical, soil physical and

OK

mineralogical) and of course the size and quality of the laboratory to which the samples are forwarded. An estimate of the rate of progress for soil sample analysis has to be made in consultation with the laboratory. Geostatistical approaches (non-aligned sampling

OK

detailed along transects)

may be used to determine soil variability and discriminating criteria between soil units. As

stated before, the purpose of study may direct and concentrate the

observations on the more "promising" parts of the area. Consequently, some land units may be studied in less detail than the rest of the area, and estimates for smaller scale may be used to calculate the work involved. Such differences in survey intensity have to be indicated checklist

on

on

the map and in the report. A

the planning of soil survey is given in table 9 . 3 .

Table 9 . 3 Checklist on the planning of soil survey.

I

survey team days Organization and Administration

I1

Preliminary airphoto-interpretation mapping units: A, B , C, etc. complexity: trafficability: accessibility: housing, campsite: transport in field:

111

Purpose of field survey: areas of high interest: minimum area of planning interest: kind of environmental data to be collected: required final scale: working scale: basic field equipment for soil sampling, soil description and mapping:

IV

Field survey expected weather conditions in survey-period: observation system(s): surface areas of land units: number of man days involved: - for geostatistical observation: - item for deep augering:

234

-

item for soil pits: item for routine augering per land unit: delay due to social or religious aspects:

V

Survey team days for other observations directed by the purpose of study other observations:

VI

Final airphoto-interpretation

VII

Laboratory analysis - samples of soil pits - other samples

VIII Preparation of maps and report

-

man-days

soil scientific work: typing: drawing: other activities

The data listed in table 9 . 3 enable the production of a time-schedule for

the soil survey. A final evaluation involves a calculation of cost of the survey. The attempt

for planning of field survey, needs further application. Good results were obtained using this method in recalculation of man-days needed for medium and small-scale soil surveys in Suriname and Pakistan. A soil map should always be accompanied by a report. An example of the contents

of a soil survey report, which may comprise the following subjects, is given below: 1)

2)

3)

4)

Introduction. Purpose of study Location of the area Material and methods. Topographic maps Geological maps Data airphotos: scale, flying height, focal distance, aerial film and camera, filters Methods of interpretation and fieldwork General information on soil forming factors in the study area. Climate Geology, geomorphology, petrology Hydrology Natural vegetation and land use Airphoto-interpretation and fieldwork. Relation between soils and soil forming factors Relation of photo-interpretation aspects with s o i l conditions Construction of legend

235 5)

6)

7) 8)

9.5.

Soil data and classification. Description of soil mapping units Soil profile description, laboratory analyses and soil classification Soil variability Land evaluation. Socio-economic considerations Selection and requirements of land utilization types Rating of land qualities Estimation of land suitability classes for land utilization types Summary. References.

Interpretation of true colour airphotos. Despite early relatively successful use of aerial colour film, it was only

in the latter half of the sixties that serious attention has been given to

their potentiality. This was primarily due to the insufficient speed and low resolution of the earlier films. Also the high cost and doubt about the value for interpretation played a part. It is argued by those who are in favour of colour photography, that the limited resolution of colour photography when compared with panchromatic photography, is offset by the higher resolution of colours. With colours, an accurate distinction between tones is possible to a degree that is 600 times to 2000 times greater than the distinction in grey tones (Myers, 1968). The value of colour photography for discrimination between objects, therefore, is beyond any doubt (for d'iscrimination between different high chroma soils, the reader is referred to Gerbermann et al., 1971). Although colour fidelity may be low, it is not a limiting factor in the identification of

terrain information (Anson,

1968).

Landform analyses can be

usefully

supplemented by photometric information extracted from colour imagery, such as the ratio Red/Blue revealing differences between soils. For details, the reader

is referred to Piech and Walker (1974).

9.6.

Interpretation of black-and-white Infrared airphotos. Generally, the black-and-white Infrared films offer a good discrimination

between various types of natural vegetation and may emphasize differences in

soil moisture conditions. Since the cost of black-and-white Infrared photography is nearly equal to that of panchromatic photography, the application of this type of film is increasing in tropical forest areas, especially when large areas are concerned.

236

De la Souchere (1966) compared panchromatic films with black- and -white Infrared films in order to find new criteria for delineation of different types of forest in Ctite-d' Ivoire. Small-scale mosaics (1:200.000) -white

Infrared photographs appeared

of black- and

to be a good aid in comparing the

contrasts in Infrared reflection of different types of forest. However, in Ctite-d'Ivoire

the differences between panchromatic and black- and

-white

Infrared as a detecting agent, were found to be variable from one region to the other. At large scale (e.g.

1:3,000),

individual crowns of trees are visible and the

studies may be directed to crown damage (Wolff, 1966). Another application of black- and -white Infrared photography may be found in detecting areas affected by salinity. The crops (e.g. salinity will

cotton) affected by

show a lower reflectance when compared with healthy crops.

However, problems may arise in discriminating between the surface soils and the plants, through which the interpretation may become difficult. Fig. 9.5 enables us to make a comparison between a panchromatic and a black- and -white Infrared aerial photograph of an area at the Surinam river. The panchromatic airphoto was taken in 1953. The black- and -white infrared airphoto was acquired 22 years later when an oilpalm plantation had been founded. Both images show the effect of shifting cultivation. The black- and white -Infrared photograph ha6 high contrast and clearly shows vegetation differences. The dark spots in the plantation may point to places with a moist soil surface.

9.7.

Interpretation of false colour airphotos. The first application of the false colour-film took place in World War I1

when it was used as a detection film for camouflaged military objects. The film is applicable from high altitudes (e.g. 9 km) enabling scales of 1:60.000 up to 1:lOO.OOO.

Owing to the recording of green, red and near Infrared radiation,

the potential of this film for discrimination between soils and vegetation is high. Plants frequently are good indicators of soil condition. Therefore, in case of soils covered by vegetation, the soil scientist has equal interest in detection capability of this film when compared with agricultural and forestry experts. In section 4.2,

the formation of colours in the colour Infrared film

is treated. Below, false colours are discussed briefly.

231

Fig. 9.5.

Panchromatic airphoto (a) and black- and -white Infrared airphoto (b) of the Victoria area at the Surinam river (courtesy CBL Surinam).

238 Dry soils appear in light blue, or light green, and in the case of high organic matter content, in grey colour on this film, while wet soils appear in dark tones. However, grass and healthy broadleaved vegetation are pictured in red to magenta and conifers show dark tones with a slightly magenta hue. Vegetation damage may result in a decrease in near Infrared reflectance and thus leads to an increase in cyan dye and a darker magenta hue. However, plants with yellow unhealthy leaves will appear in white to mauve tones. Knipling (1969) states that many of the colour differences on Ektachrome Infrared aerial photography, particularly the subtle shades of red, can be traced to variations in foliage area, density and orientation, rather than to the reflection properties of individual leaves. When

the reflectance of a plant canopy is compared to that of the single leaf,

there is a striking difference between the canopy reflectance of Visible radiation and that of near Infrared radiation. The canopy Visible reflectance may account for 40%, and the canopy near Infrared reflectance for 70% of the reflectance by a single leaf. The difference will be due to interaction of the radiation transmitted by the toplayers of the canopy with that of the lower leaves. Upon this interaction the Visible radiation is strongly absorbed while the Near Infrared is reflected. The

application

of

false

colour-film

is

reported

in

detection

of

vegetation damage in forested areas (Murtha, 1978) and in urban areas (Remeijn, 1977) as well as in assessment of severity and extent of salt-affected areas in agricultural fields (Myers, 1966; National Academy, 1970). According to Anson (1968), the Ektachrome Infrared film is excellent for soil moisture studies and delineation of vegetation boundaries. Suitable scales are reported for different studies:

-

forestry 1:6,000 and 1:16,000 (Stellingwerf, 1968);

- crown damage in urban areas 1:2,000 or 1:5,000 (Remeijn, 1977);

-

assessment of crop diseases 1:3,600 up to 1:8,400.

For the assessment of salinity problems in growing cotton crops, proper timing of the aerial survey is required. The crops have to be mature and the cotton bolls should not be open. Furthermore, moisture stress will be likely when temperatures and evapotranspiration are high, and irrigation is relatively long ago. Moisture stressed cotton shows less near Infrared reflectance than healthy cotton and produces dark magenta tones on the false colour photographs while cotton plants that are seriously affected by salinity appear as nearly black.

239 Below, an example (see plate 1) of a false colour image of an area in the Netherlands is discussed. Different land use types are clearly marked: planted forest and roadside planting (different colour tones), grassland (bright red to magenta) and arable land (light blueish-green, pink and light red to magenta; note effect of tillage).

Owing to the high reflectance of near Infrared by

grass canopies, red dominates in these places in the picture and differences in grass coverage are masked.

On

the contrary, different canopies of planted

forest and roadside planting show much contrast. At least eight different tree canopies can be recognized by evaluation of colour, size, shape and texture.

While contrast is largest between foliage trees and coniferous trees, this picture

clearly

demonstrates

the

high

potential

of

false

colour

for

differentiating between foliage tree species. To understand colour formation in the false colour image, the various objects can be described visually by their Colour Chart (plate 3 ) .

colour according to the I.T.C.

The colour codes,

obtained in percentages yellow, magenta and cyan, give an impression of the dyes

present

in

the

transparent

film

or

colour

photograph.

percentages are related to the exposure values (see par. 4.2

a.0.

These

dye

fig. 4.9).

However, without quantitative measurements and calibration techniques, the relation is qualitative and rough.

9.8.

Application of multispectral photography. Experiments have been done with multispectral photography (Yost et al.,

1969) to determine its ability for measurement of basic ecological parameters e.g.

unique signatures for species of agricultural crops, trees and soil

surface types. To correct for variables, different techniques are applied (see section 7.8),

for instance man-made targets of known spectral reflectance are

used for calibration, and measurements on illumination and spectral reflectance are carried out. Although results are promising for establishing soil surface types (National Academy, 1970),

application is found mostly in the field of

crop growing. According to Kannegieter (1980), multispectral photography may be applied in order to:

-

gain a better insight into disease behaviour of crops as a basis for more accurate control/prevention;

-

single out in time, likely priority crop areas for preventative/curative action;

- assess damage and yield-reduction

of crops.

9.9.

Interpretation of sequential aerial photography. Interesting

multitemporal

results

about

application

survey are reported by

of

Kiefer

sequential

(1973).

He

repetitive

OK

stated that the

distinction between different soil types was accomplished better by the use of photography of certain dates than by photography of other dates. Consequently, an

optimum

set

of

airphotos

can

be

made

by

selection

from

multidate

photography. Other applications are found in studies on land evaluation, and more specific in erosion studies. Milfred and Kiefer ( 1 9 7 6 ) used sequential aerial photography to study soil variability. They used airphotos taken on 20 different days from May through November 1969 of a corn field in the state of Wisconsin. The photographs were taken from a Cessna 172 aircraft at altitudes ranging from 610 to 1070 m above the terrain. The film types used were: Kodachrome 11 film and Ektachrome InfKaKed Aerof ilm (Kodak type 8 4 4 3 ) . Very little rain had fallen in the area during July, August and September; consequently, the growth of corn during this period was dependent on moisture stored in the soil, the amount of which is largely determined by site, texture and soil depth. The corn grew rapidly where sufficient moisture was available, but turned brown in places where i t was deficient. Dry areas with reduced corn growth were delineated by interpretation of the repetitive airphotos. The dry areas corresponded to slight topographic elevations of 1 to 2 m, with gentle convex slopes. Adjacent nearly-level lower areas did receive runoff from these areas and were relatively moist throughout the summer, enabling better corn growth; the soil depth was found to be the greatest in these lower areas. Thus the crop pattern revealed a dynamic soil property as well as soil distribution. The relationship between crop growth pattern and soil will vary from year to year and from region to region depending on differences in soil profile characteristics, weather conditions and other edaphic factors. Therefore, a careful evaluation of the validity of assumed causive factors is always a necessity. Soil

scientists will

statements about

often

find

it

soil variability without

difficult

to make

quantitative

conducting expensive and

time-

consuming field investigations. Sequential aerial photography offers a tool for evaluation of soil variability and may simultaneously improve the speed and accuracy of mapping. A small format camera mounted on a light aircraft can be

241 used for this purpose. For economic feasibility, the study of seasonal changes may be limited to land units selected from a large study area. Diazo techniques and additive colour techniques (see par. 5.1)

may assist in change detection.

Diazo developing of one band positive transparent materials of two or three acquisition dates in yellow, magenta and/or cyan coloured imagery, forms one of the possibilities. When superposing the diazos of three acquisition dates in yellow, magenta and cyan, the resulting coloured image is interpreted. For imagery with correct colour balance, the interpretation is as follows: black, grey and white indicate no change; coloured places have undergone a change at one or more of the acquisition dates, the colours observed are indicative for change at specific acquisition date(s).

9.10.

Conclusions Black- and -white photographs represent the most common tool for soil

survey by offering a.0. A

low cost stereoscopy.

grouping of airphoto-interpretation units is suggested. When the flow chart

on interpretation for soil survey (see Fig. 8.1) with the suggested grouping (par. 9.2),

is applied, this, together

may lead to uniformity in the legends

of interpretation maps. Fieldwork comprises a.0. boundaries.

Field

checking on validity and accuracy of interpretation

observations may

be

done

guided

by

physiographic

and

morphogenetic interpretation in transects. The interpretation products may be used for preliminary land evaluation which is very useful in the planning of field survey. True colour aerial photography is normally applied at large scales. It is argued that colour fidelity ,which is low when the colour photographs are taken from a high altitude, is not seriously limiting the identification of terrain information. Black- and -white Infrared airphotos offer a good means for discrimination between

vegetation

types

and

clearly

show

differences

in

soil moisture

conditions. Especially in tropical forest areas, application is found for this type of photograph. False

colour

photography

deserves

attention

as

it

offers

a

good

discriminating potential for vegetation types and provides means for assessment of vegetation damage in forest areas, or the severity of salinity as well as the extent of salt-effected areas in agricultural fields. The information

242

presented by the false colours may be described best through its transformation in colour codes, representing percentages of yellow, magenta and cyan.

Multispectral photography i s

generally applied in agricultural remote

sensing projects, but is also promising for soil survey in regions that contain large areas of bare soil. Multitemporal photography may be useful in areas where soil variability is large. 9.1 1.

References

Anson, A., 1968. Developments in Aerial Colour Photogrphy for Terrain Analysis. Photogrammetric Engineering 1968: pp. 1048-1057. Beek, K.J. and Bennema, J., 1971. Land Evaluation for Agricultural Land use Planning. An Ecological Approach. Wageningen, The Netherlands: 47 pp. Bennema, J . and Gelens, H.F., 1969. Aerial Photo-interpretation for Soil Surveys. Lecture notes ITC courses Photo-interpretation in Soil Surveying: 87 pp. Benson, L.A., Frazee, C.J. and Waltz, F.A., 1973. Analysis of Remotely Sensed Data for Detecting Soil Limitations. South Dakota Agr. Exp. Station. Journal Series No 1168. SDSU-RSI-J-73-05: 9 pp. Bergsma, E., 1974. Soil Erosion Sequences on Aerial Photographs. ITC Journal 197413, Enschede, The Netherlands: pp. 342-376. Breimer, R.F., 1976. Detailed Soil Survey of the Rangwe Area. Training Project in Pedology, K i s i i , Kenya, Agric. Univ. Wageningen, The Netherlands: 56 PP. 1973. Land Evaluation for Rural Purposes. Brinkman, R., Smyth, A.J. (ed.), ILRI, Summary of an Expert Consultation (Chairman: J. Bennema). Wageningen, The Netherlands, Publ. 17: 116 pp. Burrough, P.A. and Kool, J.B., 1981. A Comparison of Statistical Techniques for Estimating the Spatial Variability of Soil Properties in Trial Fields, 3Sme Colloque AISS, Traitement Informatiques des Donn6es de Sol (Tome 1 Paris: pp. 29-37. FAO, 1976. A Framework for Land Evaluation. Soils Bulletin, FAO, Rome nr. 32: 72 PP. FAO, 1979. Soil Survey Investigation for Irrigation. Soil Bulletin no 42: 188 pp. Gerbermann, A.H., Gausman, H.W. and Wiegand, C.L., 1971. Color & Color-IR Films for Soil Identification. Photogrammetric Engineering 1971: pp. 359-364. Kannegieter, A., 1980. An Experiment using Multispectral Photography for the Detection and damage Assessment of Disease Infection in Winter-wheat: agronomic considerations. ITC Journal 1980-2: pp. 189-234. Kiefer, R.W., 1973. Sequential Aerial Photography and Imagery for Soil Studies. Highway Research Record 421: pp. 85-92. Knipling, E.B., 1969. Leaf Reflectance and Image Formation on Color Infrared Films. In: Remote Sensing in Ecology; ed. by P.L. Johnson, Athens, Univ. of Georgia Press: pp. 17-29. Milfred, C.J. and Kiefer, R.W., 1976. Analysis of Soil Variability with Repetitive Aerial Photography. Soil Sci. SOC. Am. J., Vol. 40: pp. 553-557. Map Mulders, M.A., 1977. Reconnaissance S o i l Map of Northern Surinam 1:100.000, sheet 13. Soil Survey Department, Ministry of Development, Surinam. Murtha, P.A., 1978. Remote Sensing and Vegetation Damage: A theory for

243

Detection and Assessment. Symp. on Remote Sening for Vegetation Damage Assessment 1978. Publ. by Amer. SOC. of Photogrammetry: 32 pp. Myers, V.I., Asce, M., Carter, D.L. and Rippert, W.J., 1966. Remote Sensing for Estimating Soil Salinity. Journal of the Irrigation and Drainage Division. PKOC. of the Amer. SOC. of Civil Eng, IR 4: pp. 59-69. Myers, V.I. and Allen, W.A., 1968. Electrooptical Remote Sensing Methods as Nondestructive Testing and Measuring Techniques in Agriculture. Applied Optics Vol. 7, No 9: pp. 1819-1838. National Academy of Sciences, 1970. Remote Sensing. With special reference to Agriculture and Forestry. Washington: 423 pp. 1978. Soil Variability and Reconnaissance Soil Mapping: a Nortcliff, S., Statistical Study in Norfolk. The Journal of Soil Science, vol. 29, No 3, Oxford Univ. Press: pp. 403-418. Piech, K.R. and Walker, J.E., 1974. Interpretation of Soils. Photogrammetric Engineering - 1974: pp. 87-94. Remeijn, J.M., 1977. Infrarood Kleurenfilm voor Vegetatiestudies. Landbouwkundig Tijdschrift 89-9: pp. 308-313. SouchSre, P. de la, 1966. Comparaison des Photographies Panchromatiques et Infrarouges dans la Recherche de Renseignements en Zone Forestiere en Cote-d'Ivoire. IIe Symposium International de Photo-Interpr6tation, Paris 1966: 11/59-66. Stellingwerf, D.A., 1968. The Usefulness of Kodak Ektachrome Infrared Aero Film for Forestry Purposes. 11th Congress of the International SOC. for Photogrammetry, Lausanne: 6 pp. Thie, J., 1976. An evaluation of remote sensing techniques for ecological (biophysical) land classification in northern Canada. Proc. of the first meeting Canada Committee on Ecological (Biophysical) Land Classification. 25-28 May, 1976, Petawawa, Ontario: pp. 129-147. Webster, R., 1977. Quantitative and Numerical Methods in Soil Classification and Survey. Clarendon Press, Oxford: 269 pp. Wolff, G., 1966. Schwarz-weisse und falschfarbige Luftbilder als diagnostisch Hilfsmittel fiir operative Arbeiten beim Forstschutz (Rauchschaden) und bei der Waldbestandsdhgung. IIe Symposium International de PhotoInterprgtation, Paris 1966: 11/85-95. Yost, E. and Wenderoth, S., 1969. Ecological Applications of Multispectral Color Aerial Photography. In: Remote Sensing in Ecology edit. by P.L. Johnson, Athens, Univ. of Georgia Press: pp. 46-62. 9.12.

Additional reading.

Beek, K.J., Bennema, J. and Camargo, M., 1964. Soil Survey Interpretation in Brazil. A System of Land Capability Classification for Reconnaissance Surveys. First Draft. DFFS-FA@Stiboka, Rio de Janeiro: 36 pp. 1978. Land Evaluation for Agricultural Development. Thesis Agric. Beek, K.J., Univ. Wageningen, The Netherlands: 333 pp. Bennema, J. and Meester, T. de, 1981. The Role of Soil Erosion and Land Degradation in the Process of Land Evaluation. In: Soil Conservation. Problems and Prospects (ed. by R.P.C. Morgan). John Wiley & Sons, New York: pp. 77-85. Bergsma, E., 1971. Aerial Photo-Interpretation for Soil Erosion and Conservation Surveys. Part 11: Erosion Factors. ITC 9/71, Enschede, The Netherlands: 37 pp. Bergsma, E., 1980. Method of a Reconnaissance Survey of Erosion Hazard near Merida, Spain. Proc. Workshop Assessment of Erosion in USA & Europe (ed. by de Boodt & Gabriels), John Wiley & Sons, New York: pp. 55-66.

244

Bowden, L.W. and BrooneK, W.G., 1970. Aerial Photography, a diversified tool. Geoforum 1970/2, Braunschweig, Germany: pp. 19-32. Breuck, W. de en Daels, L., 1967. Luchtfoto's en hun Toepassingen. E. StoryScientia P.V.B.A., Gent: 176 pp. 1968. The development, use and efficiency of indices of soil Bryan, R.B., erodibility. Geoderma 2: pp. 5-26. Clos-Arceduc, A., 1971. Disposition des Structures D'Origine Eolienne au Voisinage d'un Groupe de Barkhanes a Parcours Limite. Revue "Photo Interpretation, No 2 - 1971, fascicule 1, Editions Technip, Paris. Dudal, R., 1981. An Evaluation of Conservation Needs. In: Soil Conservation Problems and Prospects (ed. by R.P.C. Morgan). John Wiley & Sons, New York: pp. 3-12. Fairweather, S.E., Meyer, M.P. and French, D.W., 1978. The Use of CIR Aerial Photography for Dutch Elm Disease Detection. Symposium on Remote Sensing for Vegetation Damage Assessment, Comm. VII. Int. SOC. for Photogrammetry, Seattle, Washington 1978: 12 pp. Florence, G.R., 1980. Survey and Evaluation of Rangelands in the HukuntsiNgwatle Pan Area, Kalahari, Botswana. ITC, Enschede, The Netherlands (thesis): 141 pp. Foggin, G.t. I11 and Rice, R.M., 1979. Predicting Slope Stability from Aerial Photos. SOC. of her. Foresters, J. of Forestry: pp. 152-155. Fritz, N.L., 1965. Film sees New World of Color. Citrus World 2 ( 2 ) : pp. 11-12, 26.

Gardiner, M.J. and Husemeyer, C., 1980. Selected Socio-Economic Aspects of Land Utilization. Commission of the European Communities. EUR 6876 EN: 308 PP Graham, R., 1980. The ITC Multispectral Camera System with respect to Crop Prognosis in Winter-wheat. ITC Journal 1980-2: pp. 235-254. Howard, J.A., 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Kiefer, R.W., 1972. Sequential Aerial Photography and Imagery for Soil Studies. Highway Research Record 421. Remote Sensing for Highway Engineering: pp. 85-92. Kirkby, M.J. and Morgan, R.P.C., 1980. S o i l Erosion. John Wiley & Sons. New York: 312 pp. Lee, J. and Plas, L. van der, 1980. Land Resource Evaluation. Commission of the European Communities. EUR 6875 EN: 144 pp. Mainguet, M. et Chemin, M.C., 1977. Les Marques de L'Erosion Eolienne dans le Sahel du Niger d'aprss les Images Satellites et les Photographies ' Agriennes. ler Colloque Pedologie T616d6tection, AISS, Rome: p. 139-

.

148.

Morgan, R.P.C., 1979. Soil Erosion. Topics in Applied Geography. Longman, London and New York: 113 pp. Purdue University (Lafayette, Indiana), Agric. Exp. Station, 1968-1970. Lab. for Agric. Remote Sensing. Vol. No 3 and 4, Annual reports: 175 pp. and 111 pp. 1979. Ecology and Utilization of Desert Shrub Rangelands in Thalen, D.C.P., Iraq. Dissertation Univ. Groningen and ITC, The Netherlands: 428 pp. Vink, A.P.A., 1975. Land Use in Advancing Agriculture. Springer-Verlag, Berlin. White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press, Oxford: 104 pp. Yost, E., 1967. Applications of a Multisprectral Color Photographic System. C.I.S./I.C.A.S. Symp. on Airphoto-interpretation. Ottowa, Canada: 19 PP. Yost, E.F. and Wenderoth, S., 1967. Multispectral Coibr Aerial Photography Photogrammetric Engineering: pp. 1020-1033.

245 Zonneveld, I.S., 1979. Land Evaluation and Land (scape) Science. ITC Textbook of Photo-Interpretation, Vol VII, Chapter VII, Enschede, The Netherlands: 134 pp. Zuidam, R.A. van and Zuidam-Cancelado, F . I . van, 1979. Terrain Analysis and Classification Using Aerial Photographs. ITC Textbook of PhotoInterpretation, Vol. VII, Enschede, The Netherlands: 310 pp. and suppl. 23 PP.

246

10.

AIRBORNE LINE-SCANNING IN THE 0.3-8

pm REGION

Airborne scanning is treated separately from spaceborne or satellite scanning, since it differs from the latter in enabling observation at low altitudes and consequently it may show differences in spatial and spectral resolution. The spatial resolution of a scanning system is determined by its IFOV and the speed of detection in relation to the speed of the platform ( s e e par.

6.1).

The speed of platform and groundpass of spaceborne platforms is

normally taken higher than that of airborne platforms. The same can be stated for the speed of detection. Therefore, airborne scanning permits the use of relatively long observation times per pixel. Although narrow band data at low spatial resolution can be acquired from spaceborne platforms, the use of relatively narrow bands at high spatial resolution is applicable to airborne platforms only.

If these bands are chosen carefully with regard to their

spectral allocation, they may provide much specific information on terrain features. Of course, the general advantage of scanners, which is the provision of quantitative data on reflectance or emittance, is valid for arrborne as well as for satellite scanning. For the principles of airborne line-scanning, the reader is referred to par. 4 . 3 and to Lowe ( 1 9 7 5 ) .

Imagery from airborne line-scanners is briefly

discussed in par. 6 . 4 , the processing of digital data in par. 5.2-5.4.

10.1. Airborne line-scanners

The airborne line-scanners operating in the Visible and Infrared may be divided into (Higham e.a., a)

1973):

monospectral line scanners, which are generally modifications of military hardware; they usually operate in the Infrared region of the spectrum and many are uncalibrated systems suitable for qualitative sensing only; integral film recorders are usually present, which are not suitable for subsequent automatic data processing; uncalibrated systems are a.0.

EM1

Airscan, HSD Linescan, Texas Instruments RS 310, De Oude Delft Linescan and Reconofax; systems with black body reference are the Bendix TM/LN 3 and TI RS 18; b)

modified monospectral line scanners to obtain at least one additlonal channel; this is usually achieved by the insertion in some part of the

241

optical system of a dichroic mirror to split the beam into two spectral regions e.g.

Daedalus DS 1220/30, Texas Instruments RS 14,

SAT Super

Cyclops; c)

multispectral line scanners with limited spectral selection generally in the Visible through the use of an integrated array of silicon photodiodes e.g.

Daedalus with DS-1250

(analog) and DS-1260 (digital) scanners, and

Bendix M2S; this type of system may also be extended into the Infrared by the addition of a so-called dichroic mirror; d)

multispectral line scanners with full selection capability over the whole Visible and Infrared region of the spectrum; this is obtained in the Bendix

MSDS

by

using

dichroic

mirrors

and

two

separate

grating

spectrometers for the Visible and Infrared. A s an illustration of (c),

the channels of the DS-1260

spectrometer are given

below: 1. 2. 3.

0.38-0.42 0.42-0.45 0.45-0.50

pm um pm

4. 5. 6.

0.50-0.55

urn

0.55-0.60

prn

0.60-0.65

UIII

7. 8. 9. 10.

0.65-0.69 0.70-0.79 0.80-0.89 0.92-1.10

& .I!

~rm

pm

In the example, the channels have a bandwidth of 50 nm for the central wavelength range (channels 3 up to 6 ) . The Bendix MSDS (d) differs from the DS1260 in covering a wider spectral range, being part of the UV, the Visible as

well as the Infrared up to 1 3 um. The Bendix MSDS 24 channel allocation is detailed below: Channel Number 1 2 3 4 5 6 7 8 9 10 11 12

Bandwidth (micrometers) 0.34 - 0.4 0.4 - 0.44 0.46 - 0.5 0.53 - 0.57 0.57 - 0.63 0.64 - 0.68 0.71 - 0.75 0.76 - 0.80 0.82 - 0.87 0.97 - 1.05 1.18 - 1.30 1.52 - 1.73

Channel Number

Bandwidth (micrometers)

13 14 15 16 17 18 19 20 21 22 23 24

2.1 - 2.36 3.54 - 4.0 4.5 - 4.75 6.0 - 7.0 8.3 - 8.8 8.8 - 9.3 9.3 - 9.8 10.1 - 11.0 11.0 - 12.0 12.0 - 13.0 1.12 - 1.16 1.05 - 1.09

248

The Bendix MSDS has been developed for research and is not available on the market.

The most advanced system on today's market is the Daedalus eleven

channel multispectral scanner DS-1268,

also known as the Airborne Thematic

It was developed in 1981 as a modification of the DS-1260.

Mapper (ATM).

The

system covers the bands used by the Landsat 4 Thematic Mapper, the Landsat 3

MSS and the SPOT System: wavelength um

channel

channel wavelength vm

1.

0.42 -0.45

7.

0.76-0.90

2.

0.45

-0.52

8.

0.91-1.05

3.

0.52 -0.60

9.

1.55-1.75

4.

0.605-0.625

10.

2.08-2.35

5.

0.63 -0.69

11.

8.50- 1 3 .OO

6.

0.695-0.75

10.2.

Detection in the Ultraviolet 10

About

percent

of

the

solar EMR

that

is incident on the earth's

atmosphere is in the Ultraviolet portion of the EMS. The atmosphere strongly attenuates the Ultraviolet at wavelengths shorter than 0 .2 8 urn, primarily due to Rayleigh scattering and absorption by ozone and molecular oxygen. Optical mechanical scanners using mirrors made of aluminum o r of silver metal films (Halter, 1973),

UV filters and UV sensitive detectors produce imagery of fair

quality. An example is the Daedalus DEI-238 UV-Visible detector. The low intensity of Ultraviolet radiation incident at the earth's surface and the

strong

atmospheric

influence

cause

the

information

content

of

the

Ultraviolet to be low when compared with that of the Visible and the Infrared. However, despite these limitations, some targets exhibit contrasts in the Ultraviolet that may be more useful than those obtained in other regions. In the near

Ultraviolet (read near

to Visible o r

wavelength region of the Visible spectrum (blue),

0.3-0.4

pm)

and

the short

the carbonates, phosphates

and evaporites are usually more reflective than other rock materials. Acidic rocks, such as granite and rhyolite, show little reflection in the Ultraviolet but considerable reflection in the Visible, while basic rocks such as basalt show little reflection in both regions (Cronin et al., 1973). Data are also available ahout the penetration of Ultraviolet radiation in soil materials. Coarse textured (dry)

Soil materials show deeper penetration than

249

fine textured (dry) soil materials (Cronin et al., 1973). 10.3. Detection in the Visible zone and near Infrared In chapter 3 the interaction of solar radiation with minerals, rocks, soils and plants is discussed. In summary, the following is stated about reflectance of soils and plants. Soils:

-

the general pattern reveals an increasing reflectance from 0.5 l m ~ to 2.5 um ; contrast between soils may be obtained in the 0.4-0.5

0.6-0.7

-

um and 1.7-2.5

um the

um regions;

increase of organic matter content and moisture content result in decreasing reflectance over broad spectral regions;

-

information about iron content may be obtained from a broad band at 1.1

urn, and weak bands at

0.87

!im

and in the Visible;

- H20 is indicated by bands at 1.4

~.lm and

1.9 um; OH-

by a band at

2.2 pm;

-

carbonate and gypsum are indicated by bands between 1.7 m and 2.5

um

(strong absorption due to the presence of Cog" at 2.35 m; gypsum shows a band at 1.75 pm). The

so-called

artificial

H20

bands

illumination

are

in

the

applicable

for moisture

laboratory.

Under

determination with

natural

conditions

the

radiation at 1.4 um and 1.9 pm is absorbed by atmospheric H20, which makes their application in remote sensing complicated. Plants:

-

reflection in 0.55 pm band and of near Infrared radiation; absorption in 0.44 um and 0.66 wn bands; damage

affecting

morphology

results

reflectance especially of near

in

a

decrease

of

overall

h f rared; a change in physiology

involves a shift of the green peak towards yellow wavelengths; a final change results in a shift towards red wavelengths. Besides by the reflectance characteristics of the materials, the choice of channels in remote sensing has to be directed by the wavelength regions as indicated by the major atmospheric windows (given by Lintz and Simonett, 1976). These are:

250 0.40-0.75

um

1.19-1.34

pm

0.77-0.91 1.00-1.12

um

1.55-1.75

pm

pm

2.05-2.40

pm

From the information given above, the following optimum channels for airborne scanning in detection of soils and plants are suggested (Mulders, 1986) :

information content

allocation hands in pm 0.5 3-0.58

green reflectance of plants

0.58-0.63

yellow reflectance of soils and plants

0.6 3-0.68

red absorptance by plants, contrast in

0.84-0.90

maximum NIR reflectance of plants, iron

soil reflectances content of soils 1.20- 1.30

reference value plants

1.60-1.68

reference value soils

1.72-1.78 2.10-2.25

gypsum layer silicates

2.32-2.38

carbonate.

Airborne scanning, using the suggested channels, will provide optimum contrast between soils and plants as well as between different soils and canopy types. However, there is no general agreement about the choice of channels. Tucker (1976)

found in his study on the reflectance of blue grama grass, the

spectral regions of 0.37-0.50, significant both early and

0.63-0.69

and 0.75-0.80

pm to be statistically

late in the growing season. Of these spectral

regions, only the second is given above in the selection on channels. Much agreement is found with the work of Bunnik (1978),

who considered the

influence of changing canopy morphology, and the effect of a dry o r moist bounding soil, for optimum selection of spectral bands to discriminate between different green plant canopies. He proposed four spectral bands with centre wavelength positions at 550,

670,

870 and 1650 nm. The optimum selection is

based on the determination of maximum between class separation in the feature space, defined by a minimum number of spectral bands selected within the available atmospheric windows.

251 Present scanning systems are not directed in their choice of channels as suggested above

OK

do show only part of these channels. Further testing of the

informative value of the suggested channels is necessary, especially in the near Infrared 1.72-178

>

urn and

1.60 pm, since only few data are available (e.g. 2.32-2.38

pm).

Besides bands at 0.45-0.50

n .!n

the bands

and 0.85-0.95

wn,

the 2.2 um band was pointed out to be valuable for the inventory of hydrothermally altered rocks (Rowan et al., 1977). Abrams et al.,

(1977)

used data of the Rendix scanner for the delineation of

altered rocks. The following ratios were used: expressed in channel numbers, or 1.6/2.2, in approximate centers of channels in

12/13,

1.6/0.48

12/3

and 0.6/1.0

and 5/10 when when expressed

um.

The dynamics of soil moisture have to be evaluated in determining the soil potential in rainfed agriculture. For this purpose, multitemporal reflectance data may be used effectively. Mc Culloch et al., (1975) considered the use of changes in reflectance of soil-vegetation units to detect changes in soil moisture more promising than thermal scanning, though the relationship would have to be derived for a large number of combinations. Both clay and sandy soils show a large decrease in reflectance over the 0.5-2.6

wn

region at

increasing moisture content (see Johannsen, 1969). Apart from application in the field of soil moisture mapping, airborne MSS has also been used for distinguishing freshly tilled soil from crusted surface soil. The surface roughness can be evaluated from reflectance data taken under different angles of illumination (e.g. different times of day). Furthermore, airborne Multispectral Scanning (MSS) has been used to examine soils with a moderate content of organic matter. For this purpose, Roth and Baumgardner

(1971)

studied a

soil test

area of

approximately 45

ha

in

Tippecanoe County (Indiana), lying in a transitional zone between Alfisols and Mollisols. They found a high correlation between multispectral response with the content of

organic matter

in the upper cm of soil. Since automated

processing is of great importance in the study of MSS data, the method used by Roth and Baumgardner is discussed as an example. In their study, the size of the training set for computer implemented analysis of multispectral data had an important effect on the correlation. A high rate of digitization gave much greater correlation coefficient values than does a low rate of digitization. Furthermore, the selection and number of channels had a profound influence. In stepwise regression analysis, the charnlel 0.66-0.72

252

was

the single best channel for predicting organic matter content in all

training set sizes, except for the single remote sensing unit ( R S U ) . channels

0.40-0.44

urn and

0.50-0.52

Dm

were

also

generally

high

in

The the

selection of the best two or three channels. Some details of the method are given below. Sampling:

the field was gridded at intervals of 46 m; at each grid-point a 1 kg surface soil sample was taken at a depth of up to 1 cm; the

organic matter content was determined by a modified Walkley Black method. MSS data: May 6, 1 9 7 0 , altitude 1 0 0 0 m; 6 channels in the 0.40-1.00 wn range; RSU approximately 9 m2. Low digitization rate (LDR): every eighth scan line was digitized at the rate of 220 samples per scan line. High digitization rate (HDR): every third scan line was digitized at the rate of 440 samples per scan line. Size of training sets: 1 , 4 , 9, 2 5 , 6 4 , 100 and 144 RSU; the 25 RSU training set size produced maximum correlation with LDR data. The channels pointed out for predicting organic matter should be further tested for their value in other soil conditions. The correlation may be negative. That is, the absence of organic matter may be indicated by a high reflectance in a particular channel due to the absence of masking of soil material with specific properties. In that case, high content of organic matter would produce a low reflectance in that channel. Generally, reflectance data indicate the presence or absence of particular soil materials rather than the absolute contents of those materials. This will be due to the effect of the type of the materials e.g. fine textured accumulations. coatings

on

the

mineral

mineral grains or very

For example, iron or lime may be present as

grains

and

exert

a

stronger

influence on

the

reflectance values than would be expected from their real contents. On the contrary

from

uncoated

mineral

occurrences,

high

correlations

between

reflectance values and contents may be produced. Finally, attention is drawn to the research need for:

-

the study of the soil reflection model;

-

polarization techniques in discrimination between dry and moist soil

-

back and forward scattering zones (see par.

surfaces; 2.6

and par.

3.2),

for

example at the outer sides of large angle fields of view in airborne

253

scanning for discrimination of highly absorbent and highly reflectant features. 10.4.

Detection in the mid Infrared The mid Infrared shows two atmospheric windows which enable remote sensing

(Fig. 2 . 1 2 ) ,

these being: 3.4-4.1

and 4.5-5.2

um.

The information potential of these bands (Tables 2.3 and 2.4) is as follows: bands

information potential

(pm)

3.4-4.1

C-H, C - H 2 ,

C-H3 (organic matter)

4.5-5.2

oxides, S i - 0 bending

The value of these bands for remote sensing has to be tested in future (Mulders et al., 1 9 8 6 ) .

10.5.

Conclusions Line

scanners

may

be

distinguished

roughly

into

monospectral

and

multispectral line scanners. The information content of the Ultraviolet window is low when compared with ,the Visible and Infrared. However, some targets such as carbonates, phosphates and evaporites exhibit higher reflectances in the Ultraviolet than in the Visible. A number of channels can be selected on the basis of spectral properties of soils and plants as well as on the allocation of the atmospheric windows. Application of airborne MSS in soil survey is found in acquisition of spectral signatures of soil surfaces and in discrimination of moist and dry soil surfaces. It is especially in arid and semi-arid regions where the soil is barely covered that airborne MSS is expected to be of great value for soil survey when applied in combination with

airphoto-interpretation. In other

regions, MSS may give much information about soil conditions at the time that there are large areas of bare soil (e.g.

extensive cotton or grain fields out

of the growing season). Much research is necessary to explore the high potential information content of airborne MSS. The results may be used for inventory and monitoring of the environment at a large scale, as well as for the improvement of satellite MSS techniques.

254

10.6.

References

Abrams, M.J., Ashley, R.P., Rowan, L.C., Goetz, A.F.H. and Kahle, A.B., 1977. Use of Imaging in the 0.46-2.36 um Spectral Region for Alteration Mapping in the Cuprite Mining District, Nevada. U.S. Geol. Survey. Open-file Report 77-585. Bunnik, N.J.J., 1978. The Multispectral Reflectance of shortwave Radiation by Agricultural Crops in Relation with their Morphological and Optical Properties. Thesis Agricultural University, Wageningen, The Netherlands: 176 pp. Cronin, J.F., Rooney, T.P. e.a., 1973. Ultraviolet Radiation and the Terrestrial Surface. In the Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz), Houghton Mifflin Cy, Boston: pp. 67-77. Higham, A.C., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning System and their potential Application to Earth Resources Surveys. Basic Physics & Technology, ESRO CR-231: 186 pp. Holter, M.R., 1973. Ultraviolet Imaging. In the Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz), Houghton Mifflin Cy, Boston: pp. 78-82. Johannsen, C.J., 1969. The detection of available s o i l moisture by remote sensing techniques. Ph.D. Thesis, Purdue University: 266 pp. Lintz, J.Jr and Simonett, D.S., 1976. Remote Sensing of Environment. AddisonWesley Publ. Cy, Reading, Massachusetts: 694 pp. Lowe, D.S., 1975. Imaging and Nonimaging Sensors. Chapter 8 i n Manual of Remote Sensing. her. SOC. of Photogrammetry, Falls Church, Virginia: pp. 367397. Mc Culloch, J.S.G., Painter, R.B., 1975. Application of Multispectral Scanning Systems to Hydrology. In ESRO CR-234, Plessey, United Kingdom: pp. 127149. Mulders, M.A., 1986. Band Selection in Multispectral Scanning for S o i l Survey of Arid Zones. Proc. ISSS hth intern. Symposium Remote Sensing for soil Survey. March 1985 (Wageningen, Enschede). ITC Journal, Enschede, The Netherlands. Mulders, M.A., Schurer, K., Jong, A.N. de, Hoop, D. de, 1986. Selection of Bands for a newly developed Multispectral Airborne Reference-aided Calibrated Scanner (MARCS). Proc. ISPRS Congress August 1986, Enschede, The Netherlands; pp. 301-303. Roth, C.B. and Baumgardner, M.F., 1971. Correlation Studies with Ground Truth and Multispectral Data: Effect of Size of Training Field. 7th Symposium Remote Sensing Michigan: 12 pp. 1977. Discrimination of Rowan, L.C., Goetz, A.F.H. and Ashley, R.P., Hydrothermally Altered and Unaltered Rocks i n Visible and Near Infrared Multispectral Images. Geophysics, Vol. 42, No 3: pp. 522-535. Tucker, C.J., 1976. Sensor Design for Monitoring Vegetation Canopies. Photogrammetric Engineering and Remote Sensing, Vol 42, No. 11: pp. 13991410.

10.7. Additional reading Heide, G. van der and Koolen, A.J., 1980. Soil Surface Albedo and Multispectral Reflectance of short-wave Radiation at a Function of Degree of Soil Slaking. Neth. J. Agric. Sci 28: pp. 252-258. LARS, 1968. Remote Multispectral Sensing i n Agriculture. Annual Report Vol. no. 3. Laboratory for Agricultural Remote Sensing (LARS). Purdue Univ.,

255

Indiana: 175 pp. LARS, 1970. Item Annual Report, Vol. no. 4: 112 pp. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. Polcyn, F.C., Spansail, N.A. and Mulida, W.A., 1973. How Multispectral Sensing can help the Ecologist. In The Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz). Houghton Mifflin Cy, Boston: pp. 349-359. Sabins, F.F. Jr, 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Francisco: 426 pp. 1975. An Approach to the Evaluation of Multispectral Scanning Savigear, R.A.G., Systems. In ESRO CR-234, Plessey, United Kingdom: pp. 7-50.

256 11.

REMOTE SENSING FROM SPACE IN THE 0.3

-

3.0

um

ZONE

Satellite imagery is freqoently used in extensive surveys. The cost of the standard products (e.g.

from Landsat) are low in relation to the benefit that

can be obtained from the synoptic view, since a large area is covered at one time under uniform atmospheric conditions. The multitemporal potential forms another advantage. Below, as an introduction, different space missions are discussed (par. 11.1).

For practical purposes, the discussion on technical aspects (par. 11.2-

11.3)

and

interpretation methodology

products ( par. used

11.4)

focuses on

first generation Landsat

and Thematic Mapper (par 11.5),

in earth resources surveys.

which are most widely

Finally, the application (par.

11.6)

is

commented on.

11.1. Manned space missions and unmanned satellites

For specifications on a number of satellites, the reader is referred to par.

4.4.

Below in table 11.1,

a summary is given on manned missions and

satellites. It should be noted, that the sensors often cover a spectral region Table 11.1

A selection on NASA and ESA space missions important for remote sensing of earth resources.

space missions Nimbus program Tiros program Mercury MA-4 Gemini IV Apollo-15 Apollo-16 ERTS or Landsat Skylab ATS SMSIGOES Tiros-N/NOAA HCMMIAEM Seasat 1 Space shuttle

year of (first) launching 1958 1960 1961 1965 1971 1972 1972 1973 1974 1974 1978 1978 1978 1981

manned design life or actual life (a) spacecraft

-

+ + + + + -

+

1 3 3 2

year (Nimbus D) months (1973 end of program) days weeks about 2 weeks about 2 weeks 1 year 28-84 days per visit 1 year 3 years 6 months 1978-1980 (a) 106 days (a) extended life

Note: Since 1973, also data of the so-called Defense Meteorological Satellite (DMSP) are available.

251

much wider than the 0.3-3.0

m region, but we regard the summary to be of value

at this place in the text. The use of Mercury photographs for geological mapping dates back to 1963. Other early spaceborne materials used for the study of megatectonical aspects and regional geology are Gemini photographs (van der Meer Mohr, 1968). The Nimbus Meteorological Satellite Program demonstrated the potential of repetitive coverage in space imaging for Earth Resources Surveys. The Nimbus program and the high resolution photography of Gemini and Apollo gave an impetus to the Earth Resources Technology Satellite (ERTS) program, now denoted Landsat. The Skylab program was a follow-up to the Mercury, Gemini and Apollo manned space missions. The orbital altitude of Skylab was 432 km and the orbit had an inclination of 50' the earth's

surface.

to the equator. The imaging was feasible for 75 X of

The emphasis of

the Skylab program was the use of

precisely developed technology of manned spaceflights for advanced study in physics, astronomy and monitoring of the earth's surface (Otterman e.a.,

1976).

A number of sensors was mounted for this purpose in Skylab, including a multispectral

camera

cluster,

an

Infrared

spectrometer,

a

13

channel

multispectral scanner and Microwave systems (see table 11.2). Skylab can be regarded as a step in the development towards the Space Shuttle.

The

Space Shuttle is a manned

spacecraft that carries a space

hbOKatOKy into orbit throughout experimental missions. At the end of each mission, the orbiter makes runway landings similar to those made by aircraft. The so-called Spacelab is a European space laboratory for application in the Space Shuttle missions. The purpose of Spacelab is to provide a ready access to space for a broad spectrum of experimenters in many fields and from many countries (Barrett and Curtis, 1982). Spacelab can act as a bridge between ground or airborne measurements, and long life automatic satellites. The first payload consisted of a high resolution aerial mapping camera and an active radar system (9.65 chapter 13).

GHz band; X-band see

The second payload of the Space Shuttle (flight 1981) contained

the SMIRR or Shuttle Multispectral Infrared Radiometer, which acquired the first narrow-band spectral data from orbit (pixel diametre

=

centers of the SMIRR spectral bands are as follows in ~nn : 0.60, 1.50, 2.4

1.60,

2.10,

2.17,

2.20,

2.22,

2.35.

100 m). 1.05,

The 1.20,

In particular the region 2.0

to

pm appeared to have potential for the identification of COfl and OH'-

bearing minerals such as layer silicates (Goetz et al., 1982).

258

Table 11.2.

Skylab sensors after BaKKett and Curtis (1976).

Type of sensor

S-190

Multispectral camera cluster no. no.

no. no. no.

no. S-191

Spectral sensitivity range

Type of film: 500-600 600-700 700-800 800-900 500-880 400-700

1 2 3 4 5 6

Infrared specrometer

Comments

nm nm nm nm

B&W: Panatomic-X B&W: Panatomic-X B&W: IR Aerographic R&W: IR Aerographic blOUK: IR Aerochrome COlOUK: S0-242*

nm

nm

0.4-2.4 pm and 6-16 um

Spectral resolution 2 ~ 1 0 - pm ~ to 2 . 5 ~ 10-1 um (lower at longer wavelength)

5-192

Multispectral Scanner channel 1 channel 2 channel 3 channel 4 channel 5 channel 6 channel 7 channel 8 channel 9 channel 10 channel 11 channel 12 channel 13

410-460 460-510 520-556 565-609 620-670 680-762 783-880 980-1080 1.09-1.19 1.20-1.30 1.55-1.75 2.10-2.35 10.2-12.5

nm

nm nm nm nm

nm nm nm pm pm

pm

pm pm

S-193

Microwave system (passive + active): radiometer, scatterometer, altimeter

13.8-14.0

GHz

S-194

L-band microwave radiometer

1.4-1.427

GHZ

*

Centre frequency of 1.4134 GHz: bandwidth 27 MHz

Kodak Film with high resolution at low contrast.

11.2.

Technical aspects Landsat The technical aspects of Landsat are dealt with in the Landsat Data Users

Handbooks (NASA, 1972,

1976;

US Geol. Survey, 1979).

Below some important

technical aspects are summarized. The Landsat program has been designated as a research and development tool

259

to demonstrate that remote sensing from space is a feasible and practical approach to efficient management of the earth's resources. Landsat provides the repetitive acquisition of multispectral data of the earth's surface on a global base. Two sensor systems have been selected for Landsat 1 and 2: a four channel multispectral scanner (MSS) for Landsat 1 (five channels for Landsat 2),

and a

three camera return beam vidicon (RBV). The RBV

camera

system of

Landsat

1

and

2

operated by

shuttering three

independent cameras simultaneously, each sensing a different spectral band in the range of 0.48 to 0.83 1)

0.475-0.575

pm ;

2)

0.580-0.680

pm ;

3)

0.690-0.830

um

The MSS

um

. The spectral bands are respectively:

.

is a

line scanning device which uses a mirror that scans

perpendicular to the track of the spacecraft as is shown in fig. 11.1. MSS scanning arrangement

+ 2 f o r band

(landsat-3) F i e l d o f view =

South

East D i r e c t i on of flight

- L i n e s scan-bands 4-7 - L i n e s scan-band 8

Fig. 11.1 Operation of the Landsat multispectral scanner after Short (1982).

Six lines with the same bandpass are scanned simultaneously in each of the four spectral bands for each mirror sweep. The spacecraft's motion causes the alongtrack progression of the six scanning lines. The electromagnetic energy is

260

sensed simultaneously by an array of detectors in the four spectral bands in the range of 0.5 to 1.1 pm

.

The spectral bands are respectively: 4)

0.5-0.6

pm ;

6)

0.7-0.8

pm

5)

0.6-0.7

pm ;

7)

0.8-1.1

pm

A band in the thermal Infrared from 10.4-12.6

is included in Landsat 2

pm

(band 8 ) . The MSS data are radiometrically and geometrically calibrated. The detector

outputs are sampled, encoded into six bits and formatted into a continuous data stream of 15 megabits per second. The continuous StKip imagery is transformed later

on

into

framed

images with a

10

percent

forward overlap of

the

consecutive frames. Landsat (1,

2 OK

3)

operates in a circular sun-synchronous near-polar

orbit at an altitude of 912-920 km. It circles the earth every 103 minutes, completing 14 orbits daily, and views the entire earth every 18 days, thus fixing the repetitive coverage. A typical Landsat daily ground trace is given

in fig. 11.2.

Note that due to the rotation of the earth in eastward direction,

the ground track progresses in westward direction. The sun-synchronous orbit refers to the geometric relationship between the

orbit's

descending node (south bound equatorial crossing) and the mean sun's

projection into the equatorial plane. Since the orbit plane rotates at the same rate as the mean rate of the earth about the sun, this relation is constant. In other words, the angle between the orbit plane and the line that connects the earth's centre with the sun's centre remains constant (being 37.5"). For Landsat 1 and 2 the mean sun time at descending mode was established between 9:30

and

1O:OO

a.m.

The actual mean sun time at descending node

achieved for Landsat 1 was 9:42 a.m.

and that for Landsat 2 was 9:32 a.m. The

local time is determined by discrete time zones. The image sidelap OK lateral overlap of adjacent tracks amounts 14 percent

at the equator, but increases to 85 percent at 80'

latitude. The image sidelap

at different latitudes is given in table 11.3. The overlap (e.g.

30 X )

provides stereoscopic coverage in terrain with height

differences larger than 100 metres (Hilwig, 1979). The x

185.2

CKOSS

track optical scan of Landsat 1-3 is 185.2 km. To obtain a 185.2

km scene, 390 spacecraft mirror scans (performed in 25 seconds) are

required. The nominal instantaneous field of view (IFOV) of each detector in bands 4 up to 7 is 79 meters square. Since the next sample overlaps the

261

Fig.

11.2Typical Landsat daily ground trace, showing local time variations within an orbit (after US Geological Survey, 1979).

foregoing sample by 23 metres, the effective IFOV of a detector in the cross track direction must be considered to be 56 meters. Therefore, the picture element or pixel has a nominal area of 56 x 79 meters (at nadir point). The first three Landsats had the same basic 4 band sensor package. Besides this package, Landsat 4 additionally contains the so-called Thematic Mapper (TM) The TM operates in seven spectral bands with the following spectral ranges: 1)

0.45-0.52

urn

5)

1.55-1.75

2)

0.52-0.60

urn

6)

10.40-12.50

3)

0.63-0.69

um

7)

2.08-2.35

4)

0.76-0.90

um

um um

um

262 T a b l e 11.3 S i d e l a p of a d j a c e n t Landsat 1-3 c o v e r a g e swaths a f t e r N A S A (1976). Latitude (degrees)

Image S i d e l a p ( X )

0 10 20 30 40 50 60 70 80

14.0 15.4 19.1 25.6 34.1 44.8 57.0 70 .6 85.0

~~~~~

~

~~

Both r a d i o m e t r i c s e n s i t i v i t y and s p a t i a l r e s o l u t i o n a r e improved i n t h e TM, t h e Band 6,

l a t t e r b e i n g 30 m f o r bands 1-5 and 7.

t h e t h e r m a l band, a c h i e v e s a

p i x e l s i z e of 120 m on t h e ground. Landsat 4 h a s a sun-synchronous n e a r - p o l a r 705 km o v e r t h e e q u a t o r . 9:45 a.m.

o r b i t a t a nominal a l t i t u d e of

The s a t e l l i t e c r o s s e s t h e e q u a t o r a t a p p r o x i m a t e l y

on e a c h p a s s . Each o r b i t t a k e s n e a r l y 99 minutes and t h e s p a c e c r a f t

w i l l complete j u s t o v e r 144 o r b i t s p e r day c o v e r i n g t h e e a r t h e v e r y 16 days.

The lower o r b i t of Landsat 4, n e c e s s a r y f o r t h e 30 m ground r e s o l u t i o n of t h e

TM,

results

i n a n e a r t h coverage

Landsats (NASA,

c y c l e d i f f e r e n t from t h a t

of

the e a r l i e r

1982).

In t h e e a r l y

orbits

of

Landsat

1,

the

RBV

system g e n e r a t e d

d a t a of

e x c e l l e n t q u a l i t y . However, a s a r e s u l t of a c i r c u i t f a i l u r e w i t h i n weeks a f t e r l a u n c h , t h e RBV system c e a s e d t o f u n c t i o n . The RRV on Landsat-2 is i n working o r d e r , b u t i s o p e r a t e d p r i m a r i l y f o r equipment t e s t i n g p u r p o s e s and i s b e i n g held i n reserve for possihle special

emergence u s e ( N a t i o n a l Academy of

OK

S c i e n c e s , 1977). The Landsat

3 RBV

system c o n s i s t s of

imaging a n a r e a a p p r o x i m a t e l y one-fourth spectral

band

0.505-0.750

!im

is

two RRV cameras,

each c a p a b l e of

t h e s i z e of a n HSS scene. One broad

covered

by

the

RBV

system.

The

ground

r e s o l u t i o n of t h e RBV imagery i s c o n s i d e r a b l y S h a r p e r ( 3 8 by 38 m) t h a n t h a t of t h e MSS. This a d v a n t a g e of RBV d a t a does n o t d i m i n i s h t h e v a l u e of t h e b e t t e r s p e c t r a l i n f o r m a t i o n of MSS d a t a . used i n combination ( N A S A ,

Good r e s u l t s may be o b t a i n e d when both a r e

1979, Landsat Data Users Note No 5).

A s may be e v i d e n t from t h e f o r e g o i n g ,

failures.

However,

it

problems may o c c u r due t o c i r c u i t

i s a l s o p o s s i b l e t h a t t h e a c t u a l l i f e t i m e of a system

263

extends the lifetime expected. It is therefore necessary to indicate the status of the satellite systems. The status of the Landsat series is summarized below (see NOAA, 1983, for Landsat 3 and 4): Landsat 1 July 22, 1972fJanuary 6 , 1978; RBV failure within 2 weeks; Landsat 2 January 22, 1975f.January 22, 1980; reactivated June 6 , 1980; Landsat 3March 5, 1978/September 30, 1983; thermal band failed August 11, 1978; MSS line start problem mid 1978; RBV is working nominally; Landsat 4 July 29, 1982; failure of X-band transmitter February, 5, 1983; data relay

system

operational

on

limited

basis

end

1983;

final

verification of the Thematic Mapper ground processing system January, 1985; Landsat 5 March 1, 1984; MSS and TM operational. There is a global notation system for Landsat data. A nominal scene centre may be designated by path and row number. The path number refers to

one

of the

nominal tracks. The row number refers to the latitudinal centre line of a frame of imagery.The following photographic products are available:

-

system

corrected

images, comprising radiometric and .initial spatial

correction;

-

scene

corrected

images,

additionally

containing

transformation into

Universal Transverse Mercator or Polar Stereographic coordinates. A 15-step grey scale tablet is exposed on every frame of imagery, which is related to the energy incident on the sensor. The grey tones cannot be used reliably for microscale radiometry, because the areas in the order of a few pixels are subject to influence by neighbouring areas and do not supply enough data power to average the noise down to a low figure. Digital data are available in the form of Computer Compatible Tapes (CCT), These tapes are standard half-inch wide magnetic tapes and are supplied in 9track or 7-track format.

For an optimum choice of MSS imagery and CCT there are three requirements: a)

information about availability, which can be obtained by a query for computer

search

and/or

microfilm

images;

the

requisites

involve

coordinates, required image quality and maximum cloud cover; microfilm images are useful to locate the cloud cover; b)

evaluation of meteorological data such as temperature, precipitation and evapotranspiration diagrams (fig. 11.4);

264

c)

evaluation of agricultural data by means of a crop calendar (fig. 11.5). and data about the development of natural vegetation. Inquiry forms for geographic computer search and order forms for Landsat

standard products are available at the Eros Data Center, Sioux Falls, USA. The price of 18.5 cm negative or positive Landsat MSS imagery is relatively low and CCT's are available at a reasonable price (US EOSAT: pricelists). For a detailed discussion on the selection of Landsat MSS data, the reader is referred to Hilwig (1979). To guarantee the satellite data flow, the quality of

the data, and to

provide aid and information, ground station networks as well as distribution networks must be available. The approximate receiving ranges of operating and proposed Landsat ground stations are shown in fig. 11.3.

The European stations

for Landsat data are located at Fucino (Italy) and Koruna (Sweden). The so-called Earthnet, set up by ESA for reception and distribution of satellite data in Europe, became operational in 1978 and includes two other stations: Lannion (France) for reception of HCMR and Nimbus 7 data (Nimbus 7 was launched at 2 4 / 1 0 / 7 8 ) ,

and Maspalomas (Canary Islands) for Nimbus 7 data

only. The Earthnet programme office is located in Frascati (Italy).

Data distribution

relies on this office and on a network of national points of contact. Recent satellite data have to be ordered through these national contacts. 11.3.

Annotations Landsat MSS imagery The data on Landsat photographic products as given by NASA (1972)

are

summarized below. For examples on Landsat imagery, the reader is referred to fig. 6.5 and par. 11.4. From each 55.8 1:1,000,000)

mm image (scale 1:3,369,000),

an enlargement to 18.5 cm (scale

is available.

Four registration marks are placed beyond the image corners to facilitate alignment of different spectral images of the same scene from the same payload sensor. The intersection of diagonals drawn through the four registration marks is the format centre of the image. Latitude and longitude tick marks are placed outside the edge of the image at intervals of 30 arc minutes. At latitudes above 60 degrees north or south, tick marks are spaced at one degree intervals.

265

120'

80'

40'

40'

O0

120'

80'

NASA HO ~ 1 8 04358 ( 1 ) REV 9580

kote: ;overage circl'es based on lhdsat-'3 reception (altitude: 917 km)

Fig. .11.3 World-wide location of operating or proposed ground stations for reception of data transmitted by Landsat after Short (1982). A 15-step grey scale tablet is exposed at the bottom of every frame of imagery. Above the grey scale tablet an annotation block is shown that contains the following: a)

day, month and year of data acquisition;

b)

latitude and longitude of image format;

c)

item of nadir from spacecraft;

d)

sensor and spectral band;

e) f)

sun elevation angle and sun azimuth angle; codes

for

spacecraft

heading,

orbit

revolution number

and

ground

recording station; g)

codes for size, processing, computation image centre, signal processing

266

prior to transmission and signal gain; h)

agency and project;

i)

frame identification number. The scanning nature of Landsat images appears more and more in the form of

lines upon enlargement. The discrete rectangular pixels as determined by the ground resolution of 56 x 79 metres appear when prints of medium scale are obtained from automated processing (Fig. 11.11).

11.4.

Processing and interpretation of Landsat MSS data The processing of Landsat MSS data may include:

-

photographic processing of negative into positive black- and -white images, the production of diazo materials e.g.

band 4 in yellow, band 5 in magenta

and band 7 in cyan;

-

automated processing of digital data e.g. transform Donker

OK

ratioing and principal component

PCT.

and

Mulder

(1977)

showed for a

test area at Roermond

(The

Netherlands) how PCT can be applied to produce an optimum image for visual interpretation of Landsat data (par.

5.2).

automated processing.

(1975)

Dethier et al.

Several ratios were applied in used the so-called Band Ratio

Parameter (BRP) for comparing the relationship between absorbed and reflected radiation by vegetation: BRF'

=

band

-

band

band 7

+

band 5

, where

band 7 is the intensity of radiation in

band 7 etc. Another ratio, which is often used, is the 715 ratio. Sabins ( 1 9 7 8 )

stresses the advantage of ratio values (ratio 415 Landsat) i n

removing illumination differences between sunlit and shadow areas. Hielkema (1979,

1980)

presented the following general conclusions as an

outcome of his study on Landsat data of desert areas:

-

band 7 appears to be far less sensitive to changes in vegetation cover than band 5;

-

combination of bands 5 and 7 seems to provide the best basis for separation of the abiotic and biotic environment;

261

-

combination of bands 4 and 5 indicates the best prospects for separation of abiotic spectral classes;

-

multitemporal analysis for change detection is hampered by atmospheric conditions changing through time; it is suggested to apply a correction factor obtained by PCT on a representative sample set for each acquisition date; using 715 ratios, the data normalization involves the definition of two new spectral axes in the band 7 against band 5 plot in such a way that the main 715 data axis has an orientation of 45'

and that the main data axis

intersects the spectral axis at the origin; the result is a series of band 715 data clusters of which the main axes have a slope of 4 5 ' ;

-

data sampling techniques have to be used for reducing the total data processing volume of Landsat to perform monitoring activities over large areas at an economic level. Interpretation of multitemporal Landsat imagery may be done by integrating

static and dynamic interpretation aspects. Hilwig ( 1 9 8 0 ) analysed the following interpretation aspects on Landsat imagery of the Dehra Dun region in Northern India: static aspects

-

drainage pattern alignments

dynamic aspects

-

drainage condition vegetation and land use

landform

For analysis of static aspects, the best image has to be selected from a set of images; often a band 5 or 7 image of one date is selected as the best one. However, dynamic aspects have to be studied on multitemporal combinations. Finally, a multitemporal physiographic interpretation map can be composed. Photographic and digital processing produces a set of image products. Each image product may have its specific value for interpretation. Therefore, basic data are needed for a proper selection of imagery with regard to the purpose of the interpretation. The study on small-scale soil and land use mapping of the Calatayud Basin (Prov. Zaragoza, Spain, by Mulders and O'Herne, 1984) is used as an example throughout most of the following text.

The Calatayud Basin is filled in with Miocene sediments, which are composed of gypsum, marl and limestone series in the central part and mainly of

268

Po

mm

250 200 150

50

#

I

10

0

Yearly average temperature Yearly average precipitation Yearly average potential evapotranspiration

... ___ R U D

= = =

Fig.

Ta Pa PEa

= 13.8"C = 431 mm = 704 mm

monthly average temperature ("C) monthly average precipitation (mm) monthly average potential evapotranspiration (PE in mm) recharge utilization deficit 11.4 Climatic data and soil water balance of the Calatayud Basin. (Mulders and O'Herne, 1981). T and P for station Calatayud (19481966); PE for station Zaragoza (Ta = 14.6; T distribution identical to Calatayud) and PE = c.Eo Note:Eo is evaporation of free water surface; c is a factor relating Eo to PE for a crop; it amounts to 0.65 for grassland.

conglomerates, breccies and loams at the fringes of the basin. Climatic data are given in fig. 11.4 and a crop calendar is presented in fig. 11.5. The climatic data and the crop calendar were used in the selection of imagery and digital products (see fig. 11.5).

In this case, average climatic figures

could be used. However, when precipitation is subject to strong variation and thus not reliable, data of the actual precipitation are required for the selection of satellite products. In fig. 11.5, an estimation on the percentage of green vegetation for the different crops is given. This estimation together with the acquisition dates of the satellite products gives insight in the information potential of the remote sensing data. A flow chart is suggested for small-scale soil, land use and natural vegetation

mapping with the aid of Landsat MSS data (table 11.4).

269

% o f cover by green vegetation as function o f time and crops.

Fig. 11.5

Crop calendar for the Calatayud Basin, the selected Landsat images and CCT's (Mulders and O'Herne, 1981). Agricultural activities: manuring M = P = field preparation S = sowing H = harvesting

Landsat products: u - imagery - CCT's

0

The following materials were produced in the study of the Calatayud Basin for a preliminary interpretation: a)

positive black- and -white images of (which may

he

combined to

several acquisition dates

colour comhinations using a

Colour

Additive Viewer) :

b'>

diazo imagery of several acquisition dates (hand 4 in yellow, hand 5 in magenta and hand 7 in cyan to produce false colour composites);

270

Laboratory Work

Processing

c

-

Processing of selected areas

c

C o n t r a s t Enhancement a n d / o r Enlargement i n d i v i d u a l Rand Imagery

Histogram Equali s a t i o n O K scal i n g individual Band Data

4,5,7 OK 6 combinations

4 , 5 , 7 ( O K 6 ) col o u r coded combination + rat i o i n g e.g. 715; P r i n c i p a l Component Transform

-+

+ Mult i t e m p o r a l Combinations e.g. Band 7 a n d / o r 5

c S e l e c t i o n of a r e a s f o r d i g i t a l processing

+

+

d i g i t a l multit e m p o r a l Imagery e.g. 715 01-7-5 7+ 5

271 T a b l e 11.4

continued F u r t h e r Study Photographic Products incl. airphotos

Further data Compress i o n and I n f o r m a t i o n E x t r a c ti o n

c Automated Classification Interpretation

c F i e l d Work

F i n a l Fieldwork and C l a s s i f i c a t i o n

c Desk Work

c)

C a n s t r u c t i o n of S o i l . Land Use and N a t u r a l V e g e t a t i o n Maus

d i a z o imagery of one band of d i f f e r e n t a c q u i s i t i o n d a t e s ( e . g .

band 7 of

J a n u a r y in y e l l o w , of June i n magenta and of September i n cyan t o produce multitemporal colour composites); d)

p o s i t i v e e n l a r g e m e n t s of n e g a t i v e imagery;

e)

CCT d e r i v e d p r o d u c t s a f t e r

-

l e v e l by l e v e l d i s p l a y on a line p r i n t e r o r TV s c r e e n ; h i s t o g r a m e q u a l i s a t i o n f o r enhancement of c o n t r a s t ;

-

combinations of two o r more bands in c o l o u r ,

7 / 5 r a t i o i n g and P r i n c i p a l Component Transform (PCT).

The a u x i l i a r y equipment may be t h e f o l l o w i n g :

-

l i g h t t a b l e and overhead p r o j e c t o r ( f o r a up t o d ) ; c o l o u r a d d i t i v e v i e w e r ( f o r a and d) l i n e p r i n t e r and c o l o u r g r a p h i c s system/TV s c r e e n ( f o r e )

A band 7 image of t h e Calatayud area i s shown i n f i g .

11.6 The Calatayud Basin

h a s a SE-NW o r i e n t a t i o n and i n c l u d e s most of t h e image. The p r e l i m i n a r y v i s u a l i n t e r p r e t a t i o n may comprise t h e f o l l o w i n g :

-

t h e a n a l y s i s of

s t a t i c e l e m e n t s e.g.

o f t e n p o s i t i v e black- and -white

relief,

drainage pattern/density;

imagery i s used f o r t h i s purpose (e.g.

band 5 o r 7 ) ; imagery a c q u i r e d a t low sun a n g l e s i s most s u i t a b l e f o r t h e a n a l y s i s of r e l i e f ;

-

t h e a n a l y s i s of dynamic e l e m e n t s e.g. this

is best

n a t u r a l v e g e t a t i o n and l a n d use;

acquired with multitemporal

colour

composites and f a l s e

c o l o u r composites ( p h o t o g r a p h i c o r d i g i t a l p r o d u c t s ) .

As a n i l l u s t r a t i o n of n o n - d i g i t a l methods, a n example of c o l o u r a n a l y s i s of

272

Fig. 1 1 . 6 . A band 7 image of 30 January 1975 of the Calatayud area (Landsat ID n r 2008-10081).

273

multitemporal diazo colour composites of part of the Landsat frame (see plate 2 for band 5 composite) is given in fig. 11.7. The colour analysis of fig. 11.7 multitemporal combination of band

is done by mutual composition of the that of band 7.

5 with

Besides colour,

pattern is also considered. The multitemporal combination for each of these bands is as follows: January

-

yellow, June - magenta, September

-

cyan (a low % of secondary colour

means a high intensity of reflected radiation) For arrangement of the units, the saturation of the dominant colour of the unit was used in this order: yellow, magenta, cyan. For arrangement within the units, the percent of coverage (from high to low) of the coloured components was used. A first interpretation as aided by the crop calendar (fig. 11.5)

and airphoto-

interpretation gives a good impression of the structure of the data. Some examples are discussed below. Mapping unit C contains mainly young pinus plantations, matoral and erial (low shrubs and grass), furthermore some almonds and grapes. The dominant vegetation (in 60 % of the area) results in a moderate band 7 intensity in January and in low band 7

very

intensities in June and September.

The very low band

7

intensit,ies are due to the low vegetation coverage at those dates. The moderate intensity in January will be due to the growth of matoral and erial at that time

.

Mapping unit G1 shows a dominant vegetation of grapes, unit I mainly contains irrigated fruit trees. Both units have a high reflectance in band 7 in June pointing to a relatively high vegetation cover. Mapping unit M shows very high reflectances in most of the area throughout the year in band 7 as well as in band 5, the latter pointing to an extremely low vegetation cover. The very high reflectances are due to the presence of gypsiferous soils in this unit. A comparison of the Landsat pixel size with the size of parcels that show

different land utilization types, revealed that i n a number of mapping units (e.g. A2s F3, G2, H2, J1 and J2)

it will be very difficult to indicate the type

of vegetation and/or soil surface responsible for the reflection, the size of parcels being equal to or smaller than the ground resolution cell. Also the non-dominant relative intensity figures appeared difficult to translate

214

Fig. 11.7 Colour analysis of multitemporal band 7 and band 5 colour composites of the Calatayud area (for location: see Fig. 11.6). being often a mixture of heterogeneous pixels. The translation was most successful in the mapping units with homogeneous vegetation. Apparently, there is a limit in classification accuracy as related to homogeneity of the landscape. Limitations of the visual COlOUK analysis are the inaccuracies related to the estimation of the colour codes and to the analysis of complicated colour patterns. The best results will be obtained when images of good quality are used, as acquired with reversal film. The study of the multitemporal photographic products and of the images for

analysis of static aspects is used in this stage to select areas for digital processing. Digital processing may be done to get products that are helpful for

275 i n f o r m a t i o n e x t r a c t i o n e.g.

t h e band 7 r a t i o . hand 5

Ry t h i s r a t i o a n i m p r e s s i o n may b e o b t a i n e d o f t h e h i o t i c / a b i o t i c d i s t r i b u t i o n . Fig.

11.8

the

same

p r e s e n t s t h e 7/5 r a t i o p i c t u r e f o r t h e a r e a n e a r Calatayud (approx.

area as

i n fig.

11.7).

The

7/5

image

shows a v e r y

high

contrast

b e t w e e n a r e a s w i t h l o w ( < 20 X) v e g e t a t i o n c o v e r a n d a r e a s w i t h h i g h ( > 6 0 Z ) vegetation fig.

cover;

a p p e a r i n g as w h i t e a r e a s and h l a c k a r e a s ,

respectively,

in

which i s a n e g a t i v e image.

11.8,

W

x 100 r a t i o

(5) + 1 (ratio

picture

displayed

after

histogram

e q u a 1i s a t i o n )

Fig.

The

11.8 R a t i o p i c t u r e o b t a i n e d f r o m MSS d a t a o f 4 S e p t e m b e r 1976 ( I D n r 1-215-031-084). presented

process.

number of

A

colour-coded

is

ratio-picture

poor

of

t h e a r e a n e a r C a l a t a y u d on

q u a l i t y because

of

the

i n t e r a c t i v e systems o f f e r t h e p o s s i b i l i t y

density

sliced

ratio

pictures

on

a

reproduction of

TV-screen.

displaying

In

this

c o n s i d e r a h l e i n f o r m a t i o n on v e g e t a t i o n a n d l a n d u s e c a n h e e x t r a c t e d . radiometric

and

geometric

correction

as

described

hy

nronsveld

way

Using a

and Luderus

a d i g i t a l m u l t i t e m p o r a l image c a n h e p r o c e s s e d w i t h optimum d e t e c t i o n

(1982),

p o t e n t i a l . The f o l l o w i n g r a t i o s may h e u s e d :

hands 7 bands 7

+

Problems then,

and

5 or

5

hands 7 bands 7

+ +

connected with such

products

6 - 5 6 + 5

+

4 4

matching certainly

of

multitemporal

are preferred

diazo above

imagery the

are avoided

visually

matched

276

images discussed above. In addition to the digital multitemporal image, specific questions which are

related

to

the

purpose

of

the

Survey,

landscape

performance

and

agricultural practice, determine the type of other imagery wanted. For example, relief analysis is done preferably on images acquired when the sun angle is low, and soil surface analysis preferably when the vegetation cover is low.

It may be practical to use Principal Component Transform (PCT) to obtain data compression. If performed before the actual fieldwork, the data-points to compose the sample set may be selected at random. On the other hand, the visual interpretation products of Landsat imagery and digital ratio pictures may be used for fieldwork to identify objects, thus enabling the composition of a fieldborne sample set for PCT. The PC1 and PC2, calculated by using the CCT-data of the fieldborne sample set of the Calatayud area, already accounted for 98 to 99 Z of the total variance; this implies that the original four-dimensional data set can be compressed into a two-dimensional one without significant loss of information. The values of PCl and PC2 are: PC1. = PC2

=

+ I4 -

0.33 I4 -0.35

0.53 I5 + 0.62 I6

+

0.46 I7

0.62 I5 + 0.21 I6

+

0.67 I7

PCI is a weighted summation of the four MSS-bands. PC2 strongly depresses the radiation in bands 4 and 5 . These are weighted and subtracted from the weighted summation of bands 6 and 7. The difference between terrain objects which are highly reflectant and those which are low reflectant in the near Infrared is enhanced in this way. The feature plane formed by PCl and PC2 for the data of 4 September 1976 is shown in fig. 11.9. The feature plane formed by the calculated values of PC1 and PC2 of the ground observations on reflectance is presented in fig. 11.10. When comparing the feature plane of the CCT-PC values with the one of the ground observation PC values, there appears to be a rotation over about 20" of the latter with respect to the CCT-set. This will be due mainly to atmospheric influences. According to Hielkerna (1979, 1980), the data can be normalized by defining two new spectral axes. The ground observations on reflectance and the general observations to identify terrain features are both useful for the identification of clusters in the PCIpc2 feature space of the CCT data. A better understanding is obtained a.0. the influence of vegetation cover by grapes on reflectance:

of

211

1

I

I

I

I

I

I

I

I

1

30

40

50

60

70

80

90

100

110

120 PC1

Fig.

F e a t u r e p l a n e of PCI and PC2 of MSS d a t a hth

11.9

Legend: D E F I

= = = =

grapes natural vegetation forest (pine) i r r i g a t e d crops i n fig.

s e e t h e sequence K2-E-D2-D1

September 1976.

K = wheat ( b a r e s o i l ) 0 = orchards T = town Y = n e a r l y b a r e gypsum s o i l s

11.10 where c o v e r by g r a p e s i s i n c r e a s i n g

from l e f t t o r i g h t . Fig.

11.11 p r e s e n t s t h e PC1 and PC2 p i c t u r e s ( o b t a i n e d by l i n e - p r i n t i n g )

CCT of January 1977 f o r p a r t of

of t h e

t h e Calatayud Basin. The i n f l u e n c e of t h e low

s u n a n g l e a t t h e a c q u i s i t i o n d a t a i s c l e a r l y noted i n t h e h i g h c o n t r a s t PC1 image, e s p e c i a l l y i n t h e upper p a r t of t h e image where t h e r e i s a s t r o n g r e l i e f c a u s i n g shadow a r e a s .

I n c o n t r a s t t o t h e PC1 image, t h e PC2 image does n o t show

t h e h i g h c o n t r a s t . However, some f e a t u r e s show up c l e a r l y such as p i n e f o r e s t s and

valleys

with

orchards.

Apparently

the

information

content

is

totally

d i f f e r e n t and ( a s s t a t e d above) one h a s t o choose t h e most a p p r o p r i a t e d a t a a s r e q u i r e d f o r t h e purpose of s t u d y and t h e p h y s i c a l c o n d i t i o n s . PC1 and PC2 may be shown combined through c o l o u r coding ( s e e p l a t e 4). A n a l y s i s of

t h e s e c o l o u r coded PC

imagery

e n a b l e s t h e d e l i n e a t i o n of main l a n d s c a p e

u n i t s and t h e i r c o n t e n t s w i t h r e g a r d t o land use and n a t u r a l v e g e t a t i o n a t t h e

t i m e of a c q u i s i t i o n . The i n f o r m a t i o n c o n t e n t of imagery

of

one

Fig.

acquisition

11.11

date.

i s very s p e c i f i c s i n c e i t concerns PC

Therefore,

the

boundaries

i n d i c a t e d i n t h i s f i g u r e do n o t have t o c o i n c i d e w i t h t h o s e of t h e

that

can

be

278

,----

pc2

I I \,+

(pq 30 1

--

-I

'-.

D1

+

lo+

40

30

50

60

I

I

70

80

-

90

110

120

pc 1

Fig. 11.10 Feature plane of PC1 and PC2 of ground observations on reflectance in September 1979. Legend: D1 D2

= =

E

=

F

=

grapes covering >80% K1 = wheat stubble fields grapes covering 20-80% of soil K 2 = bare s o i l s nat. veg. & grape COV. <20% 0 = orchard, fruittrees forest (pine & Q. ilex) Y = bare gypsum soils

multitemporal analysis of fig. 11.7.

This actually being s o , the main landscape

boundaries can still be delineated although minor deviations do exist. The deviations must draw the attention of the interpreter. In general there is an explanation which is often found in the fields of soil surface, land use and vegetation. A

number of

multitemporal

features can be identified in this stage on the basis of

combination and

knowledge

derived

from

field

observations.

Question marks have to be put at places where uncertainty exists on identification. These places have to be examined in the final field work. The terrain features of the area were also arranged to test automated classification. A method was used that minimizes the variance within cluster with respect to the distances of the objects to the centroids of the clusters. The results for part of the area are shown in a black- and -white coded image (fig. 11.12).

This type of coding is less expensive with regard to reproduc-

tion. However, colour coding provides much more contrast and is therefore superior for interpretation purposes. A number of land features were properly

279

Fig. ll.llPC1 (left) and PC2 (right) pictures ohtained by line-printing for the Calatayud area of Landsat MSS data of 17 January 1977 (ID nr. 2-215031-040). classified, a.0. nearly hare gypsiferous soils, forests and orchards. However, wheat i s only partly classified correctly; remarkable is the classification of the village Munsbrega, which has many white houses, thus resembling a nearly hare gypsum spot. A correct classification in other classes then the three mentioned above is hampered and may even be impossible, since there is a great variation in land use and most fields are small (mean size: 0.6-0.9 ha, that is close to the ground resolution cel), which makes it very difficult to obtain pure pixels for a training set. Therefore, many pixels could be classified only as mixtures of different classes. In this study,'it means that only in those

280

scale app.

0

1

2 km

Fig. 11.12 Automated classification of MSS data of 6 June 1976 of the area near Calatayud, using a clustering method. 8 wheat orchards forests (pine) :: nearly bare gypsiferous soils nat. vegetation 2) nearly bare soils, grapes, nat. vegetation (low coverage) parts of

the area with sufficient uniform land use units, e.g.

the river

valleys and the forested areas, automated classification has been successful. However, multitemporal approaches will certainly improve the classification results. Plate 5 shows the digital classification of this area and its surroundings in colour.

In conclusion, the following can be stated about interpretation methods.

283 The different photographic and digital products each with

their specific

information content have to be studied. The resultant interpretation products should be compared with each other. Converging evidence may present certainty in delineation of mapping units. However, in a number of cases, question marks have to be put on the interpretation maps. These question marks may refer to a complicated physical structure, to limitations of the spatial and spectral resolution of the remote sensor or to the lack of terrain knowledge. The

fieldwork comprises the mapping of key areas, the composition of

sample sets and the checking of different mapping units. Furthermore, special emphasis is laid upon the question marks arisen during the interpretation of photographic products and/or imagery derived from digital processing. With

the

results of

the

fieldwork, and

where

applicable automated

classification, a final interpretation is performed and a small scale map is constructed after field-checking.

11.5.

Interpretation of Thematic Mapper (TM) Data The TM bands are introduced in section 11.2.

was

the

improvement of

The main purpose of the TM

spatial and spectral resolution taking the first

generation Landsat MSS as a small-scale mapping tool with limited spectral potential. The improvement in spatial resolution is easy to see in fig. 11.13,

since dry

gullies and ravines as well as the parcels of arable land are pictured more precisely by the TM. The spectral resolution has been improved by the introduction of relati-

vely narrow bands. Besides the statements made by the U.S. (1982)

Geological Survey

about the information of TM bands for vegetation, rocks and soil mois-

ture, additions can be made with regard to soil mineralogy ( s e e table 11.5). An impression of the structure of

TM data can be achieved by calculating

the correlation coefficients between the different bands, being an appropriate technique for multiband data in general. In table 11.6, this has been done for the bands 1-5 and 7, for two areas in Tunisia..The correlation coefficients of the Seftimi area are lower than those of the Kasserine area, suggesting that more information may be obtained by processing the Seftimi data set. In both areas, the correlation between the first three bands is high, while also band 5 and 7 show a good correlation.

282

Fig. 11.13 TM band 4 image (a) (b) of the Kasserine Acquisition: a) 29th b) 31St

and first generation Landsat MSS band 7 image area (Tunisia: Mulders and Epema, 1985). January 1983 December 1984

Imagery with high information potential may be produced by combination of the bands 5

OK 7,

with band 4 or band 3. Furthermore, highly interesting features

283

Table 11.5.

Spectral properties of TM bands.

TM band nr

Wavelength in um

Information on vegetation, rocks and soil moisture (US. Geol. Survey, 1 9 8 2 )

Information on soil mineralogy by absorption phenomena (Mulders and Epema, 1986)

1

0.45-0.52

iron oxides

2

0.52-0.60

3 4

0.63-0.69 0.76-0.90

5

1.55-1.75

6

10.40-12.50

7

2.08-2.35

differentation of soil from vegetation and deciduous from conifeKOUS flora green reflectance of vegetation chlorophyll absorption determination biomass content, delineation of moist areas vegetation and soil moisture content vegetation stress, soil moisture discrimination of rock types hydrothermal mapping

.

II

II

II

11

I,

I,

gypsum

calcite, gypsum and layer silicates

may be extracted by a display of one band and a one band/total intensity ratio (total intensity 4

+

5

+

7).

=

summation of intensity reflective bands that is 1

+

2

+

3

+

The display of band 5 appeared to be highly sensitive in the

Seftimi area to the classes which were chosen. Gypsiferous areas could be discriminated by

careful selection of

classes

(Mulders and Epema, 1 9 8 6 ) . The 5 / 4 ratio enabled the indication of areas with a higher gypsum content within the gypsiferous area. Due to their absorption in band 5 , these areas were characterized by a lower ratio. Table 11.6 Correlation coefficients between the bands 1-5 and 7 of data sets for the arid Seftimi area (lower left) and the semi-arid Kasserine area (upper right) after Epema ( 1 9 8 6 ) . 1 1 2 3 4 5 7

-

.928 .972 .622 .6a2 .425

2 3 4 .971 .944 .835 - .978 .878 .978 - .878 .778 .790 .812 ,843 .724 .509 .533 .434

5 .834 .894 .928 .892

-

,868

7 .824 .887 .892 ,843 .975

-

The band 5/total intensity ratio image of the Kasserine area produced high contrast between bare clay soils in a playa and other bare soil surfaces in the area. The bare clay surfaces showed a low ratio value, which was most probably

284

due to a reduction of the near nadir scattered radiation (received by the TM sensor) because part of the band 5 radiation was specularly reflected by platy surface crusts. Owing to the low sun angle at approximately 9:45 a.m.

when the

TM passes, this radiation is not detected by the TM sensor.

11.6.

Application Hilwig et al., (1974) concluded in their study on visual interpretation of

Landsat-1 promises 1:500,000),

imagery of the M6rida-region (Spain) to

be

very valuable for exploratory

that this kind of imagery surveys (at scales up

valuable for reconnaissance surveys (at scales up to 1:100,000)

useful for surveys at scales up to 1:50,000

to and

in conjunction with conventional

aerial photo-interpretation. Nowadays, Landsat MSS data are applied in numerous surveys, especially in exploratory and schematic surveys. But also at reconnaissance scales, Landsat MSS

may be used as a valuable aid in the pre-fieldwork stage, since a

multitemporal coverage offers insight in the dynamics of the environment. However, some coastal areas and parts of the equatorial tropics are so clouded that it is impossible to obtain images with a low cloud cover. In such areas low altitude aerial photography and radar have definite advantages. Furthermore, the low ground resolution and the low equatorial overlap (for stereoscopic observation) of the first generation Landsat MSS determine its use to be not competitive with aerial photography. However, TM data proved to be as valuable as airphotos for reconnaissance mapping of arid areas in that they offer additional information on soil mineralogy, which as such could not be interpreted from the airphotos.

11.7.

Conclusions and comments The application of first generation Landsat MSS imagery is found to be

useful in small-scale survey. The cost of Landsat MSS images are low for smallscale inventory of large areas when compared with those of aerial photographs.

It should be noted, that the degree of detail on Landsat MSS imagery with respect to landform is much less when compared to that of airphotos. If only a broad view is needed, a schematic analysis of medium-scale airphotos in order to indicate only the main landscape boundaries, may be sufficient. However, the large number of

photographs needed to study an

285

extensive area, is a drawback for this approach. Moreover, the synoptic view and

the multitemporal capacity of Landsat are points

in favour of

its

application for exploratory survey. A synthesis between interpretation of Landsat MSS imagery and the interpretation of airphotos of selected key areas is considered to be a proper approach

in small-scale soil mapping. The study of Landsat images of one acquisition date is generally done for the analysis of static elements: relief, landform, drainage pattern/density and alignments. For the study of dynamic elements such as natural vegetation and land use, multitemporal combinations have to be used. The application of automated processing of Landsat MSS data enables a more

accurate

determination

of

terrain

features.

Automated

classification is

successful, in areas with low variability in land use and crops. The benefit of automated processing will of course be great when sufficiently large areas are concerned, e.g.

the total area of a Landsat MSS frame (185 x 185 km).

Field

checking over such large areas requires much time and finances. To utilize the higher spatial resolution of Landsat systems, RBV images may be used ( 3 8 x 38 m ground resolution) or TM (Landsat 4-5;

30 x 30 m ground resolution).

The latter

may provide specific information on the type of soil surface, making it a valuable tool for mapping of arid areas or other, large, areas with bare soils.

In par. 14.4 (2b), the French satellite SPOT-1 is mentioned, which offers a 10 m and 20 m ground resolution, and stereoscopic capability. The first products (obtained in 1986) show a very good quality, and certainly widen the application potential of satellite-derived products for environmental mapping. However, the spectral domain limits itself to the 0.50 leaving the 1.5

-

2.4

um

11.5)

unique for the TM.

11.8.

References

-

0.90

m range,

range with its high information potential ( s e e par.

Barret, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. Chapman and Hall, London: 336 pp. Item., 1982: 352 pp. 1982. Analysis of Multi-Temporal Data for Bronsveld, M.C. and Luderus, F.J.D., the Identification of Land Use and Crops (case study on the Mgrida region in the Province of Badajoz, SW Spain). ITC, Enschede, The Netherlands, IBM Netherlands and Madrid, Vol. I and 11: Vol I 38 pp. App. 34 pp; Vol. I1 45 pp. Vol I. Dethier, B.E., Ashley, M.D., Blair, B.O. et al., 1975. Satellite Sensing of Phenological events. Search Agriculture Vol. 6 nr. 1, New York, 46 pp. Donker, N.H.W. and Mulder, N.J., 1977. Analysis of MSS digital Imagery with the aid of Principal Component Transform. ITC Journal 1977-3, Enschede, The

286 Netherlands: pp. 434-466. Epema, G.F., 1986. Processing of Thematic Mapper data for mapping purposes in Tunisia. hth ISSS Symposium Working Group Remote Sensing for Soil Survey (1985). ITC Journal, Enschede, The Netherlands. Goetz, A.F.H., Rowan, L.C. and Kingston, M.J., 1982. Mineral Identification from Orbit: Initial Results from the Shuttle Multispectral Infrared Radiometer Science, Vol. 218: pp. 1020-1024. Hielkema, J.U, 1979. Advanced Training and Research on Satellite Remote Sensing Techniques and Application in the United Kingdom and the United States. FAO, Rome, AGLT/RSU series 2/79: 111 pp. Hielkema, J.U., 1980. Remote Sensing Techniques and Methodologies for Monitoring Ecological Conditions for Desert Locust Population Development. FAO, Rome/USAID, CGP/INT/349/USA: 63 pp. Hilwig, F.W., Goosen, D. and Katsieris, D., 1974. Preliminary Results of the Interpretation of ERTS-1 Imagery for a Soil Survey. ITC Journal 1974-3, Enschede, The Netherlands: pp. 289-312. Hilwig, F.W., 1979. Selection of Landsat MSS data for Inventories of Earth Resources. ITC Journal 1979-2, Enschede, The Netherlands: pp. 249-266. Hilwig, F.W., 1980. Visual Interpretation of Multitemporal Landsat Data for Inventories of Natural Resources. ITC Journal 1980-2, Enschede, The Netherlands: pp. 297-327. Karssen, A.J., 1975. The Production of a Cartographic Colour Chart. ITC-Journal 1975-1: pp. 101-106. Meer Mohr, H.E.C. van der, 1968. Geological Interpretation of Hyperaltitude Photographs from Gemini Spacecraft. 11th Congr. of the Int. SOC. for Photogrammetry, Lausanne: 6 pp. Mulders, M.A. and O'Herne, E., 1981. Methodology of Small Scale Soil and Land Use Mapping with Landsat Data. Calatayud Basin (Spain). Int. SOC. of Soil Science. Third Symposium of Working Group "Remote Sensing for soil Surveys" Jablonna, Poland: 30 pp. Mulders, M.A. and Epema, G.F., 1986. The Thematic Mapper. A New Tool for S o i l Mapping in Arid Areas. hth ISSS Symposium Working Group Remote Sensing for Soil Survey (1985). ITC-Journal, Enschede, The Netherlands. NASA, Goddard Space Flight Center, 1972, 1976. Data Users Handbook. NASA Earth Resources Program. NASA, EKOS data Center, 1979. Landsat Data Users Note. Issues No 2 and No 5, May 1979. Sioux Falls, South Dakota. NASA, 1982. Landsat Data Users Notes Issue No 23 (July). EKOS Data Center, Sioux Falls, USA. National Academy of Sciences, 1977. Resource Sensing from Space: Prospects for Developing Countries. Washington: 202 pp. NOAA, 1983. Landsat Data Users Notes Issue No 26 (March), EKOS Data Center, Sioux Falls, USA. 1976. Surveying Earth Otterman, J., Lowman, P.D. and Salomonson, V.V., Resources by Remote Sensing from Satellites. Geophysical Surveys 2: pp. 431-467. Short, N.M., 1982. The Landsat Tutorial Workbook. Basics of Satellite Remote Sensing. NASA Reference Publication 1078, Washington D.C.: 553 pp. US Geological Survey, 1978. Manual on characteristics of Landsat Computer Compatible Tapes produced by the EKOS Data Center Digital Image Processing System. US Government Printing Office 024-001-03116-7 Washington: 70 pp. US Geological Survey, 1979. Landsat Sata Users Handbook. Arlington USA. US Geological Survey, 1982. Landsat Data Users Notes, Issue No 23 (July, 1982). EKOS Data Center, Sioux Falls, S. Dakota: pp. 1-12.

281 11.10. Additional reading Allen, T. and btham, J., 1980. Landsat orbits in a melting pot. New Scientist

17 April 1980: pp. 144-152. Campredon, R. Celles, J.C., Le Page, A. et Leprun, J.C., 1982. Essai de Cartographie, GQologique Automatisee d a m un secteur SahQlien, Influence des Facteurs Pedologiques et Phytosociologiques. Bull. SOC. GQol., France, t. XXIV, No. 1; pp. 7-12. Finch, W.A. Jr., 1973. Earth Resources Technology Satellite-1. Symposium Proceedings September 29, 1972: 165 pp. Gulinck, H., Gombeer, R. and D'Hoore, J., 1977. Area Measurements in Landsat imagery with Quantimet 720. Microscopica Acta, Supplement 1. Hirzel Verlag, Stuttgart: pp. 71-76. Gulinck, H., 1980. Recalibration of Multitemporal Dfgital Landsat MSS Data for Atmospheric Interaction. Application to Phenological and Pedological Landscape Studies. Pedologie XXX, 1, Ghent: pp. 89-114. Hempenius, S.A., 1976. Critical Review of the Status of Remote Sensing. Bildmessung und Luftbildwesen. Heft 1, 44. Jahrgang: pp. 29-41. LARS, Laboratory for Applications of Remote Sensing and the Agricultural Experiment Station Purdue Univ., Indiana, 1975. Natural Resource Mapping in Mountainous Terrain by Computer Analysis of ERTS-1 Satellite Data. Research Bulletin 919: 124 pp. Masson, Ph., Chavel, P., Equilbey et Marion, A., 1982. Apports du Traitment NumQrique d'Images Landsat a 1'Etude des Failles Libano-Syriennes. Bull. SOC. Sol., France, t. XXIV, No. 1: pp. 63-71. Pacheco, R.A. and Howard, J.A., 1977. Application of Satellite Remote Sensing to Landscapes and Soils. ler Colloque PQdologie TQlQdetection AISS, Rome: pp. 109-123. Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. I and 11. The American Society of Photogrammetry: 2144 pp. Vegas, P.L., 1974. Extracting Land Use Information from the Earth Resources Technology Satellite Data by Conventional Interpretation Methods. NASA TND-7730. Lyndon B. Johnson Space Center: 54 pp. Bijleveld, J.H. and Rosema, A,, 1980. A Study of Satellite Remote Sensing. Application and Mission Objectives in Developing Countries. EARS b.v., Delft, The Netherlands: 164 pp.

288

12.THERMAL INFRARED LINE SCANNING AND RADIOMETRY IN THE INFRARED AND MICROWAVE ZONES

Hudson (1969) reports about the development of Infrared techniques. As early as 1910, many workers were intrigued by the potential abilities of heat seekers and were proposing a wide variety of Infrared search devices. Many of

the basic techniques used

today for generating tracking signals, and

suppressing the effects of unwanted backgrounds, were conceived in the 1910 era. In the early 1920's

the availability of the thallous sulfide detector

encouraged a new generation of workers to concentrate on

Infrared search

devices. Some major events in the development of Infrared techniques were: the development of the image converter tube in the early 1940's, the lead sulfide detector in the late 1940's, the development of photon detectors sensitive in the 3 to 5

!.I

m window in the mid 1950's, and of small and reliable cooling

devices in the early 1960's.

In the 1940'9,

techniques of remote Infrared

sensing were primarily devoted to military applications for such purposes as fire control, missile guidance, night vision etc. Through extensive efforts by the

military,

the

technology was

advanced

to

a

point

where

it

became

economically feasible to contemplate a wide range of peaceful uses for Infrared sensors (Schaper, 1976). Remote sensing in the thermal Infrared is very promising, since it enables us to fill in the emission properties of natural targets, and we will acquire data on an important part of the interaction between solar radiation and objects at the earth's surface. In chapter 4 (section 4.3),

the line-scanner is discussed. This, in combination

with a thermal detector is the common device for remote sensing in the far Infrared. We will concentrate on this device but also mention the so-called Infrared imagers, capable of real-time picture presentation. In the chapters 2 and 3, I have discussed various elements of basic physics in connection with the interaction between solar radiation and materials at the earth's surface, of which a number of phenomena are important for this chapter. These are: sections

subjects

2.2

radiation laws;

289 2.7

thermal properties;

3.1

spectral emissivities rocks and minerals;

3.2

thermal data soils;

3.3

thermal properties plants.

12.1.

Airborne Infrared line scanners and Infrared imagers Thermal Infrared radiation has a wavelength, somewhat smaller than cloud

drop diameters, and therefore is not able to penetrate cloud cover. It can however

penetrate

haze better

than Visible

radiation due

to

its longer

wavelength (MacDowall, 1972). The Infrared line scanners or IRLS (see section 4.3)

with their small

field of view (typically between 1 and 5 mRad) operate either in the 3.5-5 or in the 8-14 um

m

,

transmission window. Normally the detectors have to be

cooled, that is to 77 K and 25 K, respectively. The equipment can record temperature differences either very precisely (e.g. range of temperature, or less precisely (e.g. The

radiometric

temperature

will

0.1

K)

within a limited

1 K) within a wider range.

always

be

less

than

temperature because of reduced emissivity (Fitzgerald, 1974). quartz shows an emissivity minimum near 9 um

the

actual

For example,

. To avoid the emissivity minimum

of quartz, a narrow band covering the region 10.4 um

to 12.6

um

has to be

used for precise measurements (Taylor, 1979). Lowe (1975) has listed commercially available Infrared scanners: Daedalus, Reconofax (HRB Singer), scanners differ

Bendix T/M and Siddeley (TRW Hawker).

in their methods of

data

recording and

The various

their ancillary

equipment as well as in resolution, sensitivity and v/H ratio (velocity/height ratio). The Infrared imagers differ from the line scanner in that they scan in two

directions, thus forming an image without the requirement of platform motion. The AGA Thermovision System 680 operates by two rotating prisms, the Dynarad 201 by oscillating mirrors.

Several systems claim spatial resolution of 1.7

mRad and a temperature sensitivity of about 0.1

K. The Infrared Imagers are

well suited for real-time qualitative detection of thermal anomalies. They can be adapted to aircraft (MacDowall, 1972; see also Borg, 1968). 12.2.

Satellite programs One of the earliest concepts of remote sensing in the Infrared from

290

satellites is the first successful satellite of the Nimbus series. Many

thermal Infrared images with

low spatial resolution have been

acquired from meteorological satellites, a.0. Satellite),

ITOS

( Improved

TIROS

ATS (Applications Technology

Operational

Satellite),

NOAA

(National

Oceanographic and Atmospheric Administration) and Meteosat (tables 4.3

and

11.1).

The NOAA satellites circle the globe at an altitude of 1500 km in near polar orbits. Images of equatorial localities are acquired twice daily: one during the day and one during the night. Besides thermal Infrared (10.512.5 um ), a separate imaging system i s used for coverage in the Visible (0.50.7 pm ). The scanning radiometer of the early NOAA series has a ground resolution of 4.0 km in the Visible and 7.5 km in the Infrared. However, the so-called "very high resolution radiometer" of the NOAA series has a ground resolution of approx. 1 km for both the Visible and Infrared bands (Sabins, 1978). The Skylab multispectral scanner S-192 (described in table 11.2) daytime Infrared imagery in the 10.2-12.5

pm

acquired

band (channel 13) with a ground

resolution cell of 79x79 m. Landsat 3 (table 4.3)

also includes a thermal band

(10.4-12.6

um ).

However, at the end of the year 1980, an anomaly appeared in the data being returned from the Landsat 3 MSS. Because of this, NASA decided not to operate the MSS on Landsat 3 (NASA, 1981). The so-called Meteosat programme is the European space Agency's

meteorological satellite programme

(see

Lennertz and Pryke, 1978).

first

Meteosat-1

was launched in 1977 and contains two adjacent channels in the Visible (between

0.5 pm 7.1 pm

and 0.9 pm ),

besides two Infrared channels, these being the 5.7-

band and the 10.5-12.5

pm

band.

The Heat Capacity Mapping Mission (HCMM) was the first of a series of small (short-term),

relatively

inexpensive Application

Explorer

Missions

(AEM)

conducted by NASA. Compared with Landsat, the orbit accuracy and attitude stabilization is considerably less precise. The HCMM or AEM-1

was launched on April 26, 1978. The radiometer aboard

acquired data in two spectral channels, being 0.5-1.1

um

and 10.5-12.5

m

.

The ground resolution was 600 m at nadir, the swath width was about 700 km. The 620 km high near polar orbit of the satellite was sun synchronous with passes over the USA at approx. 1:30 pm and 2:30 am, closely matching the maximum and

291 minimum daily temperatures of the surface. The earth was covered only within the range of five receiving stations, thus covering parts of the USA, Europe and Australia (Lillesand and Kiefer, 1979).

In addition to the four channel MSS of Landsat 1 and 2,

the Landsat 4

(launched in July 1982, table 4.3)

carries an advanced multispectral scanner;

the so-called Thematic Mapper (TM).

Besides bands in the Visible and the Near

Infrared, the TM has one band in the far Infrared (10.4-12.5

um), which has a

120 m resolution.

12.3.

Characteristics of airborne thermal Infrared imagery Geometric distortions due to the large scan angle and aircraft motion as

well as the effect of surface winds on thermal imagery are discussed briefly in section 6 . 4 . Below I will explain some density differences that may be observed on thermal imagery ( s e e also Bennema, 1972).

An example of thermal imagery of

grassland near Uithoorn at the Amstel river in the Netherlands is given in fig. 12.1;

it concerns a day-time image.

A gully pattern is clearly marked in the grassland. The gully is cold (moist) and shows relatively warm borders (due to their dry position).

The contrast

between the grassland parcels is determined by the grass coverage: a dense cover means a low temperature. The white (warm) parcels have been intensely grazed and had a low density cover at the acquisition date. The ditches are colder than their SuKKoundingS, but the walls which are sunlit have been warmed up in the preceding hours and appear white on the image. Thermal

images record the pattern

of heat

radiated from materials,

something which the human eye is not capable of doing.

The momentaneous

radiometric temperatures of the interfaces of, respectively, soil and plant with air are registered, the first being strongly influenced by soil properties such as moisture condition of the topsoil and roughness of the soil surface, the second by crop

OK

natural vegetation properties, and in case of a low

vegetation cover, also by soil properties. For a dense vegetation cover e.g.

grown crops or dense grassland, signal

strength is determined by evapotranspiration of crops, which is related to the available soil moisture and the actual weather conditions.

Fig. 12.2 contains thermal imagery of 15 March 1973 of the Agricultural Station at the Haarweg, Wageningen, The Netherlands. The crops grown at the

292

Fig.

12.1Day-time thermal image of grassland near Uithoorn, names Binnenpolder at the Amstel (The Netherlands); acquisition date: July 1976, 2:OO pm.

293

Fig.

12.2 Thermal imagery of 15 March 1973 of the Agricultural S t a t i o n a t the Haarweg, Wageningen, The Netherlands.

294

acquisition date are given in fig. 12.3. Image quality appears to be strongly dependent

on

the meteorological conditions

(table 12.1).

Fig. 12.3 Agricultural Station at the Haarweg, Wageningen, The Netherlands 15 March 1973.

on

Experiments: g = grass g= = grass and clover g' = grass experimental field J = winter wheat ws winter wheat (sprinkler irrigation) rs winter rye (sprinkler irrigation + strips of bare s o i l ) b bare soil 1,2,. = field numbers

--

Except for the evening, image quality is good.

Influence of wind is most

visible in the morning and evening imagery. For a characterization of the grey tones on the images, the N-scale of the Standard Soil Colour Chart (Fujihira Industry Co, Ltd, Tokyo, Japan) was used: 1 2

-

-

dark grey N 410

black N 1/0

4

black N 2/0.

5 = grey N 5/0

8 = greyish white N 8/0

6 = grey N 610

9 = white

3 = greyish black N 3/0

7

=

greyish white N 7/0

The grey tone differences are related to thermal differences and therefore can be used for a qualitative signature.

295

Table

12.1 Meteorological data Observing Station Deelen at a distance of approx. 17.5 km of the Haarweg (Wageningen) on 15 March 1973.

time of observation

weather last 3 hrs

surface wind speed

05.00 am

groundfog 8 Kts increasing cloud cover

0°C

97

11.30 am

hazy

21.00 pm

increasing 5 Kts cloud cover less than 4/8

12 Kts

air temp

low cloud

turbulence

x

stratus 6/8 400 ft

NIL

8.4"C

53 X

cumulus 1/ 8 3000 ft

lightmoderate

3.0"C

69 Z

strato cumulus 3500 ft

NIL

.

rel. hum.

Further information: the precipitation in the preceeding 12 hrs was NIL and the earth's surface condition was DRY. In Table 12.2 the grey tones have been indicated for the different fields as given in Fig. 12.3. Grassland has a qualitative signature 5-7/3-6/9-7

(intermediate-warm/inter-

mediate-cold/warm) different from that of winter rye with 6/2/9 (intermediate/cold/warm) winter

and winter wheat

wheat/sprinkler

intermediate).

with

21'6-8/7

irrigation

with

(cold/intermediate-warm/warm)

2/5-6/4

OK

(cold/intermediate/-

The qualitative signatures represent the early morning/just

after noon/evening grey tones. For bare land there are different signatures, which are related to differences in soil surface texture, tillage or summer crop. Most surfaces have a clay texture and show a signature 2/3-9/dominantly 7-8 (cold/cold-warm/warm. Differences in thermal behaviour, especially just after noon, may be related to different tillage practices or summer crops. The soils were moist enough to produce thermal radiation in the evening, but in the early morning they were colder than grassland. Bare land with a sandy texture deviates in producing a signature 2/2-6/2 ( c o l d / c o l d - i n t e r m e d i a t e / c o l d ) .

The

upper part of soil is apparently dry and impedes radiation from, or into the soil. From the examples given, it will be evident that much specific knowledge is required for the interpretation of thermal imagery.

12.4. Thermal models Thermal measurements are relatively accurate and enable the indication of

296 Table 12.2 Grey tones of 21 fields of the Agricultural station at the Haarweg (Wageningen, The Netherlands). field number

relative thermal condition at different acquisition land use times; grey tones 1-3 relatively cold, 7-9 relatively warm, 4-6 intermediate condition 5:23-6:42

1 2

hrs

1 2 : 0 9 - 1 3 : 4 3 hrs

2 1 : 4 0 - 2 3 : 0 0 hrs

5(+7) 5(+7)

3(+4) 5(+4)

9(+7 +4) 9(+a)

7(+6) 2

6(+5 +4) 4 6(+4)

9(+a) 7 ~ + 7 ) 7 7

3 4 5

5

6 7

2 2

4

8 9 10 11 12 13 14 15 16

2 2 2 2 2 2 2 7(+5) 6

a a

8(+9 6(+5 +4) 3(+5) 2

7 7 7 4 8 8(+7) 7(+8) 9(+8) 9

17 18

2 2

6 6

2 4

19 20 21

2 2 2

2 2 5

2 2 4

8

6 3

8

grassland grass experimental field grassland bare land grass and clover bare land winter wheat + bare land bare land bare land winter wheat bare land bare land bare land bare land grassland winter rye (sprinkler irr. + bare soil) bare land wint erwheat (sprinkler irr.) bare land bare land winter wheat (sprinkler irr.)

small differences in vegetation morphology and coverage, soil roughness, soil moisture and porosity. Generally, the purpose of the research is to obtain insight in the thermal condition of objects at the earth's surface, rather than the identification of the objects, which is best done with the aid of Visible and near Infrared radiation. Thermal data are used at different scales of mapping. At small scales, an overall view may be obtained from the thermal condition of complex land units. At large scales, single land units or objects are recognized individually. Surface temperatures of units

such as parcels with annual crops can be

calculated from the thermal radiation received by the detector. These and other

297

data, as input to thermal models, may yield evapotranspiration estimates, and subsequently, estimates on soil moisture pressure. Natural objects show a lower emittance than a black body. Combining the formulae 2-4 and 2-5, 4 E U T

M = where

the emittance of natural objects (M in Wm-’)

is given by: (12-1)

E

=

emissivity,

u

=

Stefan-Botzmann’s constant (Wm-2K-4),

T

=

temperature (K).

The thermal Infrared is absorbed strongly by the atmosphere (fig. 2 . 1 2 ) . However, windows are found between 3 um

.

14 um

and 5 um

and between 8 m

and

In the day-time the first window also shows contribution of solar

radiation (fig. 2-4),

the second is practically free of solar radiation and is

therefore generally used. Apart from absorption, the atmosphere itself acts as a source of thermal radiation.

In calculating the crop surface temperature from remote sensing data, the influence

of

different

(Nieuwenhuis, 1979):

atmospheric

layers

can

be

evaluated

as

follows

the radiance at the top of layer n (M”) is equal to the

emittance of layer n, augmented by the amount of transmitted radiance derived from layer n-1, therefore:

where Tbc = equivalent black body crop surface temperature (K), T

=

transmittance.

Neglecting P and M in formula 2-32, the energy balance equation is as follows:

Rn

= S

+

where S

A

+ LE

(12-3)

= heat radiation from, or into the soil (Wm-’),

A

=

heat radiation from, or into the air (Wm-’),

LE

=

evapotranspiration

OK

latent heat flux into the air (w~a-~).

R~ (the net radiation) can be split up into a net short-wave and a net longwave radiation term (Nieuwenhuis, 1981):

298

+

-

p)

where Rs

=

incoming short-wave radiation flux (Wm-2),

=

Rs

p = CKOP*S E

= crop's

(R1

E

-

4

(1

Rn

0

T

( 12-4)

)

reflectance, emissivity (section 2.2),

R1

=

long-wave sky radiation flux (W~I-~),

u

=

Boltzmann constant,

Tc = crop surface temperature. Considering a crop surface with a temperature Tc ( K ) which transports heat up to a certain height above the surface through a column of air with temperature the transport equation can be expressed a s (Nieuwenhuis, 1981):

Ta ( K ) ,

A = - d C

Ta - Tc -

( 12-5)

'ah where d

=

density of moist air (Kg

r3),

C = specific heat of moist air (.J.Kg-lK-l), P rah= turbulent diffusion resistance of the atmosphere for heat transport (s.rn-')

as determined by wind velocity, atmospheric stability and

the height and roughness of the crops. Combining the equations 12-3, 12-4 and 12-5 the relation between LE and Tc can be found (Soer, 1980): ( 12-6)

The momentary evapotranspiration has to be converted into 24 hr estimates of evapotranspiration. This can be done by the so-called Tergra-model (Soer, 1977).

Subsequently,

the moisture

condition of

the

soil

(soil moisture

pressure) can be estimated from the evapotranspiration rate (Soer, 1980). This method

has

been applied successfully to obtain data about soil moisture

pressure in the root zone of grassland, but may also be practised for other conditions. However, problems may arise when plants are in a recovery period (after being stressed) before the normal water uptake and the transpiration proceed

(Jackson,

1982).

Moreover,

if

the rootzone cannot be

adequately

specified, the data obtained refer to the soil moisture availability rather than the soil moisture pressure in the rootzone.

299 Price (1982) discusses the estimation of regional evapotranspiration through analysis of satellite thermal infrared (HCMM) data. The following steps are indicated:

-

correction of the data for atmospheric effects which are related

to the

water-vapour content;

-

preliminary estimation of LE; correction of LE through the use of a numerical simulation model, the Tell-US model. The Tell-US model is presented by Rosema (1978).

He used the following

eq ua t i o n s :

-

the transient heat flow equation for a homogeneous soil

dT/dt

=

where T

=

2 2 a d T/dZ

( 12-7)

soil temperature (K),

t = time ( s ) ,

Z = depth (m),

,

a

=

a

=

A

= soil thermal conductivity (Wm-lK-l),

A/C

soil thermal diffusivity (m2 s-'),

C = volumetric heat capacity of the soil (Jm-3K-1);

-

The surface heat balance equations a.0.

LE =

dL (sa

-

h. go)

LE in the case of bare soil

/ ra

( 12-8)

=

heat of evaporation (J Kg-l),

sa h

=

specific vapour density at height Za,

=

surface relative humidity,

go

=

saturated specific vapour density at the surface,

d

=

density (Kg m-3),

ra

= turbulent diffusion resistance for heat transport ( s m-').

where L

300 A simulation model of the daily course of the soil surface temperature and heat balance is used. Atmospheric stability is important. Due to the relatively high stability of the atmosphere

at

temperature and

night, the

there

is

a

high

thermal inertia of

correlation between soils.

the

surface

In the day-time, due

to

atmospheric instability, the surface temperature largely depends on the level of evaporation, i.e.

on the surface relative humidity, or crop resistance. The

so-called Tell-us interpretation algorithm solves the thermal inertia P (2-29) and the surface relative humidity (h) and additionally determines the daily evaporation total. Look-up graphs, such as the one given in Fig. 12.4

are used

for their determination. Tell-us (originally developed for bare soil surfaces) uses two remotely sensed

surface

temperatures,

close

to

the

daily

maximum

and

minimum

temperatures and needs only a few place-dependent input parameters, and seems therefore operationally attractive. However, Huygen (1979) points to problems related to the application of Tell-us to vegetated surfaces. For more information on the Tell-us model, the reader is referred to Klaassen and Rosema ( 1 9 7 9 ) and Huygen et al. ( 1 9 7 9 ) . Estimates on thermal inertia are often used as a discriminating criterion between different soil types. In studying various soil surfaces, I’ratt ( 1 9 7 9 ) found differences in thermal inertia between different soils having the same volumetric moisture content. Apart from its dependency on the soil moisture content, the thermal inertia appears to be strongly dependent on the porosity. Soils with a different porosity but the same moisture content vary strongly in their thermal inertia values (see fig. 12.5). For the estimation of the thermal inertia, Pratt ( 1 9 7 9 )

uses two primary

values, being: the maximum diurnal temperature difference of the soil surface ( AT ) and the albedo of the soil surface (A),

which are both correlated to

soil moisture content, texture and structure (porosity),

and may be estimated

from a remote distance. The value of thermal inertia is then estimated, using a calibration chart (see fig. 12.6).

The chart is calculated from model slmula-

tion of the diurnal temperature variations for a given set of meteorological conditions. 12.5.

Interpretation of thermal data. There are three basic approaches in the handling of thermal data, namely

301

l i n e s o f equal - _ _ - -- -P h ...............d a i l y evap.

322

:/\

31e LL

I

314

VI

L

1 0

1 310

m 7

v

? 306 c 3 ,

m L W W c,

3

n

302 298

294 291 Night t e m p e r a t u r e (26.30 h r s ) K

Fig. 1 2 . 4 . Look-up graph March 5, 1971 Avondale loam, Phoenix (Arizona) after Rosema ( 1 9 7 8 ) . Courtesy of the European Space Agency. the application of thermal models ( s e e Sabins, 1978),

the empirical approach

and the physical explanation assisting the visual interpretation of thermal imagery. With the Terga model, SOeK (1980) temperatures that

agree well with

grassland in the Netherlands).

derived simulated crop surface

the actual

temperatures measured

(for

The calculated evapotranspiration rates were

compared with those derived from water balance estimates, the differences being within 30 percent accuracy. Rosema (1978) consisting of

reports about results obtained from a bare soil test plot,

so-called Avondale loam

Phoenix, Arizona).

(US Water

Conservation Laboratory,

The interpretation algorithm discussed in the previous

section ( 1 2 . 4 ) has been applied to this data set. A good correspondance was

302

P

P

100 % sand S

0 .r

-v

.r v)

0

n

5 V

7

.r

0

m

100% c l a y @ - ~ o r o st yi = 3 0 %

0-Porosi ty=40 %

P

P

100 % sand

100 % c l a y 0.1 M o i s t u r e C o n t e n t (m3m3)

'

I

'

I

0.5 M o i s t u r e Content (

@Porosity=50 %

0.3

m3P)

t-Porosity=60 %

Fig. 12.5 Thermal inertia (Jm-2s-fK-1) simulation of soils with a variable clay/sand ratio and moisture content for porosities ranging in value from 30 to 60 percent after Pratt et al., ( 1 9 7 9 ) . found between average soil moisture content of the top 7 cm of soil and the average soil moisture content determined with the Tell-us algorithm. However, the daily evaporation according to the Tell-us algorithm was somewhat underestimated. Huygen and conditions of

Reiniger

(1979)

have

tested

the Tell-us model

a catchment area in the UK (Grendon).

for

the

They met two problems

concerning the model, being: the numerical value of the soil heat capacity and

303

4000

3000

2000

1000

0.2

0.4

0.6

0.8

A1 bedo

Fig. 12.6 Thermal inertia calibration model to calculate thermal inertia values from maximum diurnal temperature difference ( A T ) and albedo values after Pratt e.a. (1979); wind speed 2.5 m s- , surface roughness 0.001 m, radiative sky temperature - 13"C, air temperature 15-25°C. the assumption of a constant surface relative humidity. The night surface temperatures proved

to be sensitive to the (high) heat

capacity value employed. The soil temperatures simulated with a relatively high soil heat capacity were lower than the "correct" values, the difference ranging from 1.3"C for a water-saturated soil to 2.7"C for an air-dry soil. For the rather moist atmosphere in Grendon, condensation will have its effect on surface temperature. However, condensation is not included in the model when

calculating the cumulative evaporation. Huygen and Reiniger (1979) suggest corrections for these problems and conclude that the use of simulation models and the look-up tables they produce should always be accompanied by a proper examination of the assumptions inherent to the models. The empirical approach involves a correlation between image signatures and

304

the corresponding ground

features without

a direct

consideration of

the

underlying physical causes. The thermal imagery in this approach is interpreted visually,

or

the

interpretation is

done with

the aid

of

densitometric

measurements. Image enhancement may be achieved by density slicing. An example of the empirical approach is discussed in par. 12.3.

One may also use physical explanation to assist the visual interpretation. Bijleveld (1977) applied this interpretation method on thermal images of an area in Zeeuws Vlaanderen (The Netherlands).

The images were acquired at four

points of time within 2 4 hrs. Particularly in the day-time, temperature differences in images can be seen between one parcel and another, which may be due to differences in surface roughness. The surfaces covered with vegetation, apart from the tree-covered areas, exhibit a large diurnal amplitude of the Surface temperature. Part of the area is clearly discriminated from the rest of the area in showing lower temperatures of bare soil surfaces at night and higher temperatures during the day-time.

The soils in this part are dry sands rich in quartz.

During the day-time the dry quartz sand of the bare soil generally develops a higher real temperature and radiative temperature than moist clay deposits (the sand has a high reflectance but a low absorptance when dry). At

night

the

sandy surface develops a

real temperature lower

than

its

surroundings; the difference in radiative temperature may be even larger than that in real temperature, considering the relatively low emission coefficient. Quartz has a low emission coefficient when compared to clay, feldspar, humus or water. Thus, a bare soil surface that has a higher radiative temperature than its surroundings during the day and a lower one at night is generally a dry surface and is very likely to be a sandy surface. Compaction of soil may

be detected by

IRLS (Janse, 1973),

since it

produces a higher thermal conductivity and density. Although the specific heat of compacted soil is lower, mainly due to a lower water content (see table 3.1),

the thermal inertia (2-29) will be higher, assuming the surrounding soil

to contain about 20 % air and 20 % water. In this case, the compacted soil will have a relatively low temperature at 14:OO a.m.,

since much heat is transported

downwards, but it also shows a relatively low night temperature the latter as a

305

result of the high rate of heat transfer at the compacted soil surface.

It is possible that I R L S may provide a new soil-mapping tool in arid areas. This may be true when the surface conditions as influenced by tillage or range management are identical over large areas. Otterman et al., (1975) described a case where management was important. They studied albedo and temperature of nearly bare ( <

25

Z

vegetation cover)

overgrazed areas and nearby areas with a vegetation coverage between 25 Z and 80 Z respectively, in the Sinai/Gaza strip and in the Negev. The overgrazed

soil has a very high albedo in contrast to the vegetation covered soil. The latter is affected in a significant way by dark vegetation debris littering the surface. The protected site was measured to have summer afternoon temperatures which are some six degrees higher than those of the bright, protected side. The higher radiation temperatures on the vegetated site are an indication that the evapotranspiration and thermal inertia of the green biomass in this study area do not affect appreciably the thermal flux, which is actually dominated by the albedo differences. This is supported by the results obtained by Saltzman and Ashe (1976).

They found that the diurnal temperature range at the surface is

most sensitive, on a percentage basis, to the conductivity of the soil and to the surface albedo, in that order; quite sensitive to the emissivity and less sensitive to the water availability factor for evaporation. With regard to the phenomena studied, Saltzman and Pollach (1977)

state the

following: the high temperatures and "darkness" of the Negev are caused by plant

debris with

conductivities closer

to

that of

soil, than to

live

vegetation.

12.6.

Application of thermal Infrared line scanning Hudson (1969) presented a summation of applications of Infrared techniques

of which I will only give a selection. Apart from military, industrial and medical applications there is a broad application field in Earth Resource Surveys a.0.: remote sensing of weather conditions;

-

determination of constituents of the atmosphere; measurement of the earth's heat balance; terrain analysis a.0. in volcanic areas; detection of water pollution;

306

-

sea-ice reconnaissance;

-

detection of forest fires.

Van Dijk et al., ( 1 9 7 1 ) did not find an unambiguous correlation between temperature measurements at 1.5-2.0

m below the soil surface and the 1nfrar.ed

line-up of an area in Oman. The temperature variations found by remote sensing could only be related to superficial effects of surface features and to the presence of shallow groundwater. This limits the possibilities for geological application of IRLS. However, they expect interesting application fields for the detection of surface salt-domes and large structural depressions. Very interesting applications are found in the field of agriculture a.0.: the estimation of evaporation over large areas;

-

study of microclimate and the location of night frost areas; the study of soil temperature and soil moisture condition; detection of diseased crop areas and extend of soil salinity (see Myers et al., 19615).

Furthermore, thermal data (e.g.

Landsat 4 ) may be used in combination with

Visible and near Infrared data, to improve differentiation of land cover types (Ormsby, 1 9 8 2 ) .

12.7.

Non-imaging sensing in the Infrared and passive Microwave sensing. Infrared radiometers (see also section 4.3)

operate in the following way:

the radiant flux of an area is measured and compared with the energy from a black body source of a known temperature. By this comparison, the absolute temperature can be obtained rather accurately. Fig.

12.7

represents schematically the elements of a radiometer. In this

figure, the primary optical system is shown as a refractive element, but reflective systems are more widely used. The wavelength range is controlled by a filter or a combination of a filter and other

optical

elements.

The

modulator,

or

chopper, causes

the

detector

alternately to l o o k at the target and then to check the internal reference. The output

of

the detector

is a

chopped alternating electrical signal, the

amplitude of which is related to the radiance difference between the target and the reference.

307

Radiation reference Object plane

Image o f f i e l d stop i n o b j e c t plane Primarv

A-

-

I

I

__--ten1

Fig. 12.7 Elements of a radiometer after Lowe ( 1 9 7 5 ) . (Used by permission o f Am. Soc. for Photogrammetry and Remote Sensing.)

The radiometer records the radiant temperature measured along a narrowwidth path on the ground. At any instant in time, the radiometer senses the thermal radiation within its instantaneous field of view (IFOV or

R

).

A small I F O V is desirable for high spatial detail. On the other hand, the great

quantity of energy, which is obtained by a large I F O V ,

permits more sensitive

temperature measurements and thus an improvement of radiometric resolution can be expected. An

example of a thermal radiometer is the Barnes Model PRT-5,

the 8 to 10 pm

has a temperature range of -50°C as small as 0.1"C

which operates in

band. For aircraft use it is supplied with a 2.5 mrad I F O V .

It

to i 1 5 0 " C and responds to temperature changes

(Lillesand and Kiefer, 1979).

Passive Microwave sensors exist both in the form of radiometers and scanners. The basic configuration of a Microwave radiometer includes an antenna with a large beamwidth. The antenna signal is alternately sampled together with a calibration temperature reference signal. The low strength antenna signal is amplified and compared with this reference signal. The difference between these

308 signals is electronically detected. A scanning device, the so-called "Naval Weapons Center High Resolution Microwave Imaging System" has been developed. The product of this system is an image which bears a marked resemblance to thermal imagery. Estes et al., (1977)

report about passive microwave imagery

obtained by this scanner from a flying-height of 760 m. Density measurements on the

basis

of

this

type

of

imagery

have

been

found

to

relate quite

systematically to the moisture content of the topsoil. During

the

past

decade

there

has

been

a

significant

interest

in

investigating the potential of Microwave radiometry to obtain information on soil moisture. The effect of moisture on the dielectric constant of soil, the response of microwave sensing to soil moisture, the effect of soil surface roughness, as well as the masking effect of vegetation to the respons of the underlying soil have been investigated. The results indicate that passive microwave measurements using wavelengths from a few cm down to 21 cm ( 1 , 4 GHz) can only indicate the effect of soil moisture to very shallow depths, being approximately measurements

2

cm.

of

bare

Furthermore, soil

the

Microwave

indicate that, when

brightness

roughness

temperature

increases, the

sensitivity to soil moisture decreases. The effect of the roughness on the measurement sensitivity is dependent on the wavelength of the EMR used for detection (Newton et al., 1982). Using a model with roughness correction, Burke and Schmugge (1982) found a more sensitive response to soil moisture content of bare soils at a wavelength of 21 cm, than at either 2.8

cm or 1.67

cm. In

studying wheat and alfalfa fields, the 2 1 cm radiation provides soil surface moisture information as it penetrates through the vegetation layers. At the shorter wavelengths of 2.8

and 1.67

cm, the vegetation controls the overall

microwave signature, since the short wavelength radiation cannot penetrate through the vegetation canopy. The investigators of test-flights on radiometry often spend much time in determining the relation between the sensor output and the ground scene. Which particular object in the ground scene produced the response in the sensor output? To overcome this problem, Epler and Merrill (1969) describe the use of a movie camera aligned in such a way that the optical axis nearly coincides with the radiometer bore sight, and the camera field of view includes the complete boresight path. On each image, fiducial marks are fixed with respect to the camera optical axis

309 and serve as a reference for all measurements on the images.

12.8. Conclusions Infrared line scanners, Infrared imagers and Infrared radiometers are the instruments for sensing the thermal Infrared, using airborne or spaceborne platforms. The HCMM of

1978 gave an impetus to the modelling of thermal

processes at the earth's surface. Some models use one remotely sensed surface-temperature, close to the daily maximum, and need a large number of place-dependent input parameters. However, the Tell-us model uses two remotely sensed surface-temperatures close to the daily maximum and minimum temperatures and needs only a few place-dependent input parameters. The use of simulation models and the look-up tables they produce, should be accompanied by a proper examination of the assumptions inherent to the models to avoid misinterpretation.

It is clear that much specific knowledge is required for the interpretation of thermal data.

Furthermore, the data are very sensitive to physical surface

properties and may reveal much information on this topic. The use of airphotos e.g.

false colour, or true colour airphotos in a complementary way is advised. There is a wide field for application of Infrared techniques of which

agricultural applications such as evaporation studies are very promising. Passive microwave sensors were originally characterized by a low spatial resolution. However, recently scanner devices became available which offer an important improvement with regard to this aspect.

I am well aware of the fact that the present text on thermal data is only an introduction to this subject and consequently an extensive list is produced on additional reading to indicate ways of further study. 12.9. References* Bennema, J., 1972. De toepassing van Luchtopnames in de Bodemkunde. Landbouwkundig Tijdschrift 84ste jaargang nr 1: pp. 6-14. Borg, S.B., 1968. Thermal Imaging with Real Time Picture Presentation. Applied Optics, Vol. 7, no 9: pp. 1697-1703.

*

see also chapter 3.

310 1982. E f f e c t s of v a r y i n g S o i l M o i s t u r e C o n t e n t s Burke, H.K. and Schmugge, T . J . , and V e g e t a t i o n Canopies on Microwave Emissions. I E E E Trans. on Geoscce and Remote S e n s i n g , Vol GE-20, No 3: pp. 268-274. B i j l e v e l d , J.H., 1977. Thermal I n f r a r e d Scanning f o r t h e Survey of Q u a t e r n a r y Geology. “ A T e s t i n an A g r i c u l t u r a l Area”. NIWARS publ. No 39, D e l f t , The N e t h e r l a n d s : 88 pp. D i j k , C. van, Mulder, C . J . , P o l e y , J.Ph. and S t e v e n i n c k , J. v a n , 1971. E x p l o r a t i o n f o r ( s h a l l o w ) G e o l o g i c a l S t r u c t u r e s w i t h t h e Thermal I n f r a r e d Imagery Technique i n some D e s e r t Areas of Oman. 7 t h Symposium on Remote S e n s i n g , Michigan: pp. 2115-2131. E p p l e r , W.G. and Merrill, R.D., 1969. R e l a t i n g Remote Sensor S i g n a l s t o GroundT r u t h I n f o r m a t i o n . Proc. of t h e I E E E , Val 57, No 4 A p r i l 1969: pp. 665675. E s t e s , J.E., Mel, M.R. and Hooper, J . O . , 1977. Measuring S o i l M o i s t u r e w i t h and Airborne Imaging Passive Microwave Radiometer. Photogrammetric E n g i n e e r i n g and Remote S e n s i n g , Vol. 43, No. 10: pp. 1273-1281. F i t z g e r a l d , E., 1974. M u l t i s p e c t r a l Scanning Systems and t h e i r P o t e n t i a l A p p l i c a t i o n t o Earth-Resources Surveys. S p e c t r a l P r o p e r t i e s of M a t e r i a l s . ESRO CR-232, N e u i l l y , France: 231 pp. Hudson, R.D. Jr., 1969. I n f r a r e d System E n g i n e e r i n g . John Wiley & Sons, New York, London: 642 pp. 1979. A T e s t of t h e T e l l - u s Model f o r t h e Huygen, J. and R e i n i g e r , P., c o n d i t i o n s of t h e Grendon T e s t S i t e . T e l l - u s N e w s l e t t e r 8. J o i n t Research C e n t r e , I s p r a , I t a l y : 16 pp. Huygen, J., 1979. F u r t h e r Developments of t h e T e l l - u s Model. T e l l - u s N e w s l e t t e r 11, J o i n t Research C e n t r e , I s p r a , I t a l y : 17 pp. Jackson, R.D., 1982. Soil Moisture Inferences from Thermal-Infrared Measurements of V e g e t a t i o n Temperatures. IEEE T r a n s a c t i o n s on Geoscience and Remote S e n s i n g , Vol. GE-20, No 3: pp. 282-285. J a n s e , A.R.P., 1973. Toepassing van Warmteheelden. Landbouwkundig T i j d s c h r i f t 85-6, The N e t h e r l a n d s : 10 pp. 1979. G e n e r a l i s a t i o n of t h e T e l l - u s Model t o K l a a s s e n , W. and Rosema, A., V e g e t a t e d S u r f a c e s . EARS bv. D e l f t , The N e t h e r l a n d s : 18 pp. Lennercz, D. and Pryke, I., 1978. The E a r t h O b s e r v a t i o n Programme of t h e European Space Agency. Proc. of I n t . Conference on E a r t h O b s e r v a t i o n from Space and Management of P l a n e t a r y R e s o u r c e s , Toulouse 6-11 March 1978, ESA SP-134: pp. 163-176. L i l l e s a n d , T.M. and K i e f e r , R.W., 1979. Remote S e n s i n g and Image I n t e r p r e t a t i o n . John Wiley & Sons, New York: 612 pp. Lowe, D.S. ( a u t h o r - e d i t o r ) , 1975. Imaging and Nonimaging S e n s o r s . C h a p t e r 8 i n Manual of Remote Sensing ( e d . R.G. Reeves) Amer. Sac. of Photogrammetry, F a l l s Church, V i r g i n i a : pp. 367-397. 1972. A Review of S a t e l l i t e and A i r c r a f t . Remote S e n s i n g MacDowall, J., Instrumentation. 1st Canadian Symposium on Remote S e n s i n g , Ottawa, 7 F e b r u a r y 1972: pp. 39-68. Asce, M., C a n t e r , D.L. and R i p p e r t , W . J . , 1966. Remote S e n s i n g f o r Myers, V . I . , Estimating Soil Salinity. J o u r n a l of t h e I r r i g a t i o n and Drainage D i v i s i o n . Proc. of t h e Amer. SOC. of C i v i l Eng. I R 4: pp. 59-69. NASA US Geol. Survey, Eros Data C e n t e r , 1981. Landsat Data Users Notes. I s s u e No 16 J a n u a r y 1981. Newton, R.W. e.a., 1982. S o i l M o i s t u r e I n f o r m a t i o n and Thermal Microwave Emission. IEEE Trans. i n Geoscce and Remote S e n s i n g , Vol. GE-20, No 3: pp. 275-281. Nieuwenhuis, G. J . A . , 1979. Influence of atmosphere on t h e r m a l i n f r a r e d r a d i a t i o n . Nota ICW 1159, Wageningen, The N e t h e r l a n d s . Nieuwenhuis, G . J . A . , 1981. A p p l i c a t i o n of HCMM S a t e l l i t e and A i r p l a n e R e f l e c t -

311 t i o n a n d Heat maps i n A g r o h y d r o l o g y . ICW Techn. B u l l 122, Wageningen, The N e t h e r l a n d s o r Adv. S p a c e Res. Vol 1, COSPAR: pp. 71-86. Ormsby, J.P., 1982. The u s e o f L a n d s a t - 3 Thermal Data t o h e l p d i f f e r e n t i a t e Land C o v e r s . Remote S e n s i n g of E n v i r o n m e n t 12, E l s e v i e r S c c e . P u b l . Co, New York: pp. 97-105. O t t e r m a n , J . , W a i s e l , Y. a n d R o s e n b e r g , E., 1975. W e s t e r n Negev a n d S i n a i E c o s y s t e m s : C o m p a r a t i v e S t u d y of V e g e t a t i o n , Albedo a n d T e m p e r a t u r e s . Agro-Ecosystems 2. E l s e v i e r S c i e n t . P u b l . Cy, Amsterdam: pp. 47-59. P r a t t , D.A. a n d E l l y e t t , C.D., 1979. The Thermal I n e r t i a Approach t o Mapping o f S o i l M o i s t u r e a n d G e o l o g y . Remote S e n s i n g of E n v i r o n m e n t 8, E l s e v i e r N o r t h H o l l a n d : pp. 151-168. P r i c e , J.C., 1982. E s t i m a t i o n of R e g i o n a l S c a l e E v a p o t r a n s p i r a t i o n t h r o u g h A n a l y s i s of S a t e l l i t e T h e r m a l - I n f r a r e d D a t a . I E E E T r a n s . o n G e o s c i e n c e a n d Remote S e n s i n g , Vol GE-20, No 3: pp. 2A6-292. Rosema, A., 1978. The A p p l i c a t i o n of Thermal I n f r a r e d Remote S e n s i n g Data t o S o i l M o i s t u r e a n d E v a p o r a t i o n D e t e r m i n a t i o n . J o i n t ESA/FAO/I!MO Int. Training Course in Satellite Remote Sensing Applications in A g r o c l i m a t o l o g y a n d A g r o m e t e o r o l o g y , FA0 Rome: 19 pp. S a b i n s , F.F. Jr., 1978. Remote S e n s i n g . P r i n c i p l e s a n d I n t e r p r e t a t i o n . W.H. Freeman and Cy. S a n F r a n c i s c o : 426 pp. S a l t z m a n , B. a n d Ashe, S . , 1976. The V a r i a n c e of S u r f a c e T e m p e r a t u r e due t o D i u r n a l a n d C y c l o n e - s c a l e F o r c i n g . T e l l u s 28: pp. 307-322. Saltzman, R. and P o l l a c k , J.A., 1977. S e n s i t i v i t y of t h e D i u r n a l S u r f a c e T e m p e r a t u r e Range t o Changes i n P h y s i c a l P a r a m e t e r s . J o u n a l of A p p l i e d M e t e o r o l o g y , Vol. 16: pp. 614-619. Schaper, P.W., 1976. I n f r a r e d S e n s i n g Methods. In: Remote S e n s i n g f o r E n v i r o n m e n t a l S c i e n c e s . S p r i n g e r - V e r l a g , B e r l i n , H e i d e l b e r g , New York: pp. 84-109. S o e r , G.J.R., 1977. The T e r g r a Model, a M a t h e m a t i c a l Model f o r t h e S i m u l a t i o n of the Daily Rehaviour of Crop S u r f a c e Temperature and Actual E v a p o t r a n s p i r a t i o n . NIWARS p u b l . 46, D e l f t , The N e t h e r l a n d s . S o e r , G.J.R., 1980. E s t i m a t i o n o f R e g i o n a l E v a p o t r a n s p i r a t i o n a n d S o i l M o i s t u r e C o n d i t i o n s u s i n g Remotely S e n s e d Crop S u r f a c e T e m p e r a t u r e s . Remote S e n s i n g o f E n v i r o n m e n t 9, E l s e v i e r N o r t h H o l l a n d I n c . : pp. 27-45. T a y l o r , S.E., 1979. Measured E m m i s s i v i t y of S o i l s i n t h e S o u t h e a s t U n i t e d S t a t e s . Remote S e n s i n g of E n v i r o n m e n t 8, E l s e v i e r N-Holland: pp. 359-364. 12.10.

Additional reading

Bliamptis, E.E., 1970. Nomogram R e l a t i n g T r u e a n d A p p a r e n t R a d i o m e t r i c T e m p e r a t u r e s of G r a y b o d i e s i n t h e P r e s e n c e of a n Atmosphere. Remote S e n s i n g of E n v i r o n m e n t 1. h e r . E l s e v i e r P u b l . Cy I n c . : pp. 93-94. F e d d e s , R.A., 1971. W a t e r , Heat a n d Crop Growth. Commun. Agric. Univ. Wageningen, The N e t h e r l a n d s : 184 ppp. F r i e d m a n , J.D., 1970. The A i r b o r n e I n f r a r e d S c a n n e r i s a G e o p h y s i c a l R e s e a r c h T o o l . O p t i c a l S p e c t r a 1970 Vol 4 ; n r 6 : pp. 35-44. Goddard S p a c e F l i g h t C e n t e r , 1978. H e a t C a p a c i t y ?Tapping M i s s i o n (HCMM) D a t a Users Handbook f o r A p p l i c a t i o n s E x p l o r e r Mission-A (AEM), NASA: 120 pp. H e i l m a n , J.L., Kanemasu, E.T., Rosenberg, N.J. a n d M a d , R.L.. 1976. Thermal S c a n n e r Measurement of Canopy T e m p e r a t u r e s t o e s t i m a t e E v a p o t r a n s p i r a t i o n . Remote S e n s l n g of E n v i r o n m e n t 5, Amer. E l s e v i e r P u b l . Cy: pp. 137-145. H e i l m a n , J.L. and Moore, D.G., 1980. Thermography f o r E s t i m a t i n g N e a r - S u r f a c e S o i l M o i s t u r e u n d e r D e v e l o p i n g Crop C a n o p i e s . J o u r n a l of Applied M e t e o r o l o g y Vol. 19, No 3. Amer. M e t e o r o l o g i c a l SOC.: pp. 324-328. H e i l m a n , J.L. a n d Moore, D.G., 1982. E v a l u a t i n g N e a r - S u r f a c e S o i l M o i s t u r e

312 using Heat Capacity Mapping Mission Data. Remote Sensing of Environment 12. Elsevier Publ. Co, New York: pp 117-121. Hoop, D. de, 1977. Thermografie als hulpmiddel by Hydrogeologisch Onderzoek. Symposium Luchtwaarneming 1/2-09-1977, Delft, The Netherlands: pp. 89105. Hoppe, G.D. (ed.), 1972. Microwave Radiometry and its Potential Application to Earth Resources Surveys. European Space Research Organisation RAC-03R17: 104 pp. Idso, S.B., 1982. Humidity Measurement by Infrared Thermometry, Remote Sensing of Environment 12, Elsevier Scce. Publ. Co, New York: pp. 87-91. Kahle, A.B., Madura, D.P., Soha, J.M., 1979. Processing of Multispectral Thermal IR Data for Geological Applications. NASA, Jet Propulsion Lab., Pasadena, California, JPL Publ 79-89: 39 pp. Kiefer, R.W., 1972. Sequential Aerial Photography and Imagery for Soil Studies. Highway Research Record 421. Remote Sensing for Highway Engineering: pp. 85-92. Koolen, A.J., 1979. Temperatuurbeelden van onbegroeide grond. Op weg naar Landbouwpraktijk? Landbouwkundig Tijdschrift pt 91 nr 9, KGL, The Netherlands: pp. 258-264. Kumai, R., Silva, LeRoy, F., 1973. Emission and Reflectance from Healthy and Stressed Natural Targets with Computer Analysis of Spectroradiometric and Multispectral Scanner Data. The Lab. for Applications of Remote Sensing. Purdue Univ., Indiana, LARS Information Note 072473: 211 pp. LeSchack, L.A. and Kerr del Grande, N., 1976. A Dual-wavelength Thermal Infrared Scanner as a Potential Airborne Geophysical Exploration Tool. Geophysics, Vol. 41, No 6: pp. 1318-1336. Loor, G.P. de, 1969. Possibilities and Uses of Radar and Thermal Infrared Systems. Photogrammetria 24. Elsevier Publ. Cy, Amsterdam: pp. 43-58. Monteith, J.L., 1973. Principles of Environmental Physics. Wiliam Clower & Sons, Ltd., London: 241 pp. Nieuwenhuis, G.J.A., 1980. Remote Sensing en het onderzoek naar de Waterhuishouding van Landbouwgewassen. Cultuurtechnisch Tijdschrift 19/5: The Netherlands: 10 pp. Oetjen, R.A., Bell, E.B., Young, J. and Eisner, L., 1960. Spectral Radiance of Sky and Terrain at Wavelengths between 1 and 20 microns. Instrumentation. Journal of the Optical SOC. of America, Vol. 50, Nr 12: pp. 1308-1313. Pratt, D.A., Ellyet, C.D., McLauchlan, E.c. and McNabb, P., 1978. Recent Advances in the Application of Thermal Infrared Scanning to Geological and Hydrological Studies. Remote Sensing of Environment 7. Elsevier North Holland Inc.: pp. 177-184. Pratt, D.A., Foster, S . J . and Ellyett, C.D., 1980. A Calibration Procedure for Fourier Series Thermal Inertia Models. Photogrammetric Eng. and Remote Sensing Vol. 46, No 4: pp 529-538. Price, J.C., 1980. The Potential of Remotely Sensed Thermal Infrared Data to infer Surfaae Soil Moisture and evaporation. Water Resources Research, Vol. 16 No 4: 787-795. Price, J.C., 1981. The Contribution of Thermal Data in Landsat Multispectral Classification. Photogrammetric Engineering and Remote Sensing, vol. 47, No 2: pp. 229-236. Quiel, F., 1975. Thermal/IR in Geology. Some Limitations in the Interpretation of Imagery. Photogrammetric Engineering and Remote Sensing, 1975: pp. 341-346. Rosema, A., 1974. Simulation of the Thermal Behaviour of Bare Soils for Remote Sensing Purposes. 7th Int. Seminar Heat and Mass Transfer in the Environment of Vegetation, Dubrovnik: 13 pp.

313 Rosema, A., 1975 a. A Mathematical Model for Simulation of the Thermal Behaviour of Bare Soils based on Heat and Moisture Transfer. NIWARS publ. No 11, Delft, The Netherlands: 92 pp. Rosema, A., 1975 b. Heat Capacity Mapping, is it feasible? Proc. 10th Int. Symposium on Remote Sensing of the Environment: 12 pp. Savigear, R.A.G. e.a., 1975. Multispectral Scanning Systems and their Potential Application to Earth Resources Surveys. Earth Science Applications ESROIESTEC Contract No 1673172, Neuilly, France: 202 pp. Schaerer, G., 1974. Passive Sensing Experiments and Mapping at 3.3 mm Wavelength. Remote Sensing of Environment 3. her. Elsevier Publ. cy, New York: pp. 117-131. Schneider, S.R., McGinnis, D.F. Jr. and Pritchard, J.A., 1979. Use of Satellite Infrared Data for Geomorphological Studies. Remote Sensing of Environment 8, Elsevier North Holland Inc.: pp. 313-330. Sellin, L. and Svensson, H., 1970. Airborne Thermography. Geoforum 2, Journal of Physical, Human and Regional Geosciences, Pergamon, Vieweg, Braunschweig, Germany: pp. 49-60. Smith, J.A. e.a., 1981. Thermal Vegetation Canopy Model Studies, Remote Sensing of Environment 11, New York: pp. 311-326. Spiro, I.J. (ed.), 1976. Modern Utilization of Infrared Technology 11. Proc. of the SOC. of Photo-Optical Instrumentation Engineers. August 26-27, San Diego, California: 230 pp. Thackrey, D.E., 1973. Research in Infrared Sensing. In: The Surveillant Science. Remote Sensing of the Environment ed. by R.K. Holz, Houghton Mifflin Cy, Boston: pp. 209-219. Torres, Cl., 1973. La Thermographie. Questions, Techniques et Problemes de l'hterpretation: Revue Photo-interpretation 1973-2/3, Editions technip, Paris: pp. 48-73 et pp. 32-55. Verstappen, H.Th, 1977. Remote Sensing in Geomorphology. Elsevier Scientific Publ. Cy, Amsterdam: 214 pp. Vincent, R.K., Rowan, L.C., Gillespie, R.E., Knapp, C., 1975. Thermal-Infrared Spectra and Chemical Analyses of twenty-six Igneous Rock Samples. Remote Sensing of Environment 4. her. Elsevier Publ. Cy Inc.: pp. 199-209. Vincent, R.K., 1975. The Potential Role of Thermal Infrared Multispectral Scanners in Geological Remote Sensing. Proc. of the IEEE: pp. 137-147. Watson, K., 1971. Geophysical Aspects of Remote Sensing. Proc. of the Int. Workshop on Earth Resources Survey Systems, NASA SP 28312: pp. 409-428. Watson, K., 1974. Geothermal Reconnaissance from Quantitative Analysis of Thermal Infrared Images. Proc. 9th Int. Symposium on Remote Sensing of Environment, Univ. of Michigan, Ann Arbor: pp. 1919-1932. Watson, K., 1975. Geologic Applications of Thermal Infrared Images. Proc. of the IEEE: pp. 128-137.

314 13.

ACTIVE SENSOR SYSTEMS

Active sensors supply their own source of energy to illuminate features of interest. A common example is a photocamera used with flash bulbs. The main active systems for remote sensing are:

-

Lidar or Laser systems;

-

Radar (or Radio Detection And Ranging).

These active systems are like the thermal Infrared systems capable of day and night operation. Radar was extensively used by

the military

during World War I1 but its

application has spread since then to many purposes. There are two features that distinguish Radar from other remote sensing techniques:

-

it uses Microwaves which are capable of penetrating the atmosphere under poor weather conditions (e.g. clouds, haze, rain and snow);

-

the wavelengths used for radar are large when compared to Visible and Infrared, and consequently surfaces have to be relatively rough to produce diffuse reflection; surfaces that appear rough in the Visible may be smooth for Microwaves.

13.l.Laser systems The Laser systems or Lidars operate in the short wavelength portion of the EMS: UV, Visible and NIR. The information about Lidar systems given below is extracted from the review on Remote Sensing Instrumentation by MacDowall (1972). The radiation is emitted from a laser unit either in pulses or continuous waves; the scattered radiation is collected by an optical system. The laser, used as a source of radiation for the Lidar, produces a very narrow coherent beam: a beam width of 0.1

mRad is not unusual. Consequently, a very high

resolution is achieved. Since this is an active system, it is capable of day and night operation. F o r day-time use, precautions must be taken to eliminate sunlight from the returns. Since the laser light is monochromatic, sharp filters at the laser wavelengths can be used for this purpose. However, owing to its short wavelength, lidar is not able to penetrate clouds.

315

Three different types of aircraft Lidars can be mentioned:

-

the Laser Profiler or Altimeter; the laser emits either a pulse or a continuous wave of light which is directed straight down to the earth below the aircraft; in this way a profile of the terrain can be obtained;

-

Reconnaissance or Mapping Lidar; the laser beam is swept across a strip of terrain either directly beneath,

OK

to the side of the aircraft and

perpendicular to the flight path; the scattered or reflected radiation is measured and recorded in a way very similar to a scanner;

-

Raman and Fluorescence Lidar Systems; the radiation from the laser is used to excite the materials of interest; the resulting fluorescence and Raman emissions are recorded, and are unique for each type of material; these lidar systems generally operate in the UV range and therefore are seriously hampered by haze.

Collis

and

Russell

(1976)

report

about

applications

of

Lidar,

being

profilometry for topographic mapping, bathymetry (see Hickman and Hogg, 19691970), water turbidity observations and atmospheric probing. For technical information, the reader is referred to Johnson (1970).

13.2.Radar

systems

Radar is an active system which applies short pulses of energy in the Microwave portion of the EMS. The Microwave region of the EMS extends from wavelengths of 1 mm to several metres (see Fig. 2.2). the 0.75-100

Most radars operate in

cm wavelength zone. The band designations used in the USA are

listed in table 13.1.

A l s o the frequencies are given, since they are applied

very often for designation of spectral bands in the Microwave region. Table 13.1 Radar band designations after Long (1975). Band Frequency P L S C

X K, K

K,

300-1,000 MHz 1,000-2,000 MHZ 2,000-4,000 MHz 4,000-8,000 MHz 8,000-12,500 MHz 12,500-18,000 MHz (12.5-18.0 GHz) 18.0-26.5 GHz 26.5-40.0 GHz

Wavelength 30-100 15-30 7.5-15 3.75-7.5 2.4-3.75 1.67-2.4

cm cm cm cm cm cm

1.1-1.67 0.75-1.1

cm cm

316

Radar systems may or may not produce images; they may be groundbased or mounted in aircraft or spacecraft. A common form of non-imaging radar is the Doppler radar system used to measure vehicle speeds. The so-called Doppler effect concerns the alteration of frequency caused by relative motion between observer and source. The observer receives re-radiation at a different frequency (f') as compared to the (fixed) frequency of a moving source (f): f' is greater than f for approaching sources and is smaller than f for receding sources. Another form is the "plan position indicator" radar. This system has a display screen on which a radial sweep indicates the position of objects producing radar echoes (Lillesand and Kiefer, 1979). Many imaging radars used for remote sensing are real-aperture Side-Looking Airborne Radars (SLAR).

The antenna points to the side with a beam that is wide

vertically and narrow horizontally. A short pulse strikes a target and a signal returns to the radar antenna. The time delay associated with the signal sent and received (echo), gives the distance between target and radar. The picture presented in fig. 13.1 illustrates a return for a particular instant of time of strong signals coming from a.0.

trees and a sloping edge, while no signal is

coming from a radar shadow area. In the imaging radar, the signal return is modulated and transferred via a lens to a film. The film i s in the form of a strip that moves synchronously with the motion of the aircraft, s o that as the aircraft moves forward the film also moves. When the aircraft has moved one beamwidth forward, the return signals come from a different strip on the ground and produce an image line on the film adjacent to the preceding line. The images are comparable with those from a strip camera or an optical scanner. The geometric aspects of SLAR operation are summarized in fig. 13.2. The slant range (SR)

to any given object is given by (Lillesand and Kiefer,

1979) :

SR

=

ct 2

where c

=

(13-1)

speed of Em,

t = time between pulse transmission and echo reception; the factor 2 i s

introduced, because the time is measured for the pulse to travel both the distance to and from the target.

-

317

Recorder

S l o p i n g Edge

Scrub Growth (Brush, Grass, Bare Earth, e t c )

Fig. 13.1 Principle of Side-Looking Airborne Radar after Ulaby et al., (1981).

swath Fig. 13.2 SLAR geometry (modified) after Moore et al. ( 1 9 7 5 ) . a = depression angle 9 = angle of incidence or grazing angle SR = slant raFge GR = (SR2-h2) B = angular beam width. (Used by permission of Am. Soc. for Photogrammetry and Remote Sensing.) For Microwaves, the resolution is usually meant to b e t h e half-power response

318 width of the measuring system. Fig. 13.3 illustrates the kinds of resolution possible with Microwave sensors. The active systems can distinguish objects by angle, range and speed resolution, whereas the passive system is restricted to angle resolution alone. The angle resolution of a radar system is determined by the angular beamwidth of the antenna. According to Innes (1973) there is an easy rule which relates the aperture (A), as expressed

by

the number of wavelengths ( N X ),

with

the angular

beamwidth ( 6 ) : A

=

N. X than 6

=

1/N of a Radian.

( 13-2)

From (13-2) it can be concluded that in principle both shorter wavelengths and larger antennas may be used for improvement of angular resolution. The possibilities, however, are limited owing to atmospheric effects at shorter wavelengths

(see

fig.

2.15

and

2.16)

and

problems

connected

with

the

application of large antennas on aircraft. The resolution of the system can be improved through application of angle and range resolution together (fig.

13.3b).

By comparing the frequency of the

transmitted signal with that of the received frequency, the Doppler frequency shift, which is directly proportional to the relative speed of the aircraft and the point on the ground, can be observed. Using angle and speed resolution together, the size of the resolution cell becomes smaller (fig. 13.3~). Fig. 13.3d shows furthermore the resolution cell reached when range and speed resolution are combined. The SLAR described in Fig. 13.1

is a Real Aperture Radar (RAR),

where

resolution is determined by the actual length of the antenna aperture. Since antenna length is physically limited when using aircraft, most of the realaperture SLAR use wavelengths between 3 and 0.8 cm to achieve beamwidths in the order of milliradians (Moore et al., 1983).

The resolution of these systems is

generally described by the so-called slant range or cross-track resolution and perpendicular to the slant range direction by the along track or azimuth resolution. The pulse duration and depression angle determine the spatial resolution i n the direction of wave propagation, the slant range direction. The ground resolution

319

I

!

\ \

/

beam- contourAngle resolution alone, used by a l l passive and some a c t i v e sensors

F i r s t null contour I

/

\ \

beam c o n t o u r - \

-

Angle and speed resolution. Active sensors only.

A

A

/--\ - --

/

W 5 e s o l u solu t i o n 1/ cc c e 11 ll power speed> response contouy. , \

-

____----

_-//

1----

2 power range Lresponse contour

1 / 2 power ' range

response contour

Angle and range resolution together. Active sensors only.

Range and speed resolution together. Active sensors only.

Fig. 13.3 Resolution techniques used in Microwave sensing (Moore, 1983). (Used by permission of Am. S O C . for Photogrammetry and Remote Sensine.) in this direction (R,)

R

=

is found from (Lillesand and Kiefer, 1979):

cT 2cosa

where T a

=

-

(13-3)

pulse duration, depression angle or angle between the horizontal platform plane and

the line connecting the radar antenna and the object being sensed.

320 The along track resolution is determined by the angular beam width of the antenna ( 6 ) and the ground range (GR).

As the antenna beam fans out with

increasing distance

the along

from

the aircraft,

track

resolution (Rt)

decreases. It is given by (Lillesand and Kiefer, 1979): Rt

=

( 13-4)

GR.6

A typical resolution profile for a high resolution SLAR is given in fig. 13.4.

25

20

15 10

A l t i t u d e , 6150 m 0

10

5

15

20

Ground r a n g e (km)

Fig. 13.4

Typical resolution profile for high resolution SLAR after Moore et al. 1975. (Used by permission of Am. SOC. for Photogrammetry and Remote Sensing.) From this figure the following data are extracted: direction

ground resolution at distance from aircraft of 5 km 10 km 15 km 20 km

slant range along track

15 m 8.5 m

The

early

radar

12 m 10.5 m

systems

made

10.5 m 16 m

11 m 13 m

use

of

non-coherent

radiation.

The

application of radar in satellite systems made it necessary to develop coherent radar with fine resolution. Furthermore, it became possible to use specific signal processing techniques.

321 The resolution problems of real-aperture SLAR are overcome in Synthetic Aperture Radar (SAR).

These systems employ a very short antenna but through

modified data recording and processing techniques they synthesise the effect of a very long antenna e.g.

a 2 m antenna can be made effectively 600 m long. In

S A R , return signals from the center portion of the beamwidth are discriminated

by detecting Doppler frequency shifts. A Doppler shift is a change in wave frequency as a function of the relative velocities of a transmitter and a reflector. Within the wide antenna beam, returns from features ahead of the aircraft will have upshifted (higher) frequencies, and returns from the area behind the aircraft will have downshifted (lower) frequencies; returns from the center portion of the beamwidth will experience little

OK

no frequency shift.

Through the use of range resolution by processing the return signals according to their Doppler shifts, a very small effective beamwidth can be generated. Consequently, larger wavelengths may be applied in SAR than in RAR. Different modes

of

polarization may

be

applied

in transmitting and

receiving. A radar signal can be transmitted either in horizontal (H), or vertical (V) linear polarization. Also circularly polarized radar waves may be produced. For linear polarization there are four different combinations:

-

H send, H receive

(OK

HH); H send, V receive

(OK

HV);

V send, H receive

(OK

VH); V send, V receive

(OK

VV).

HH and W data can be transformed in so-called like-polarized imagery, while from HV and VH data so-called cross-polarized imagery can be produced. The fundamental equation showing the amount of signal received by a radar system from a particular target is called the radar equation, which may be written as follows (Skolnik ed., 1970, Long, 1975): P G p I-

=-

aA

t t

K

4n(SR)’

-

( 13-4)

where Pr

=

power received, Wm-2,

Pt

=

power transmitted, Wm-*,

Gt

=

the gain of the transmitting antenna in the direction of the target,

SR

=

the slant range to the target (distance in m from radar to target),

=

the effective aperture of the receiving antenna in m2,

U =

the effective backscattering area of the target or radar cross-

section (RCS) in m2, that is the actual cross section of a sphere which,

322 when placed in the same position as the target, would scatter back to the radar the same amount of energy as is returned by the target.

In equation 13-4, the first quantity

PtGt -

gives the power per unit area

4n( SR) transmitted to the target, the second quantity determines the energy reradiated by the target with a RCS u of eq. 13-4,

except u

,

. All of the factors on the right hand side

are under control of the radar designer;

a

describes

the target. Using the same antenna for transmission and reception, Gt and A, are related by (de Loor, 1976): ( 13-5)

where

X

Two

=

wavelength.

definitions are in common use, being the differential scattering

coefficient ao and the return parameter y: ao =

01s

where uo

( 13-6)

is the RCS per unit illuminated surface-area S, which is determined

by the grazing angle ( 0 )

,

the width of beam ( B ) ,

the slope and the orientation

of the target; y

=

( 13-7)

o/si

where y is the RCS per unit projected area Si, being the area normal to the direction of propagation of radiation illuminating the area. Both uo usually expressed in dB (x dB dR).

S

=

10 log x

e.g.

x

as well as Si are considered to be planes,

=

u

1 or

o

dB, x

=

and y are

1,000 or 30

can be understood to

be composed of S enlarged by the surface roughness of the target (considering surface scattering only). Some examples of SLAR and SAR systems are given below (see Ulaby et al., 198182) :

323

System

Real-aperture SLAR: ANIAPQ-97 Motorola ANIAPS-14D S A R : Good year GEMS Seasat S A R

13.3.

Pixel (m) at 6 km altitude GR=5km GR = 20 km

wavelength (cm)

0.86 3.2

8.6 x 14.1 23.0 x 9-4 60.1 x 46.8 161 x 31.3 nominal pixel dimension (m) 15 x 15 6.25 x 25

3 25

Interaction of Microwaves with objects at the earth's surface The target properties that determine the reflection of radar waves are:

surface roughness, slope and orientation, and dielectric properties. Moore (1976)

points to the great influence of resonant sized objects. For

example, gratings or fences may produce strong radar signals. Surface roughness The so-called relative surface roughness has been defined by the smooth criterion of Rayleigh (2-23).

Ulaby et al.,

(1982)

propose the so-called

Fraunhofer criterion to explain the scattering behaviour of natural surfaces in the Microwave region. According to this criterion a surface is smooth if ( 13-8)

This criterion appears to be consistent with experimental observations, while

the Rayleigh criterion is not. Surface roughness may be described by the standard deviation of surface height (uz) relative to a reference surface (x-y plane). Consider a surface with a point that has a height z (x, y) above the x-y plane. The standard deviation of the surface height,

uz

, is

then given by: (13-9)

where

Z

is the mean height of the surface and

Angular response curves for uo measurements at 1.1

GHz for five bare-soil fields with approximately the same

soil-moisture content but with different u The effect of surface roughness on uo 1)

y2 is the second moment.

(scattering coefficient, 13-6) based on

shows a rapidly decreasing

are given in fig. 13.5.

is evident: the smoothest surface (field

with increasing angle of incidence, the

roughest surface (field 5) exhibits only a small variation between nadir and

324

30" incidence.

20 15

h

M v -0

10

0 0

+J ra

5

.r

V

;re; o a

0 0

-5

cn S

'i: -10 a, +

c,

-15 v)

-20 Pol ari za t Frequency

-25

0

5

10

15

20

25

30

Angle o f incidence (degrees) Fig. 13.5 Angular response curves of the scattering coefficient at 1.1 GHz for five bare-soil fields with different surface roughness (Ulaby et al., 1978). (Copyright 1978 IEEE.) If a smooth surface happens to be perpendicular to the incident radar beam, then the return signal is intense. However, if a smooth surface is at any other angle to the radar beam, none of the energy is returned to the antenna, but is specularly reflected into space. Conversely, rough surfaces of land as well as water scatter the incident energy in all directions, thus returning some of it to the antenna. Agricultural fields ploughed in one direction show a regular surface roughness. In that case, the orientation of the furrows is decisive for the roughness experienced by the incoming radar waves and the intensity of the return signal.

325

Slope/orientation

It can be concluded, that the surface illuminated (S) is determined by the sensor parameters (direction of illumination and depression angle) as well as by the slope and orientation of the target. The surface illuminated is relatively small when slopes are pointing towards the sensor and relatively large when slopes are facing away from the sensor. Hence, in the former case the energy will be piled up in the reflected signal, while in the latter case it will be spread out. Therefore, the former results in a strong return signal and the latter in a weak. Orientation plays an important part in scattering from vegetation canopies. Large leaves of which the surface normals are turned towards the radar will exhibit a relatively large scattering coefficient. Dielectric properties General considerations The dielectric properties of terrain features are important in determining the intensity of radar returns. From the data in table 13.2, the strong influence of the moisture condition of soil on the conductivity values and dielectric constants is evident. The results obtained by Cihlar et al., (1974) and Schmugge et al., (1978) are given in fig. 13.6(a) Fig. 13.6(a)

and (b) respectively.

indicates that an increase in soil moisture leads to an increase

of the dielectric constants. Also the scattering coefficient energy (f

=

4 GHz or

X

=

( 0 ' )

of radar

7.5 cm) increases with the soil moisture content

(fig. 13.6b). The radar energy, being incident upon the surface of a homogeneous soil medium, which is not reflected at that surface, is travelling through the medium; energy is lost by absorption as well as scattering. The so-called extinction coefficient, or power attenuation coefficient (Ke), is the sum of the power absorption coefficient (K,)

and the power scattering

coefficient (Ks): K = K + K e a s

P - P where K = o e P D 0

(13-10)

326 Table 13.2 Conductivity (.a) and dielectric contents (E' and E") of soil and water at different wavelengths of EMR ( A ) after Long (1975, adapted from Kerr, 1951).

x

U

E'

E"

mho /m

Medium 3 m

Sea water

-

20' - 25°C 28'C Distelled water, 23°C Fresh-water lakes

20 cm 10 cm 3.2 cm 3.2 cm l m 9 cm 9 cm l m

Very dry sandy loam Very wet sandy loam Very dry ground Moist ground Arizona soil Austin, Tex., soil, very dry

4.3

80

6.5

69 65 67 80

16 12 - 3 -2 10 -10

3.2 cm

0.03 0.64 10-2 10 0.10

3.2 cm

0.0074

l m

2 24 4 30 3.2

774 52 39 30.7 23 0.06 0.60 1.62 32.4 0.006 0.06 0.19

2.0

0.014

Note: for laboratory measurements of the complex dielectric constant of soils, the reader is referred to Wiebe (1971). P = power at depth D (m).

Other concepts are the penetration depth and Skin depth. The penetration depth

may be defined as the depth at which the power has been reduced to

u

l / e of its original value. If scattering in the soil medium is ignored: = -1

N

Ke = Ka

=

2 a and 6

P

( 13-1 1)

2a

where the field attenuation coefficient a

=

2n -

Im [GI

,

xO

Xo

is the wayelength in free space and

E

is the relative complex dielectric

constant (h= imaginary part of). For materials with

E"/E'

<

0.1 (see 2-11 up to and including 2-16)

,

Ulaby e t

al. (1982) give the following formula for 6 : P

6

-a@

P =-

2nE"

(13-12)

327

2 CI lu VI S

2826-

Frequency: 4.0 GHz S o i l type: sand loam clay

I

I

- ----2 200

24-

V

x

c,

22

V

/

I I

W

18-

.. ..

W

.? 1 6 -P 2 14W tx

12

-

10

=

8-

Imaginary part

6 -

-15

Soil moisture (g/cm

Fig.

13.6

Polarization: HH Frequency (GHz) : 4.25 0 Angle o f incidence ( ) =10 RMS Height d : 1.1 - 4.1 cm

3 s o i l moisture content (g/cm )

3

Dielectric constants and scattering coefficient as a function of soil moisture content. a) dielectric constant values after Cihlar et al., (1974) b) scattering coefficient as a function of Moisture content for bare soil with different surface roughness after Schmugge et al.. (1978).

which is applicable to most natural materials except for water. The

penetration =

2 6

=

depth

l / a (see 2-13)

should

.

not

P The measured scattering coefficient

be

oo

confused

with

the

skin

depth

is plotted in fig. 13.7 against skin

depth and the corresponding effective attenuation coefficient a

(In Nepers

cm-I or Ln A1/A2 per cm-' where A1 is amplitude of the original signal and A2 of the return signal; 1Np=8,685dB).

It can be concluded that oo increases

almost linearly at all incidence angles with the attenuation. The increase is highest at low incidence angles (measured from the vertical).

In nature, both

surface and

volume

scattering are

usually

present

contribute to the return signal of incident radar energy. However, it may be

and

328 Frequency 7.1 GHz P o l a r i z a t i o n HH Incidence angle O0 0 -.. 1oo 20° -30°

24 20

0

.

16 12

A

a f

8

-.

/

60° 70'

/'

/.

0

/'

. /'.

/

loo

./,

/ /"

/'

/

/

4

//.

0

-- 50'

______

/.

//'

40'

V-

oo

/

/

/o /..

0

-4 -8 -12

-16 C I

I

J

1

1 .o 1.5 A t t e n u a t i o n ae i n Nepers (cm)

0.5

I

I

8.0 4.0

2.0

1 .o 6 S k i n depth

0.7

(cm)

Fig. 13.7 Scattering coefficient as a function of attenuation and skin depth after Ulaby et al. ( 1 9 7 4 ) . convenient to ignore one or the other of these. For example, in the Microwave region, sea-water has a large

E

and is treated as a homogeneous medium capable

of surface scattering only. At optical wavelengths,

E

of sea water is much

smaller and dust particles in the water can make volume scattering important. Also wet soil may be assumed to show mainly surface scattering. In surface scattering, the scattering strength is proportional to

E

of

the medium at the surface and the angular scattering pattern is governed by the surface roughness. In volume scattering, the scattering strength is proportional to the average

E

of the volume and to the discontinuities inside the

329

medium, the angular scattering is determined by the roughness of the boundary surface, the average

of the medium and the geometry of inhomogeneties (see

E

Ulaby et al., 1982). A qualitative illustration of the dependence of u0

in volume scattering on the

average dielectric constant of media is given in fig. 13.8. large

E

show a

lower uo

at high angles of

backscattering curve for volumes with large

Both a small and

incidence but

the angular

drops faster than for small E

E

media. 0 0

u

I

m

20

0

40

60

Angle o f i n c i d e n c e

80

8 (degrees)

Fig. 13.8 Dependence of the volume backscattering coefficient on the average dielectric constant (after Ulaby e.a., 1982). For the radar frequencies of 1.3 GHz, 4.0 GHz and 10.0 GHz, Ulaby et al., (1982) present some curves that provide understanding of the lower boundary of moisture content, at which surface scattering dominates over volume scattering (fig.

13.9).

The 4- and 10-GHz ( A

=

7.5 and 3 cm)

curves show that surface

scattering is the main contributor to scattering of this radiation at moisture conditions above 0.05 g/cm3. Greater penetration is reached with 1.3 GHz radar waves even at relatively high moisture contents. Determination of Soil moisture Fig. 13.5 showed for 1.1

GHz that uo

of the rough surface (field 5) is

approximately independent of the angle of incidence. Analyses in the 1-8 GHz region indicated that for 5 GHz ( A

=

6 cm)

, either

HH or W polarization, the

effect of surface roughness as well as the vegetation cover is at a minimum in the 7-17" range (angle of incidence) while the sensitivity of uo

to soil

330

I

Fig. 13.9

I

I

Penetration depth in loamy soil as a function of moisture content (after Ulaby e.a., 1982). is strong (Ulaby e.a.,

moisture content

1982).

Therefore, this range is

suitable for measurements of soil moisture. Soil moisture content should be expressed in mf, the percent of field capacity (here moisture at 1/3 bar soil tension) :

-+ m

mf

100 x

m

= 100

g

(13-13)

x FCV

where the graviometric (g) and volumetric ( v ) moisture contents are given for the actual moisture contents (m) and

at field capacity (FC).

Empirical expressions were derived by Schmugge (1980) relating FCg and FCV to the soil texture of his sample set: FC = 25.1

-

0.21s

FC,,=

-

0.0023s

g

0.30

+

0.22C percent by weight

(13-14)

+

(13-15)

0.005C g

where S and C are the percentages of sand and clay particles in the soil

331 samples. Fig. 13.10 shows the response of uo to mf of the top 5 cm layer of bare soil.

Frequency (GHz): 4.5 Polarization : HH Angle of incidence 8 (degrees): 10 Bare s o i l data: I 1 f i e l d s with d i f f e r e n t Soil types and surface roughnesses

18 12

-

m

6

U

v

owl 0

0

-6

2+:

-12

0

-18

- 24

I

0

25

-..'

(dB)=0.148 mf-15.96 N=181 p=O .85 I I

50

75

100

A

Multiple data points 1974 1975 1977

125

150

Soil moisture of Top 5 cm l a y e r , mf ( % o f f i e l d c a p a c i t y )

Fig. 13.10 Measured backscattering coefficient of bare soil as a function of mf for a variety of soil surface-roughness conditions and soil textural compositions (Ulaby et al., 1982). The data shown were measured at 0 =loo and f around 4,5 GHz and include a wide variety

in

surface

roughness

conditions

as

well

as

in

soil

textural

composition. The last square linear regression between uo (d B) and mg ( X ) is given by: uz(d B)= 0.148 mf- 15.96

(13-16)

where uo is uo of bare soil and the linear correlation coefficient is equal to 0.85. Similar studies were conducted for fields planted in milo, corn, soybeans and wheat. Data of these four types of crops observed over a wide range of soil moisture conditions and plant-moisture and plant-height variations, are given

in fig. 13.11. The least square linear regression is given by:

332 (13-17)

u0 (dB)= 0,133 mf- 13.84 can

where uo is uo of the canopy and the linear correlation coefficient is equal can to 0.92. I I 1 I I I 18 Vegetation data 12 - A Corn

-

-

6 M -0

0 -

v

0

b

-6

-

-12

-

-18-

Frequency (GHz) : 4.5 P o l a r i z a t i o n : HH Angle o f i n c i d e n c e 0 (degrees): 10Oo(dB) = 0.133 mf - 13.84

N = 143 p = 0.92 I

13.4

I

I

I

1

I

*

Ground penetrating radar. Johnson

et

al.,

(1980)

report

(Geophysical Survey Systems Inc.) ground penetrating radar

OK

about

the

application

of

the

GPR. The GSSI system is an impulse radar which

radiates repetitive pulses at frequencies between 80 and 1000 MHz ( A 375

cm)

GSSI

radar in soil survey, also indicated as = 30

-

into the earth. The transmitted radar signals are scattered from

various interfaces within the ground and picked up by the radar receiver. The interfaces may be different soil horizons, soil/rock interfaces, or other materials with contrasting dielectric properties. Organic matter, salt content, clay mineralogy, particle size and moisture content are some soil properties affecting the dielectric properties. A s the antenna is moved along the surface, a recorder produces a graphic record

along a traverse. For rapid exploratory work the antenna may be towed at speeds up to 8 km/hr.

333

The choice of frequency is an important consideration. Generally, low frequency radiation propagates to the greatest depth, but high frequency radiation produces better resolution. The choice depends on the soil conditions and purpose of study. The GPR signals commonly penetrate to depths of 3 to 10 m, but at some sites penetration as deep as 20 m has been achieved. The depth of penetration is reduced if the soil is saturated with water and/or contains an appreciable amount of silt

OK

clay. Soils with a high content of montmorillonite are highly

attenuative and penetration may not exceed 1 m.

Similarly radar does not

penetrate deeply in soils with a high salt content. The GPR signal StKUCtUKe consists of the following basic components:

-

a strong surface reflection immediately following the transmitted pulse;

-

the reflection of an interface at a time equal to the pulse travel time from

the transmitted pulse, which serves as a time reference;

the surface to the interface and back to the antenna. The graphic recorder produces an image by printing strong signals in black and weak signals in the grey range. The travel time (t) may be converted into a depth scale if the velocity of propagation in the penetrated material (Vm) is known ( s e e also 13-1):

( 13-8)

where D

=

depth in m, c = velocity of EMR m s-l,

t

=

pulse travel time in ns

f

=

relative dielectric constant of material Fm-l,

Vmr

=

velocity of propagation in the material = c/ 5 m s - l .

The GPR has been found to be capable of detecting changes of some diagnostic

soil horizons such as albic, spodic and argillic horizons A slight increase of texture, however, was not recorded. The same applies to

the capillary fringe, forming the upper edge of the water table. However, a water table in coarse, sandy and gravelly soils is usually detected.

334 300

The

MHz

frequency

( A =

100 cm)

provided excellent data.

Yet, the

properties of the upper 38 cm, including the A horizon were masked by the first strong surface reflection. Higher frequencies can be used to minimize this dead zone.

13.5. Vegetation backscattering. The canopy backscattering coefficient includes contributions from the vegetation cover and the soil surface as well as from multiple scattering caused by interactions between the vegetation volume and soil surface. Attema and Ulaby (1978) proposed that the canopy volume can be represented by a cloud of

water

particles per unit volume with -1 (m ) may then be expressed by:

mass

%.

The

extinction

coefficient K K = A

e

(13-19)

m 1 v

where A1 is a constant at a given frequency which is different for different crop geometries and

is

the sum of

the volume absorption and scattering

coefficients. The latter is a function of the shape and size of the real scattering elements (leaves, stalks and fruit). Van Kasteren and Smit (1977) discuss measurements on the backscatter of Xband radiation of a number of crops. They concluded that only a complex of (mainly geometrical) parameters (e.g. distance, amount of scattering

leaf size and distribution in space, row

soil surface not covered by

differences

found

between

crops.

crops)

Comments

can explain the

are

given

on

the

dependence of scattering from crop canopies as related to soil tillage and growing stage. Some of these are quoted below:

-

potatoes grown in rows (the incident waves directed perpendicular to the direction of rows);

at the start of the growing season, the waves are

scattered back by the walls of the ridges and a high reflection is obtained, especially at high grazing angles; later on an irregular structure of the canopy arises and angular dependency disappears;

-

cereals (at the start of the growing season); the scattering for all angles is nearly the same; as the height and coverage of thz crop increase, a

scattering pattern arises that is more angular dependent. Radar may be used for classification of crops. Bush and Ulaby (1978) suggest, that for the best classification accuracy of crops, the band of

335 approx. 14 GHz, a dual polarized system, and viewing fields at off nadir angles

in the 40"

to 6 0 "

range, should be employed.

To

attain

classification

accuracies exceeding go%, multidate acquisition is required. (precision of 1 dB or better)

Furthermore, the radar system has to be accurate and differences originating from

speckle have to be avoided. This can be done

by the calculation of average reflected levels per agricultural field in data processing (Hoogeboom, 1982). 13.6.

Radar image characteristics. Radar records the distance of the radar source to a reflecting object e.g.

the distances OS, OT,

OV and OW in fig. 13.12.

The image is constructed by

circling each object-point, taking the radar source as a centre and the intersections with a l i n e as the image-points.

radar

imaqe l i n e

S'

T

T'

U'

U

X'

V' W'

W

X

Fig. 13.12 Flagpole-effect and shadow in radar imagery. a = angle of radar beam with horizontal, or depression angle.

In radar imagery there are typical effects: a.0.

the fold-over, or

flagpole-effect, and the radar shadow. The flagpole-effect causes the top of a high object to be registered before the bottom, hence the synonym of fold-over.

In fig. 13.12,

two flagpoles are drawn: ST and mi. S is located higher than T ,

therefore nearer to the radar source and will be recorded first; S I T ' is the echo difference of top and bottom. The echo difference increases when Z or h increases, but it decreases at a larger distance to the radar (SR = slant range): T'U'

V'W'

<

and W'X'

S'T'.

are the so-called radar shadows. In these zones behind the

336

obstacles (ST and VW), no details of the terrain are registered. At a greater distance of the radar source the length of the radar shadow increases ( W ' X ' T'U').

>

When comparing distances, the nearby distances appear to be suppressed

in real aperture SLAR. The radar image from a far distance approaches the real terrain configurations more accurately (Fig. 13.13).

Fig. 13.13.

Object space

Image space

(a)

(b)

Deformation in radar images after Innes (1973).

Airborne photography and mirror scanning have their imaging domain in the area within 45"

from nadir, that is up to a distance of 1.00

Z; radar is

complementary with regard to imaging when compared with these systems. In Fig. 13.14, 4.67

the coverage of the systems is compared; radar covers an area of

Z.

In Fig. 13.15, Fig. 13.15

a number of radar imaging aspects are given schematically.

(a) compares the perspective projection (using an optical centre)

with the radar projection. Deformation in perspective projection (e.g.

aerial

photography) increases radially from the optical centre. The deformation in radar projection at large a (=10-20"),

the "shaded"

a ( = 30-45")

is clearly demonstrated; at small

a more accurate projection of the terrain is derived. Note also area E'H' (F and G are in this area).

Piling up of energy takes place at slopes facing the radar, while slopes facing away from the radar show a spreading of energy. Compare: A'B' with B'C' (A'B' B'C').

<

The slopes facing the radar are pictured in bright tones, the slopes

facing away from the radar are presented in grey or black tones.

337

1.00 2

0

-1.00

2.75 Z

Z--1.75

5.67 Z

Z-

4.67 Z

4

4

Fig. 13.14 Terrain coverage with aerial photography and airborne scanning (1.00 2) and radar (4.67 2 ) after Innes ( 1 9 7 3 ) . Parallax is demonstrated in Fig. 13.15

(b).

The radar source is at the same

altitude and has the same scan direction, but is at a different distance from the terrain. For comparison the image line of R" a

=

20-45"

with B ' ,

and for

a

= 10-20"

is given above that of R' for

with G', as fixed points; such radar

images may be studied stereoscopically. Fig. 13.15

(c) gives a schematic picture of the influence of slope on radar

projection in relation to large a

a ; steep slopes show a fold-over in projection at

values.

Stereo SLAR imagery is discussed by Koopmans (1974);

to obtain a stereo

image a 6 0 Z sidelap is desirable. When using two overlapping strips with same scan directions but different altitudes, or one positive and one negative of two strips with opposite scan directions and from different altitudes, it is possible to fuse the images and to obtain a three-dimensional picture (an alternative way is given in fig. 13.15

b).

Koopmans (1974) gives formulae to

calculate the height from the parallax difference, making an approximation by considering the wave front as being straight instead of spherical. From fig. 13.16

the following equations can be derived to calculate the height

(h) of vertical objects from stereo imagery: a)

with same scan directions P -P = AP = h tg a2 2 1

h =

AP tga - tga 2

-

h tg a

1 (13-20)

1

338 photo 1 p e r s pec t ive p r o j e c t ion

B'

B ' D'

A'

A' C'

R

photo 4

photo 3

J

hl

radar projection

photo 2

/jo4

J,

F'

G' J ' K'

C'E'

K'

H' I ' J'

(a 1 a =10-20°

A =20-45' R"

B

I1

I1

I

I

C I8 I

E 'I

K'

L'

-

1

R'

B'

D'

B ' C'

R

(c> A Fig.

A

D

A

13.15Radar projection of different terrains: (a) compared with perspective projection, ( b ) from same altitude but at different distances, (c) fold-over of steep slopes (schematically).

339

for explanation see 13-21 b) with opposite scan directions AP = h tga

h =

+h

1

AP tga + tga 1

where

tga

2 (13-21)

2

AP is the parallax difference, and

a

1

and a2

are the depression

angles towards the top of the object.

Fig. 13.16

Radar parallax and slope measurement after Koopmans (1974). a) scanned from the same direction b) scanned from opposite directions

Equations can be derived to calculate the angle of slope of

the objects.

Depression angles are calculated from the flying-height and ground range towards the end of shadow. An error will be introduced when the shadow does not lie in the reference plane. Therefore, one is measuring an apparent slope which has to be corrected to a true slope.

13.7.

Interpretation of radar imagery. Landscape analysis with radar imagery is described by Nunnally (1969).

Banyard ( 1 9 7 9 ) uses aerial photographs of forest types as a photo-truth key for radar interpretation in training exercises for tropical foresters. Koopmans (1973)

discussed drainage system analysis on radar images. He con-

340

cluded that stereo radar is more reliable for this purpose than monoscopic radar. In studying radar imagery, he found that the drainage density obtained by monoscopic interpretation may be only 2 / 3 of that obtained from the study of stereo-radar. Furthermore, the junctions of tributaries to main rivers as well as the tracing of water-divides on monoscopic radar images is susceptible to relatively large errors and their delineation is best done with stereo-radar. The synoptic view offered by radar imagery is very valuable for geology, since the analysis of drainage pattern (and density) and geological structure may be performed over large areas. For geological interpretation of radar images the reader is referred to Mekel (1972). As

an

example

of

physiographic

interpretation,

the

monoscopic

interpretation of the radar image of fig. 13.17 is given in fig. 13.18.

A

first

division in landtypes is made, mainly based on the appearance of high lights and

radar shadows, or contrast in the images. The shadows are evaluated

according to their length. The high lights (as a result of piling up of energy) are related to slopes facing the radar and may be used together with the shadows in tone contrast. Rough terrain will be characterized by a high tone contrast. To avoid misunderstanding: also agricultural fields with different types of crops may be characterized by a high tone contrast. However, in fig. 13.18,

we are concerned with a relatively homogeneous dense cover of natural

vegetation. Further subdivision appeared to be possible in this case on the basis of ridge pattern and river system; drainage pattern was used here as a land characteristic not leading to further subdivision. The following conclusions are drawn on the basis of the data on the maps constructed by the Ministerio das Minas E Energia of Brasil (Projeto Radam, 1975) at a scale 1:1,000,000:

-

geology

-

the area consists mainly of rocks such as migmatites, gneisses,

granites, schists, quarzites; the parallel orientation of the ridges and the angulate drainage pattern are witness of metamorphic pressure at many places in the area during its geological history;

-

geomorphology - a table mountain and many areas with inselbergs bear witness

-

soils

to strong erosion in the past;

-

mainly Ultisols and locally Oxisols; Entisols and Inceptisols are

found in the valleys and on the footslopes. The scale of the final maps of the Radam Project does not allow a more detailed discussion on the value of the interpretation units for soil survey but it will

341

Radam Project, 13.17 Semi-controlled radar mosaic of part of SB.21-2-C. Rrasil (Ministerio das Minas E Energia, 1975). (Reproduction Projeto RADAM BRASIL.) be obvious that the interpretation units are meaningful for a first description Fig.

of the land. Furthermore the interpretation can be made in a relatively short

time

.

342 Legend of Fig.

13.18.

I n t e r p r e t a t i o n of p a r t of a s e m i - c o n t r o l l e d r a d a r mosaic

of t h e Radam P r o j e c t ( B r a s i l ) .

Ridge p a t t e r n Tone c o n t r a s t ...........................

B.

Steeply dissected land

1. v h 2. h

1.1. p a r a l l e l 1.2. s p e c k l e d 2.1. p a r a l l e l 2.2. s p e c k l e d

v v v v

speckled patchy (isolated hills)

h m

h h h h

DrainaEe pattern -------------C. Rolling t o h i l l y land

D.

Undulating l a n d a d j a c e n t t o Rivervalley land

1. v h 2. h 3. m v l

-

E. R i v e r v a l l e y l a n d

angulate angulate angulate

-

m

m 1 1

R i v e r systems -------------

1. tributary v 1 v a l l e y s w i t h adjacent f ootslopes 2. main r i v e r v 1 valleys A b b r e v i a t i o n s : v h v e r y h i g h , h h i g h , m moderate, 1 low, v 1 v e r y low.

Fig.

13.19 shows a S e a s a t

-

1 image of p a r t of The N e t h e r l a n d s . S e a s a t

o p e r a t e d i n t h e p e r i o d between 26 June 1978 and 21 November 1978. T e c h n i c a l a s p e c t s Seasat-1:

wavelength of r a d a r = 23.5 c m , r a d a r beam w i d t h =

6 " , IFOV= 25 m, swath w i d t h = 100 km, d e p r e s s i o n a n g l e a b o u t 70'.

A p o l d e r a r e a w i t h h i g h c o n t r a s t i n g p a r c e l s i s c l e a r l y marked a s oposed t o

g r a s s l a n d w i t h medium g r e y t o n e and f o r e s t a r e a s w i t h l i g h t g r e y t o n e . The d i f f e r e n c e s i n g r e y t o n e c a n be r e l a t e d t o d i f f e r e n c e s i n roughness and i n dielectric properties. F o r e s t a c t s a s a v e r y rough s u r f a c e , r e s u l t i n g i n i d e a l d i f f u s e r e f l e c t i o n and, a s a consequence, a s t r o n g r e t u r n s i g n a l t o t h e r a d a r a n t e n n a .

Smooth s u r f a c e s showing s p e c u l a r r e f l e c t i o n w i l l r e f l e c t t h e energy away from t h e s e n d e r / a n t e n n a e.g.

s o i l s u r f a c e s w i t h f u r r o w s p a r a l l e l t o t h e d i r e c t i o n of

t h e i n c i d e n t r a d i a t i o n and p e r f e c t l y calm w a t e r s u r f a c e s . The o r i e n t a t i o n and d i e l e c t r i c p r o p e r t i e s of t h e o b j e c t s a r e i m p o r t a n t . A h i g h

343

t.m. Fig.

=

t a b l e mountain

13.18 I n t e r p r e t a t i o n of p a r t of a s e m i - c o n t r o l l e d r a d a r mosaic SB.21-Z-C of t h e Radam P r o j e c t ( B r a s i l ) s c a l e 1: 250.000. For legend s e e t e x t .

r e t u r n s i g n a l has been d e r i v e d from r a i l - r o a d s and r o a d s d i r e c t e d p e r p e n d i c u l a r t o t h e i n c i d e n t r a d a r waves. Apparently a h i g h s p e c u l a r r e t u r n s i g n a l i s

344

Fig. 13.19 Seasat-1 ( s a t e l l i t e ) S A R mosaic from o r b i t 1493 of 9 October 1978. produced by t h e l i n e a r components of t h e s e o b j e c t s , e s p e c i a l l y of r a i l s , b u t a l s o s t e e p w a l l s of d i t c h e s a l o n g r o a d s . S p e c u l a r as w e l l a s d i f f u s e r e f l e c t i o n may t a k e p l a c e on v e g e t a t i o n s u r f a c e s such as g r a s s l a n d o r on m o d e r a t e l y smooth

water s u r f a c e s b o t h w i t h a s e c o n d a r y r e l i e f caused by wind a c t i o n a t t h e t i m e

345

Fig.

13.20 Land-use and soils in the central part of the Interpretation of the Seasat mosaic of Fig. 13.19.

Netherlands.

of acquisition. Furthermore,

roads may

produce radar returns due t o diffuse reflection by

planting at their sides. A summary is given in table 13.3. The capability of radar to discriminate different land-use types is illustrated in fig. 13.20.

346 Table 13.3. grey tone

Interpretation of grey tones on Seasat-1 imagery(fig. reflection/ scattering

roughness

moisture condition

objects

13.19).

white

specular diffuse diffuse specular

smooth' rough rough smooth

d rY dry moist wet

rail roads, roads 1 town's soil surface furrows 1 forest ditches canals 1

light grey

specular diffuse

smooth rough

dry moist

diffuse specular diffuse + specular diffuse + specular specular specular + diffuse specular specular no reflection (radar shadow)

rough smooth' moderate moderate smooth' moderate smooth smooth

wet dry moist wet dry moist moist wet

rail roads II forest, arable land with beets water surface roads It , rail roads II grassland water surface roads ' soil surface furrows ' soil surface water surface eastern side of dikes

medium grey

dark grey black

-

-

roughness: soil surfaces - furrows water surfaces waves planting at road sides induce a certain roughness

orientation of objects in relation to incident radiation: 1 perpendicular tl parallel ' oblique

-

+

Legend fig. 13.20 Land use A

Arable land

Soils -

0Alluvial soils* (sands excluded)

GA

Grassland and Arable land

Predominantly calcareous sand soils

G

Grassland

Complex of podzols, old arable land,

F

Forest

Gley soils and inland dunes

N

Nature areas

Peat, mucky clay, shallow clay soils

H

Heath

over peat

@

Built-up area

0

Lake area

*

a.0.

loamy sands, clays, clay over

peat, peaty clay

Note: In a number of instances, the distribution of soils is found to be closely related to parcelling (size, shape and arrangement of parcels) as it is visible on the radar imagery.

341

13.8.

Remote sensing with radio waves. The frequency band designations of

Union are given i n table 13.4.

the International Telecommunication

(see also Fig 2.2).

Barringer (1976) discussed the use of VLF (Very Low Frequency) radiowaves for geophysical mapping.

Most

radio-geophysical systems take advantage of the

stations operated by various government agencies. The frequencies are in the vicinity of 20 kHz and skin depths vary from 15 m up to 150 m depending on the conductivity of the materials of the earth's surface. The atmospheric 13.4.

Table

Frequency band designations of International Telecommunications

Union after Beckman (1975).

Abbrev.

Wavelength, A

Frequency f

~

VLF

3 -

LF

30

MF

300

HF

3

VHF

30

UHF

300

SHF

3

EHF

30

-

30

100

kHz

~~~

-

Name

~~~

10 km

Very Low Frequency

10 - 100 km

300 kHz

-

10 m

10-

l m

3,000 kHz

1,000

30 MHz

100

300 MHz

-

100 mm

10-

lmm

3,000 MHz

1,000

30 GHz

100

300 GHz

Low Frequency

1 m

Medium Frequency High Frequency Very-High Frequency Ultra-High Frequency

10 mm

Super-High Frequency Extremely High Frequency

transmittance of VLF signals is such that they can be employed up to a distance of 5,000 km from the source. Instrumental approaches to

the utilization of

VLF

signals have

included

measurements of the absolute field strength and the tilt angle of the magnetic component perpendicular to the direction of propagation. The so-called Radiophase employs the vertical electric field as a phase reference

for measuring

the

in-phase and

out-of-phase

components of

the

horizontal magnetic field. The results of modeling with this system have indicated

that

the amplitudes of

the in-phase and

out-of-phase magnetic

components are indicative of conductivity contrasts. The flow of electrical currents in the ground is highly sensitive to certain types of geological structure such as stress-metamorphism and shearing.

348 Radiophase measurements in zones of deep tropical weathering, showed that the major structures are still present (in relict form) in the weathered zone and can be detected by this method. The Radiophase system described above, makes use of the electric as well the magnetic field components. A new method, the so-called E-phase, operates

as

entirely on the electric field components. It has been shown that when a radiowave propagates over homogeneous earth, the horizontal currents generated at the earth-air interface are phase shifted by 45"

with respect to the propagating field. The resultant electric field is

tilted

slightly

forward

in the

direction of

propagation.

The

horizontal

electric field amplitude is related to the square root of the resistivity of the underlying terrain, and the tilt varies at VLF from a few minutes of arc over highly conductive terrain, to 1" or more over resistive ground. An E-phase installation can be mounted on aircraft such as helicopters. Resistivity

maps

produced

by

E-phase

are

contoured

in

ohm-meters,

indicating apparent resistivity, and according to Barringer (1976) they are not dissimilar from resistivity maps produced by conventional ground methods. In general, gravel and sand are relatively resistive unless they are saturated with saline water.

Clay materials are normally relatively conductive as a

result of ion-exchange effects. Frozen grounds tend to be much more resistive than thawed grounds. Conversely, heated grounds are likely to be more conductive than cooler grounds.

It is possible to operate at higher frequencies than the VLF range in order to restrict the measurements to shallower penetrations which will be important for soil survey.

13.9.

Applications and future developments. De Loor (1976) and other authors indicate several application fields for

radar, namely:

-

geological mapping; hydrology

(see

Foster,

1981)

e.g.

drainage

basin

analysis,

riverbasin

morphology;

-

sea, coastal and oceanographic studies e.g.

mapping of sea and swell waves,

mapping of ice, detection and control of oil pollution;

-

vegetation studies (e.g.

forest regrowth monitoring, see Hardy, 1981);

349

-

agriculture e.g.

crop identification and soil moisture studies.

For the use of radar imagery in land-use interpretation, the reader is referred to Henderson (1977).

Simonet (1970) reports about crop identification.

Some of his comments are given below:

-

Some crops depolarize an incident polarized beam to a different degree than

others, hence, polarized radar may be used in crop discrimination;

-

the use of more than one frequency and multitemporal observation enhance the accuracy of crop discrimination;

-

colour combining of multiple polarization imagery will be an aid in crop discrimination. The application of radar in environmental studies in South America is well

known. We only mention the "Projeto Radam" in Brasil (Ministerio das Minas E Energia of Brasil, 1975 and other reports) and the "Proyecto Radargrametrico del Amazonas" in Colombia (Instituto Geografico Agustin Codazzi, et al., 1979).

In these projects geological maps, soil maps, vegetation maps, land use maps and potential land use maps at a small scale have been produced with the aid of radar imagery and field survey. Owing to the unfavourable weather for aerial photography

in these areas (limited number of flight days),

radar is an

important tool for mapping of the environment, since it is independable on weather conditions. For this reason, radar is also an important aid in regional inventarisation of disasters (e.g.

flooding) in that it enables a rapid and reliable acquisition

of remote sensing data. The use of stereoradar and the application of COlOUK imagery for the

enhancement of the representations are some of the most promising developments. Furthermore, significant advances in radar capability can be expected as a result of the improvement of spatial resolution and multispectral approaches in data collection, as well as from the application of multipolarization. The potential of operating at longer wavelengths is afforded by the technology of SAR:However,

a boom in the application of radar may be expected through

their implementation in spaceborne systems (Lillesand and Kiefer, 1979). Aeroresistivity maps produced by E-phase Radio Field methods have a number of significant geological applications (Barringer, 1976), these being:

-

mapping of sedimentary strata e.g. exploration for kaolin;

gravel deposits;

350

-

mapping of ice lenses in discontinuous permafrost zones; exploration for geothermal areas; hematite and manganese exploration.

13.10. Conclusions A number of systems can be distinguished a.0.:

Lidar or Laser Radar,

Radar, Radiophase and E-phase. The Lidar systems operate in the short wavelength portion of the EMS. Three different types of Aircraft Lidars can be mentioned: the Laser Profiler OK

Altimeter, the Mapping Lidar, the Raman and Fluorescence Lidar.

The Radar systems operate in the Microwave portion of the EMS in different bands e.g.

X = 0.75-1.1

cm (P-band),

cm (Ka-band),

X

= 2.4-3.75

cm (X-band) up to X

= 30-100

and different modes of polarization can be applied. Sidelooking

Airborne Radar (SLAR) and Synthetic Aperture Radar ( S A R ) are the main systems for reconnaissance and exploratory mapping. The properties of a target that determine the radar echo are: roughness, slope, orientation and dielectric properties, as well as the presence of resonant-sized objects. Ground penetrating radar (GPR) may be used for the detection of boundaries of soil horizons which show strong differences e.g. albic and spodic horizons, OK

the soil

-

rock boundary. Traverses with a maximum penetration depth of 3 to

10 m may be produced by moving the sender and the antenna along the surface.

Radar imagery shows some defects e.g. the occurrence of

the fold-over of steep slopes, and

black radar shadows behind high objects, thus entirely

masking terrain features (shadows on airphotos show detail to some extent, owing to scattering of low intensity diffuse sky light). Radar imagery may be regarded as complementary to aerial photography in having imaging capability in the domain between a =45' and a = l o " . Very Low Frequency (3-30 kHz) radiowaves may be used for conductivity and resistivity mapping with penetration depths between 15 m and 150 m. At higher frequencies, the measurements will be restricted to shallow penetration, which, however, is important for soil survey. Radar is extensively applied in environmental studies in South America. The capability of radar to produce imagery independent of weather conditions makes it an important aid in the making of a regional inventory of tropical wet

351 areas, and when a rapid recording of a terrain is required e.g.

during or just

after flooding. It is expected that the application of radar will be promoted through the implementation of it in spaceborne systems and by the improvement of spatial resolution. Research is needed to determine the capabality of remote sensing with radiowaves for soil survey.

13.11

References.

Banyard, S.G., 1979. Radar Interpretation based on Photo-truth Keys. ITC Journal 1979-2, Enschede, The Netherlands: pp. 267-276. Barringer, A.R., 1976. Airborne Geophysical and Miscellaneous Systems. In: Remote Sensing of Environment Ch. 8 (ed. by Lintz, J.Jr. and Simonett D.S.), Addison-Wesley Publ. Cy, London: pp. 291-322. Beckman, J.A., 1975. Communications for Imaging Systems. Chapter 11 in Manual of Remote Sensing Vol I (editor Reeves, R.G.). her. SOC. of Photogrammetry, Virginia: pp. 589-609. Bush, J.F. and Ulaby, F.T., 1978. An Evaluation of Radar as a Crop Classifie Remote Sensing of Environment, Elsevier North Holland: pp. 15-36. Cihlar, J. and Ulaby, F.T., 1974. Dielectric Properties of Soils as a Function of Moisture Content. Remote Sensing Laboratory. Univ. of Kansas: 61 pp. Collis, R.T.H. and Russell, P.B., 1976. Laser Applications in Remote Sensing In: Remote Sensing for Environmental Sciences. Ecological Studies 18, Springer Verlag, Berlin: pp. 110-146. Foster, J.L., 1981.Multisensor Analysis of Hydrologic Features with Emphasis in the Seasat S A R . Photogrammetric Engineering and Remote Sensing. Vol. 47, No. 5: pp. 655-664. Hardy, N.E., 1981. A Photo Interpretation Approach to Forest Regrowth Monitoring using Side-looking Airborne Radar Grant County, Oregon. Int. J. Remote Sensing, Vol. 2. no. 2: pp. 135-144. Henderson, F.M., 1977. Land Use Interpretation with Radar Imagery. Photogrammetric Engineering and Remote Sensing, Vol. 43, No. 1: pp. 95-99. Hickman, C.D. and Hogg, J.E., 1969-1970. Application of an Airborne Pulsed Laser for Nearshore Bathymetric Measurements. Remote Sensing of Environment, Vol. I. her. Elsevier Publ. Cy, Inc. New York: pp. 47-58. Hoogeboom, P., 1982. Classification of Agricultural Crops in Radar Images. Int. Geoscience and Remote Sensing Symposium, Munich, June 1-4, 1982: 5 pp. Innes, R.B., 1973. An Interpreter's Perspective on Modern Airborne Radar Imagery. In: The Surveillant Science. Remote Sensing of the Environment (ed. Holz, R.K.), Houghton Mifflin Cy, Boston: pp. 282-290. Instituto Geogrsfico "Agustin Codazzi" et al., 1979. La Amazonia Colombiana y Sus Recursos. RepGblica de Colombia. Proyecto Radargrametrico del Amazonas, BogotL: 590 pp. y mapas. Johnson, C.M., 1970. Laser Radars. In: Radar Handbook (ed.-in-chief Skolnik, M.I.), McGraw-Hill Book Cy, New York: pp. 37-1137-69. Johnson, R.W., Glaccum, R. and Wojtasinski, 1980. Application of Ground Penetrating Radar to Soil Survey. Soil and Crop Science Society of Florida, Proc. Vol. 39: pp. 68-72. Kasteren, H.W.J. van, Smit, M.K., 1977. Measurements on the Backscatter of Xband Radiation of Seven Crops throughout the Growing Season.

352 NIWARSfPubl. nr. 47, The Netherlands: 37 pp. and appendices. Kerr, D.E., 1951. Propagation of Short Radio Waves. Massachusetts Institute of Technology, Radiation Laboratory Series, Vol. 13, McGraw-Hill Book Cy, New York. Koopmans, B.N., 1973. Drainage Analysis on Radar Images. ITC Journal 1973-3, Enschede, The Netherlands: pp. 464-479. Koopmans, B.N., 1974. Should Stereo SLAR Imagery be preferred to Single Strip Enschede, The Imagery for Thematic Mapping? ITC Journal 1974-3., Netherlands: pp. 424-444. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp. Long, M.W., 1975. Radar Reflectivity of Land and Sea. Lexington Books, D.C. Heath and Cy, London: 306 pp. Loor, G.P. de, 1976. Radar Methods. In: Remote Sensing for Environmental Sciences, Springer Verlag, Berlin: pp. 147-186. Loor, G.P. de, 1977. Microgolven en Gewassen. Symposium Luchtwaarneming. TH Delft, sept. 1977. Ned. Ver. voor Fotonica, "s-Gravenhage, The Netherlands: pp. 57-87. MacDowall, J., 1972. A Review of Satellite and Aircraft. Remote Sensing Instrumentation. 1st Canadian Symposium on Remote Sensing: pp. 39-68. Mekel, J.F.M., 1972. The Geological Interpretation of Radar Images. ITC Textbook of Photo-Interpretation Vol. VIII, Enschede, The Netherlands: 61 PP. Ministerio das Minas E Energia of Brasil, Departamento Nacional Da Produsao Mineral, 1975. Projeto Radam. Folha SB 21 Tapajbs. Levantamento de Recursos Naturais Vol. 7. Rio de Janeiro: 409 pp. e mapas. Moore, R.K. et al, 1975. Microwave Remote Sensors, Chapter 9 in Manual of Remote Sensing Vol. I (editor Reeves, R.G.). Amer. SOC. of Photogrammetry, Virginia: pp. 399-537. Moore, R.K., 1976. Active Microwave Systems. In: Remote Sensing of Environment (ed. by Lintz, J.Jr. and Simonett, D.S.). Addison-Wesley Publ. Cy, London: pp. 234-290. Moore, R.K., 1983. Radar Fundamentals amd Scatterometers. Chapter 9 in Manual of Remote Sensing, 2nd edition Vol. I. (editor Colwell, R.W.), Amer. SOC. of Photogrammetry, Virgina: pp. 369-427. Moore, R.K. et al., 1983. Imaging Radar Systems. Chapter 10 in Manual of Remote Sensing 2nd edition Vol. I. (editor Colwell, R.N.), Amer. SOC. of Photogrammetry, Virginia: pp. 429-472. Nunnally, N.R., 1969. Integrated Landscape Analysis with Radar Imagery. Remote Sensing of Environment 1, Amer. Elsevier Publ. Cy, New York: pp. 1-6. Schmugge, T., Ulaby, F.T. and Njoku, E.G., 1978. Microwave Observations of Soil Moisture: Review and Prognosis. Goddard Space Flight Center, Greenbelt, Maryland, Soil Moisture Workshop, South Dakota State University: 28 pp. Simonett, D.S., 1970. Remote Sensing with Imaging Radar: a Review. Geoforum 2 Journal of Physical, Human and Regional Geosciences. Pergamon, Vieweg Braunschweig, Germany: pp. 61-74. Skolnik, H.I. ed., 1970. Radar Handbook. McGraw-Hill Book Cy. New York. Ulaby, F.T., Cihlar, J. and Moore, R.K., 1974. Active Microwave Measurement of Soil Water Content. Remote Sensing of Environment 3, her. Elsevier Publ. Cy: p. 185-203. Ulaby, F.T. Aslam, A. and Dobson, M.C., 1981. Effects of Vegetation Cover on the Radar Sensitivity to Soil Moisture. Remote Sensing Laboratory, Techn. Rep. 460-10, Univ. of Kansas, Lawrence, Kansas. Ulaby, F.T., Moore, R.K., Fung A.K., 1981-82. Microwave Remote Sensing. Vol I and 11. Addison-Wesley Publ. Cy., London: 1064 pp.

353

Wiebe, M.L., 1971. Laboratory Measurements of the Complex Dielectric Constant of Soils. Texas A & M University, Remote Sensing Center. Techn. Report RSC-23: 19 pp. (fig. excluded). 13.12.

Additional Reading.

Alexander, L. and Kritikos, H., 1980. An Investigation of the Autocorrelation Function of Radar Images. 6-th Canadian Symposium on Remote Sensing, May, 1980: pp. 154-158. Attema, E.P.W. and Ulaby, F.T., 1978. Vegetation Modeled as a Water Cloud. Radio Sci, 13: pp. 357-364. Attema, E.P.W., 1980. Satelliet Aardobservatie in het Microgolfgebied. Ruimtevaart. Orgaan van de Nederlandse Vereniging voor Ruimtevaart (NVR) POB 3166, 2601 DD Delft: pp. 68-83. Dabrowski, H. et Rebillard, P., 1982. Applications, du Radar lat6ral a l'observation des Ph6nomSnes G6ologiques dans les Alpes Occidentales Francaises. Bull. SOC. G6ol. France, 1982 ( 7 ) , t. XXIV no 1: pp. 87-95. Davies, D.H., 1970. Radar- a New Mapping Device. De Ingenieur Jrg. 82, nr. 33. Technisch Wetenschappleijk Onderzoek 6, Kon. Inst. V. Ingenieurs, The Netherlands: pp. 71-80. Deane, R.A. and Donville, A.R., 1972. Radar Scattering from Natural Surfaces In: SLAR Systems and Their Potential Applications to Earth Resources Surveys, Vol. 2. Prepared by EASAMS for ESRO, ESTEC Contract 1537/71 EL. Elachi, C.L.A, 1982. Shuttle Imaging Radar Experiment. Science Vol. 218, No. 4576. Washington her. Ass. Adv. Sci: pp. 996-1003. Haralick, R.M., Caspall, F. and Simonett, D.S., 1970. Using Radar Imagery for Crop Discrimination: A Statistical and Conditional Probability Study. Remote Sensing of Environment 1. Amer. Elsevier Publ. Cy: pp. 131-142. Hirosawa, H., Komiyama, S . and Matsuzaka, Y., 1978. Cross-polarized Radar Backscatter from Moist Soil. Remote Sensing of Environment 1. Elsevier North-Holland: pp. 211-217. Janse, A.R.P., 1974. Radarflecties van Gewas, Bos en Bodem. Landbouwkundig Tijdschrift/pt 86-12: pp. 316-321. Janse, A.R.P., 1975. Reflections of Radar Waves by Soils, Crops and Forest: A Review of Some Recent Dutch Work. Neth. J. Agric. Sci 23: pp. 308-320. Janse, A.R.P. en Bouten, W., 1980. Radarreflecties van Bodemoppervlakken. Cultuurtechnisch Tijdschrift Jrg. 19, Nr. 5., Utrecht, The Netherlands: pp. 268-270. Jensen, H., Graham, L.C., Porcello, L.J. and Leith, E.N., 1977. Side-looking Airborne Radar. Scientific American, October 1977: pp. 84-96. Koolen, A.J., Koenigs, F.F.R. and Bouten, W., 1979. Remote Sensing of Surface Roughness and Top Soil of Bare Tilted Soil with an X-band Radar. Neth. J . Agric Sci 27, Wageningen: pp. 284-296. Leberl, F., 1974. Evaluation of SLAR image quality and geometry in PRORADAM. The ITC Journal 1974-4. Enschede, The Netherlands: pp. 518-546. Lewis, A.J., MacDonald, H.C., 1970. Interpretive and Mosaicing Problems of SLAR Imagery. Remote Sensing of Environment 1, Amer. Elsevier Publ. Cy: pp. 231-236. Loor, G.P. de, 1969. Possibilities and Use of Radar and Thermal Infrared Systems. Photogrammetria 24. Elsevier Publ. Cy Amsterdam: pp.43-58. Peake, W.H. and Oliver, T.L., 1971. The Response of Terrestrial Surfaces at Microwave Frequencies, Ohio State Univ. Electroscience Lab. Techn. Rep. AFAL-TR-70-301. Rao, R.G.S. and Ulaby, F.T., 1977. Optimal Spatial Sampling Techniques for

354 Ground Truth Data in Microwave Remote Sensing of Soil Moisture. Remote Sensing of Environment 6. Elsevier North Holland: pp. 289-301. Rudd, R.D., 1974. Remote Sensing. A Better View. Duxbury Press, North Scituate Massachusetts: 136 pp. 1977. Radarreflectie van Gewassen. Symposium Luchtwaarneming. TH Smit, M.K., Delft, sept. 1977. Ned. Ver. voor Fotonica, Is-Gravenhage, The Netherlands: pp. 156-166. Tricart, J.L.F., 1979. Comparaison des Informations "Ecographiques" fournie par trois types de Radar. ITC Journal 1979-4, Enschede, The Netherlands: pp. 535-547.

Uenk, D. and Kasteren, H.W.J. van, 1978. Radarvluchten 1977. Oost- en Zuid Flevoland. Centrum voor Agrobiologisch Onderzoek CAB0 Int. Rep., Wageningen, The Netherlands: 18 pp. Vermeer, J., 1970. Interpretatie van Radar- en Infraroodbeelden. De Ingenieur JKrg 82, nr. 33. Technisch Wetenschappelijk Onderzoek 6. Kon. Inst. V. Ingenieurs, The Netherlands: pp. 87-91. White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press, Oxford: 104 pp.

355 14,IMPLICATIONS OF REMOTE SENSING

Remote sensing is becoming more and more complex due to the increasing number of acquisition and processing techniques. This complexity may cause it to become less accepted and less used. However, some of the techniques have found a definite place in environmental survey (par. 14.1). For environmental inventories, the use of remote sensing tools is a logical decision. Analysis of the environmental remote sensing data and the field observations enables land evaluation as a step in the planning of alternative

ways

of

land

use.

The

latter

normally

requires

specific

interpretation aspects to be emphasized more than the normal aspects cansidered for soil survey, and may be supported well by modern remote sensing techniques (par. 14.2). Methodology of environmental research, aided by remote sensing, should be further

developed

with

respect

to

data

handling

and

field

description

techniques (par. 1 4 . 3 ) . This is even more true, since many new techniques have been created the last decade. A view on near-future developments in remote sensing is presented in par. 14.4. Finally, attention is paid in par.

14.5 to various political and legal

aspects, and in 14.6 to education and training in remote sensing.

14.1. Summary

on

applications

The conclusions given in the chapters 9 through 13 are summarized below. Black- and -white panchromatic airphotos are the common tool for soil survey in offering large, to medium-scale imagery with low cost stereoscopy. Black- and -white Infrared airphotos may be used for showing differences in soil moisture condition and vegetation cover types. To get even clearer imagery of the latter,

application

of

false

colour

aerial

photography

offers

good

possibilities. Multispectral photography is accepted as a research tool for agricultural remote sensing projects, but is also promising for soil survey in regions with large areas of bare soils. The application of multispectral scanning in the Visible and near Infrared is most promising i n arid areas and other areas where much bare soil

356 surface is present, at least during some time of the year. Satellite MSS e.g. Landsat provides a synoptic view and has a multitemporal capacity. The latter is very important for studies of the dynamics of the environment. The TM with its better spectral and spatial resolution, broadens the application field of the Landsat series. Scanning techniques are also applied for sensing the thermal Infrared. The data may be used for studies of soil moisture balance and evaporation. Radar may be applied

in reconnaissance and exploratory mapping.

The

capability of radar to produce imagery independent of weather conditions makes it an important aid in regional inventorying of tropical rain-forest areas. The so-called ground penetrating radar may be used in the terrain for detection of boundaries between s o i l horizons which show strong differences in texture or moisture content. 14.2.

Land evaluation Besides

airphoto-interpretation

(par.

9.4),

other

remote

sensing

techniques may be applied in studies on land evaluation, such as: -airborne MSS using bands in the NIR and Visible; for determination of terrain features; lnultitemporal satellite MSS data; for identification and mapping of land use, crops and natural vegetation by using crop

OK

natural vegetation calendars;

-thermal IRLS; for studies of crop or soil temperature and moisture balance (see Rose and Thomas, 1968); -radar;

for determination of terrain features, the acquisition being not

dependent on weather conditions. It has been emphasized that multitemporal studies are of great value, since land evaluation is concerned with the ecology of the agricultural and natural environment. The dynamics of the environment influence the growth of plants enormously. It is the influence of the environment as shown by the growth of natural vegetation or crops during a period of time, which is a major subject of study. Satellite MSS biomass

throughout

(especially TM) can be applied to obtain estimates on time.

Thus, different land units can be compared and

evaluated with regard to their productivity. The following examples of environmental mapping which are aided by remote sensing techniques, illustrate once more the potential of remote sensing as a

351

tool in land evaluation studies: -monitoring of natural processes aided by the detection of changes; -surfacial water mapping for flood conditions (flood hazard);

sequential

observations (time difference: hours or days) may provide estimates on run-off OK

intake rate;

-soil mapping; more specific information about soil moisture condition or about roughness of the soil surface may be obtained; in this connection the area of eroded or bare land is important, too; -land use mapping and soil management; e.g. and fallow land,

OK

acreage of land under cultivation

conservation measures;

-vegetation mapping; e.g. fire, wind, water, hail

OK

areas of green vegetation; vegetation damage by diseases.

Finally, attention is drawn to the application of large-scale airphotos in studies of landscape design. Airphoto-interpretation enables a first inventory of features which can be used for an evaluation of the actual physiognomy. Some important features, which can be studied for this purpose by airphotointerpretation, are: -the distribution of high objects (e.g. houses, dykes and dunes or vegetation higher than 2 m); -the surface area, form and distribution of waterbodies, of marsh and dry land ; -the type and distribution of vegetation cover types; -the expected transparency of tree 14.3.

OK

shrub

TOWS.

Methodology

It is no secret that many advanced high resolution systems as well as data processing systems are only available for military use and that security ratings have a negative effect

on

the development of remote sensing for

peaceful purposes. However, the systems available for civilian use already produce quantities of data, too large for the processing facilities. A first generation Landsat MSS produces 15 megabit s-l

while the TM generates at least lo4 megabits

s-'.

Some authorities consider that a data stream below 5 megabits s-l would he most suitable for a remote sensing system. It is evident that there is a need for studies on data compression (Barrett and Curtis, 1982),

and that we should be

careful with application of high resolution systems which produce tremendous

358 amounts of data. Compression of MSS data may be reached in processing on different ways, such as: -ratios enhancing certain phenomena of the land surface; -PCT of a sample set; -multitemporal combinations. Normally, there is a phase of visual interpretation and a first approach to physiographic description and classification of the area. The physiographic units are characterized by their relative location and landsurface properties. The land surface properties may be classified using certain algorithms; the results have to be checked in the field. Furthermore, change detection may help in a number of cases to characterize processes, and pattern recognition aids to describe the distribution of objects OK

phenomena in the units. The data accumulated from remote sensing systems can be put in systems

capable of efficient data storage and expedient data processing and retrieval, the so-called Geographic Information Systems ( G I S , Simonett et al,, 1983). G I S is an information system which enables assembling and analyzing diverse data of specific geographic areas, using the spatial locations of the data as a basis. The data can be channelled to the level at which decisi.on making takes place. Remote sensing data may improve the information on natural resources and as such they are essential as an input to the G I s . Models are needed to explain the complex natural soil system. The models are used to build up a hypothesis during the interpretation of remote sensing data.

Dijkerman (1974)

has given a characterization of models according to

their nature, function and design (see table 14.1) Some notes are given for explanation of table 14.1 (for more information, the reader is referred to the original publication). Concrete models consist of real physical objects (soil column or soil samples) that stand model for the system under study. Conceptual models use abstract concepts created in the human mind. Scale models are models in which the system to be studied, is scaled down up) to a size or number convenient for study or comprehension.

(OK

359

Table 14.1 Characterization of models after Dijkerman (1974). Characterzation of models 1. Nature of models 2.

concrete model conceptual model

a. b. C.

d. Function of models

1. 2.

3. 4.

5. Design of models

1.

2.

3. 4.

mental model verbal model structural model mathematical model

observation model experimental model descriptive model explanatory model predictive model scale model idealized model analogue model computer simulation model

The models used in remote sensing studies may be characterized according to:

-

their nature in conceptual models (mental, verbal or structural);

-

their function in observation, descriptive, explanatory and predictive models;

-

their design in scale and analogue models. The modern remote sensing techniques, e.g.

the TM, make a quantitative

correlation of field data with remote sensing data within reach. For this, knowledge of the interaction process of EMR with objects at the earth's surface is needed. Since most remote sensing techniques have a limited penetration capability, we may concentrate at this stage on the properties of the landsurface. A first subdivision of parameters of the land surface which are important

for the interaction process can be made as follows: 1)

reflective and absorptive properties of the surface a) roughness producing shadow in forward (and reflecting surfaces in backward) direction soils and rocks

vegetation

-

soil texture, surface texture of minerals, structure, slaking, tillage, stoniness, rock outcrops, micro-relief, meso-relief, height, structure, type, X of coverage;

360 b) contribution of the reflecting surface soils and rocks

vegetation

-

moisture content,

-

green vegetation %,

-

dead foliage %, and other remains,

colour and mineralogical composition, organic matter content,

COlOuK,

free water and ice, c) contribution of shadow areas through scattering of skylight;

2)

slope and orientation

-

slope (angle, form, length) and exposition,

-

orientation of objects e.g.

strike of slopes, vegetation, dunes or

furrows. Consideration of these parameters and convential ways of describing the soil and land surface (Guidelines, FAO, 1977) reveals that generally the degree of detail does not enable a proper correlation of field data with remote sensing data

(Mulders, 1986).

More quantitative ways of describing the land surface have to be developed. Generally spoken, real percentages of sand, gravel etc. have to be taken into account in stead of broad classes. All parameters of the land surface including dunes, live vegetation and vegetation remains have to be quantified with regard to their nature, distribution

,

coverage and orientation.

If correlation of land surface parameters and remote sensing data is made possible, the basic maps for the GIS can be improved and dynamic features can be monitored with the aid of satellite systems. One can reach the phase of understanding processes in a quantitative way and the models can be predictive, thus serving decision making and appropriate action. An example of the use of satellite remote sensing in environmental management

is the FA0 Development Project on Remote Sensing Applications for Desert Locust Survey and Control (Hielkema, 1982). 14.4.

Recent and future developments Below the recent and future developments are summarized by taking regions

or nations involved in the developments of systems as a starting point.

361 1.

a.

USA --Organisations such as National Aeronautics and Space Administration or Geological Survey, EOSAT EKOS Data Center (Sioux Falls),

NASA, U.S.

Optical Systems Division of Information Technology (ITEK) and GEOSAT (Committee

industries

and

companies

mainly

from

USA)

provide

for

continuing efforts in: the Landsat and TM series, the Oceanographic Research Satellites (the first one was the Seasat 1 in 1978 using Infrared and Microwaves),

the Space Shuttle manned space flight (the first launch of a Space Shuttle Vehicle was in 1981; see Simonett et al., 1983). The Shuttle Imaging Radar (SIR) may be taken as an example for the diversity in research of the Shuttle Missions (see Koopmans, 1983): SIR-A, 1981 with L band S A R and horizontal polarization, SIR-B, 1984 item SIR A but with selectable radar look angles, SIR-C, 1987 with L band and C band S A R and multiple frequencies and polarizations. b.

!e_w-c2nce!cs The

U.S.

Geological Survey is examining the feasibility of

satellite system, the so-called Mapsat (U.S. Mapsat is based

on

a new

Geological Survey, 1981).

the Landsat mission, including the original Landsat

orbit and data communication system. The Mapsat concept incorporates capabilities such as: a 10 m resolution, spectral bands 0.47-0.57 stereoscopic coverage

mn, 0.57-0.70 on

um and 0.76-1.05

m,

a demand bases.

The Geosat committee examines the feasibility of

Stereosat, a linear

array sensor system with spatial resolution of 15 m, temporal resolution

of 48 days and along track stereoscopic coverage (Hempenius et al., 1982).

C.

!?theE-Res?SG Since 1969 research has been conducted to develop a technique using natural gamma radiation attenuation to measure snow water equivalent and

362

soil moisture from low-flying aircraft. The gamma flux from the soil is a function primarly of the water content and radio-isotype concentration ( 4 0 K, 238 U and ' 0 8 T1) near the surface.

The gamma radiation technique is capable of measuring soil moisture values in the upper 20 cm of the soil surface with the accuracy (RMS of 3.9

%)

required for operational hydrologic and agricultural applications

(Jones et al., 1983). 2.

Western Europe --------------

a.

European Space Agency

OK

ESA. ESA has developed a launch vehicle called

ARIANE, which is capable of delivering a payload of 1700 Kg into a geostationary orbit. A joint venture between NASA and ESA is the development of Spacelab, to he transported by the Space Shuttle orbiter (Spacelab 1, 1983). Of particular interest in Spacelab are the Metric Camera Facility (MC) and the Microwave Remote Sensing Experiment (MRSE).

The MC is a standard

Zeiss 30/23 aerial camera with a 30 cm focal length and a 23 x 23 cm format. The images cover an approximate ground area of 190 x 190 km with a ground resolution of approximately 20 m. An eighty percent overlap of consecutive photographs is obtained. For first results of interpretation, see Girard (1985). Later on, a camera with 60 cm focal length is planned as well as mounting on

free-flying satellites.

The MRSE operates as a two-frequency scatterometer to measure hackscatter from the ocean surface at two adjacent frequencies and as a thermal radiometer to measure surface temperature (Simonett et al, 1983). New concepts are: the ESA Resources Satellite-1 (ERS-1) and Advanced ESA Resource Satellite (AERS). The ERS-1 is directed to ocean observation and is planned for launch in 1987. The sensor payload aims the following:

-

C-band S A R with 30 x 30 m ground resolution and a 80-100 km swath,

-

an Infrared radiometer with channels at wavelengths of 3.7

~nn

and 12 Inn

and IFOV of 1 x 1 km,

-

-

a Microwave Radiometer with two channels at 23.8 GHz and 36.5 GHz, a three beam C-band scatterometer for measuring wind direction and

velocity,

363

-

a radar altimeter a.0.

for sea-state determination (Haskell, 1983).

The AERS is directed to land observation and has been proposed for launch around 1989. Its payload is to include the S A R , from ERS-1, an Optical Imaging Instrument (011) with six spectral bands in the range between 0.52-2.35

um

and and IFOV of 30 m; furthermore, one panchromatic band

with a 15 m IFOV, and a 175 km swath (Simonett et al., 1983). b.

France a.0.

Centre Nationale Etude Spatiale or CNES (Toulouse).

In 1986, the French* earth observation satellite or Systsme Probatoire d'observation de la Terre (SPOT-1) was launched by the ARIANE. This satellite was placed in a sunsynchronons orbit at a mean altitude (45'

Northern latitude)

98.70',

of 832 km. The orbit has an inclination of

the mean local solar time at descending node is 10:30 hrs. The

temporal resolution of 26 days can be enlarged using the steerability of the socalled HRV instruments (Chevrel et al.,

1981).

The HRV or High

Resolution Visible imaging instruments comprise a pushbroom scanner with linear arrays which operate in either of two modes: a three-band multispectral mode with the bands 0.50-0.59

-

0.68 um and 0.79-0.89 Um

(for selection see Begni, 1982),

ground resolution of 20 m; a black- and -white panchromatic mode

-

(0.51-0.73

m

)

rn , 0.61having a

with a ground

resolution of 10 m. The steerable HRV instruments enable off-nadir viewing. Thus they offer the possibility of obtaining stereoscopic pairs of images by the lateral stereoscopy principle. Two images can be obtained of a given scene on successive

satellite passes

on

either

side

of

the vertical.

This

improvement is very important for the application of SPOT in landscape analysis. There will be no complete world wide SPOT coverage. The user has to request for acquisition of unique, multitemporal

OK

stereoscopic coverage

(Rivereau, 1984). The Netherlands Agency for Aerospace Programmes (NIVR),

C.

*

Sweden and Belgium participate in the program.

in cooperation

364 with

Indonesia, have

planned

the development of

a

Tropical Earth

Resources Satellite (TERS) which would carry a multispectral linear array sensor. An equatorial orbit and orbital altitude of 1680 km, besides a so-called cloud detector in forward direction to select cloud free areas for data acquisition, are planned.

The

TERS will have a very high

temporal resolution being 11 times per day. Furthermore, three spectral bands with a ground resolution of 16 m and a panchromatic band with a ground

resolution

of

8 m

are

part

of

the

proposed

system

(Van

Konijnenburg, 1984). 3.

U.S.S.R. The Salyut 6, placed in orbit in 1977, has carried several multispectral film camera systems for earth observation. Certain missions in the Cosmos series were also designated as Earth Resource Observation Spacecraft. The latter have low orbital altitudes (220-270

km) and are recovered after 15-30 days of operation (U.S.

Geol.

Survey, 1982). In June 1980, the "Meteor" satellite was launched including a.0. a sensor package

known

as

"Fragment".

It

consists of

an

optical-mechanical

scanning unit with 80 m ground resolution at nadir and the following spectral bands: 0.4-0.8 1.5-1.8

4.

pm, 0.5-0.6

um, 0.6-0.7

um and 2.1-2.4

pm

pm, 0.7-0.8

pm, 0.7-1.1

!.nn,

1.2-1.3

m,

(Sirnonett et al., 1983).

N_ati~"al-~E~~e-_A9e~~~-~~-~~~_a~-~~-~~~~~ NASDA plans the launch of the MOS-1 or Marine Observation Satellite 1 at

the end of 1986. The orbital altitude is 909 km. It carries a payload of three instruments:

-

a Multispectral Electronic Self Scanning Radiometer (MESSR) with four

-

a Visible and Thermal Infrared Radiometer (VTIR) with a 500 km swath, one

spectral bands between 0.51 and 1.10 um,

a 50 m IFOV and a 100 km swath;

band in the Visible with a 0.9 km IFOV and three bands in the Infrared between 6.0 and 12.5 pm

-

with an IFOV of 2.6 km;

a two-frequency Microwave Scanning Radiometer (MSR). If this satellite is successful, a second and third spacecraft may be launched. Furthermore, an earth resources satellite is planned which will

365

Carry a linear-array stereo camera and an SAR (Simonett et al., 1983).

5.

Canada -----The Canadian Radarsat is scheduled for launch in 1990. It is planned to

carry a C-band or L-band SAR. It is designed to provide information on the ocean as well as the land surface (Raney, 1982). 6.

Indian Space Research Organisation ( ISRO) ......................................... The

ISRO developed an earth observation satellite (e.g.

Bhaskara-2

launched in 1981) which carries a two-band television camera system and a two-frequency Microwave radiometer system. 7.

The Peoples Republic of China ............................. Several satellites have been launched since 1975. Chinasat 10 was to Carry a two channel meteorological radiometer with Visible and Infrared bands. A 11-band multispectral scanner, linear array sensor and S A R were announced to be developed in 1984 (Simonett et al., 1983).

Some general trends are likely to continue in future (Barrett and Curtis 1982) :

-

national and international commitments to remote sensing will increase the

ground

receiving stations for satellite data

will become more

numerous, often linked to centralized data-processing facilities;

-

more new satellite series and concepts will be designed and tested;

-

more nations will join the once select club of the USA and USSR operating environmental satellites of their own;

-

satellite data analyses will increasingly combine data from different satellite systems and convential sources for maximum benefit to the user.

More specific with regard to the remote sensing systems, the following trends can be observed:

-

the development of systems with higher spatial resolution;

-

emphasis on data compression techniques;

improvement of the radiometry and spectral resolution; the increased application of S A R and thermal Infrared radiometers in satellite systems;

366

-

research in multidirectional information to obtain a.0.

stereo images;

more research after selection of spectral bands providing for specific information. Research in the Infrared has to be directed to spectral signatures. The

spectral features in the mid and far Infrared (Tables 2.3 and 2.4), position of the atmospheric windows (Fig. 2.12)

and the

indicate potential information

in the following bands (Mulders, 1986): potential information ___-_---__-----------

bands-!!?--!%3.40 -

4.10

-

10.00

phosphates, sulphates, Si-0

13.00

A1-OH, carbonates, H-0-A1,

4.50 9.00

10.00

C-H, C-H2, C-H3 (organic matter) oxides, S i - 0

5.10

Si-0-Si, A1-0-Si

14.5.

Political and legal considerations There is nothing inherently bad, immoral, or unlawful about remote sensing

unless the products produced are used detrimentally against anyone. However, the potential for the above by using remote sensing information does exist (Lins, 1985). Since the invention of the aircraft, we have assumed that property rights do not extend into the space over the land. No permission is needed to fly over one's land holdings. However, an individual, a company or government would be held liable for damage caused by the aircraft. In using satellites for earth observation, legal questions of surveillance are disregarded and it is considered to be permissible to gather data about another country. However, these data can be interpreted into terms of natural resources e.g.

the potential occurrence of petroleum and mineral resources

OK

may be used

for global crop forecasting (Mac Donald et al., 1985).

As noticeable a.0.

in the United Nations Committee on the Peaceful Uses of

Outer Space, several nations (e.g.

Brazil and Argentina) have become seriously

concerned about international regulations. The Soviet Union and France have proposed the following set of governing principles (Lins, 1985): a)

any remote sensing state must transmit to a sensed state, on mutually

367 acceptable terms, information the former obtains regarding the natural resources of the latter; b)

no state which obtains, through remote sensing, information concerning

the natural resources of another state shall make that information public without the prior consent of the latter state; c)

remote

sensing

of

earth

resources shall respect

the

principle

of

permanent sovereignty of states over their wealth and resources.

14.6.

Education and training Technology transfer may be defined as the process by which scientific

knowledge and the skills to apply that knowledge, are transferred. The transfer is often a complex process that involves significant differences in perceived needs, institutional structures and available resources. Many technicians in advanced countries are familiar with the principles underlying remote sensing, so that the users' community realizes its potential and limitations. This may be different in developing countries (Simonett et al., 1983). Specialists of almost 120 countries have purchased Landsat data from the

EROS

Data

Center.

Of

these countries, roughly

two-thirds

developing world (National Academy of Sciences, 1977).

belong

to

the

In a number of these,

institutions or other government agencies have the task to conduct or control remote sensing operations. These centres are of great importance to the development of remote sensing. of Sciences (1977)

The National Academy

has formulated the following

requirements for remote sensing centres: a)

a

remote

sensing

centre

should

employ

trained

personnel

with

a

concentration of scientific skills; b)

data analysis should be conducted through an interaction among personnel with diverse disciplinary training;

c)

there should be strong ties between the remote sensing centre and the users' agenciee, concerning the level of data flow, and the priorities of data collection and processing;

d)

the

remote

sensing

centre

should

have

ground

truth

studies

for

e)

the centre should be capable of handling remote sensing data from a

confirmation of remote sensing studies; variety of platforms;

368

f)

the centre should have the facilities for efficient data storage and retrieval;

g)

the centre should have the capacity for making an overview analysis on a national

regional scale.

OK

The centres can be of great importance in education and training as to remote sensing, but there is still a need for courses on remote sensing for students of developing countries (Mulders, 1978).

Although students of developing countries can take classes at the various universities (entrance levels often differ per country and/or per university), they generally prefer to attend courses specially organized for this purpose, such as:

-

the courses at the International Institute for Aerial Survey and Earth

-

Sciences (ITC/Unesco Centre) in Enschede, The Netherlands; the courses at the IPI, Indian Photo-interpretation Institute (Dehra Dun), the CIAF

(Centro

(Columbia)

OK

Inter-American0

de

FotointerpretaciBn)

in

Bogota

at the Regional Centre for Training in Aerial Surveys in

Ile-Ife (Nigeria).

In this connection, MSc-courses (including training on airphoto-interpretation and often also other remote sensing techniques) should be mentioned e.g.:

-

Land Resource Management or Planning at the Land Resource Division, Tolwooth, United Kingdom;

-

Pedology and Soil Survey, Univ. of Reading, United Kingdom;

-

Geomorphology, Univ. of Sheffield, United Kingdom; Soil Survey and Land Evaluation, Agricultural Univ.,

Wageningen, The

Netherlands.

In other cases special training programmes may fulfil the specific needs. Such programmes are offered by various organizations, e.g. EROS DATA CENTRE (U.S.A.)

and SOGESTA Cy (Urbino, Italy).

the FA0 (Rome), the The latter course is

organized in cooperation with UNEP, the United Nations Environment Programme. Another form of contribution towards the needs of developing countries in educating specialists in remote sensing, are the shortterm training seminars, courses and workshops organized under the United Naffons Programme on Space

369

Applications. The Committee on the Peaceful Uses of Outer Space plays a coordinating role. The awarding of fellowships is possible in connection with this programma. 14.7.

References

BaKKett, E.C. and Curtis, L.F., 1982. Introduction to Environmental Remote Sensing ( 2 nd. ed.). Charman and Hall, London: 352 pp. Begni, G., 1982. Selection of the Optimum Spectral Rands for the SPOT Satellite. Photogrammetic Engineering and Remote Sensing Vol 48., No. lo., Amer. SOC. of Photogrammetry: pp. 1613-1620. Chevrel, M., Courtois, M. and Weill, G., 1981. The SPOT Satellite Remote Sensing Mission. Photogrammetric Engineering and Remote Sensing Vol. 47, No. 8, Amer. SOC. of Photogrammetry: pp. 1163-1171. Dijkerman, J.C., 1974. Pedology as a science: the Role of Data, Models and Theories in the Study of Natural Soil Systems. Geoderma, 11, Elsevier Scient. Publ. Cy, Amsterdam: pp. 73-93. FAO, 1977. Guidelines for Soil Profile Description. Girard, M.C., 1985. InterprQtation PQdologique des Photographies prises par Spacelab 1. ITC Journal PKOC. 4th Symp. of Isss. Working Group Remote Sensing for Soil Survey (Wageningen and Enschede, The Netherlands). Haskell, A., 1983. The ERS-1 Programme of the European Space Agency. ESA Journal 1983, Vol. 7. ESTEC, Noordwijk, The Netherlands: pp. 1-13. Hempenius, S.A., Marwaha, B.S., Murialdo, A. and Wang Ren-Xiang, 1982. The second generation of Earth Observation Satellites. Communication ITC Enschede, The Netherlands. 1982. Satellite Remote Sensing, A new Dimension in Hielkema, J.U., international Desert Locust Survey and Control. FAO, Rome, 010680: 10 pp. Jones, W.K. and Carroll, T.R., 1983. Error Analysis of Airborne Gamma Radiation Soil Moisture Measurements. Agricultural Meteorology, 28. Elsevier Scient. Publ. Cy, Amsterdam: pp. 19-30. Koopmans, B.N., 1983. Space-borne Imaging Radars, present and future. ITC Journal 1983-3, Enschede, The Netherlands: pp. 223-231. Lins, H.F. JK., 1985. Some legal considerations in Remote Sensing. In the Surveillant Science: Remote Sensing of the Environement (R.K. Holz ed.) John Wiley & Sons, New York: pp. 382-388. Mac Donald, R.B. and Hall, F.G., 1985. Global Crop Forecasting. In the Surveillant Science: Remote Sensing of the Environment (R.K. Holz, ed.), John Wiley & Sons, New York: pp. 389-406. Mulders, M.A., 1978. Education and Research on Remote Sensing for Soil Survey. A first approach to Inventory. ISSS Working Group Remote Sensing for Soil Surveys. Agric. Univ. of Wageningen, The Netherlands. Dept. of Soil Scce. and Geology, Publ. nr. 669: 35 pp. 1986. The Significance of detailed Description of the Land Mulders, M.A., Surface for understanding of Remote Sensing Data. Transactions ISSS Congress Hamburg 1986: pp. 1220-1221. Mulders, M.A., Schurer, K., Jong, A.N. de and Hoop, D. de, 1986. Selection of bands for a newly developed Multispectral Airborne Reference-aided Calibrated Scanner (MARCS). Proc. of 7th ISPRS VII) SYmP. on Rem. Sens. for Res. Devel. and Envir. Management. Enschede, The Netherlands: pp. 301-303. National Academy of Sciences, 1977. Remote Sensing from Space: Prospects for Developing Countries. Report of the Ad Hoc Committee on Remote Sensing.

370 Raney, R.K., 1982. Radarsat-Canada's National Radar Satellite Program. Inst. of Electr. and Electronics Eng., Geoscience and Remote Sensing SOC. Newsletter, Vol. X X I , no. 1: pp. 5-9. Rivereau, J.C., 1984. Access to SPOT Data and Product Distribution. ITC Enschede, The Netherlands, Seminar on SPOT Technology and Applications 25-26 January 1984: p. 8. Rose, C.W. and Thomas, D.A., 1968. Remote Sensing of Land Surface Temperature and some Applications in Land Evaluation. Paper of CSIRO. Symposium 26-31 August 1968: 9 pp. Simonett, D.S. et al., 1983. The Development and Principles of Remote Sensing. Chapter 1 in manual of Remote Sensing 2nd edition (R.N. Colwell, editor). her. SOC. of Photogrammetry. Falls Church, Virginia: pp. 1-35. U.S. Geological Survey, 1981. Landsat Data Users Notes Issue No. 17, Eros Data Center, Sioux Falls: pp. 2-4. U.S. Geological Survey, 1982. Landsat Data Users Notes Issue No. 2 1 and 24, Eros Data Center. Van Konijnenburg, R., 1984. Stand van zaken in het TERS Project. Ruimtevaart, Orgaan v.d. Nederlandse Vereniging voor Ruimtevaart (NVR) Delft, The Netherlands: pp. 44-46. 14.8.

Additional reading

Hempenius, S.A., 1974. How can ecology prepare itself for remote sensing? ITC Journal, Enschede, The Netherlands: pp. 561-571. Kinnucan, P., 1982. Earth-scanning satellites lead Resource Hunt. High Technology Vol. 2, No. 2. Techn. Publ. Cy. Boston, USA: pp. 53-60. Voute, C., 1983. Education and Training in Remote Sensing for Resource Development. ITC Journal, 1983-1: pp. 34-42.

371 Plate 1. False colour airphoto of an area in the Netherlands (Graafschap) Z= 1520 m, scale 1:10,000. Camera Wild RC8, wide angle c= 152.35 nun, lenstype UAg 432, AV filter 1.4X, Wratten 12. Film: Ektachrome Infrared 2443. Acquisition KLM Aerocarto, The Netherlands. Plate 2. Multemporal band 5 combination of 1st generation Landsat; Calatayud area, Spain. Diazo: yellow January '75 ma genta June ' 75 cyan September '75 Plate 3.Fragment of the ITC Colour Chart (derived from the Ostwald Colour System). The colours are composed by colour dots. The sequence, in which colours are indicated, is as follows: first figure yellow, second figure magenta, third figure cyan. Colour code numbers: O= O X , 1= lo%, 2= 20%, 3= 35%, 4= 50%, 5= 70%, 6= 100%. Example: 561= 70% yellow + 100% magenta + 10% cyan. Plate 4. 1st generation Landsat. PC1 (green) and PC2 (red) colour combination of 4 September '76 of the Calatayud area, Spain (courtesy: ITC). Plate 5.Classification using Ward's clustering method (digital data of 1st generation Landsat of June '76) Legend: white= gypsiferous areas with extremely low vegetation coverage very dark green= moderate coverage of Quercus ilex or Pinus halepensis dark green= low to moderate coverage by low shrubs and herbs olive green= grapes, wheat, bare brown soil or greyish soil and almonds light green= mainly orchards red= badlands with marl or gypsiferous material, moderate coverage by lichens and extremely low coverage by low shrubs and herbs light blue= water

372

373

374 ABBREVIATIONS, SYMBOLS, UNITS OF MEASlJRE GENERAL AEM ATS C-band CCD CCI CCT EM EMR EMS ERS ERTS ESA GOES GPR GR HCMM HF IFOV IR IRLS L-band MSP MSS MTF NASA NIR NOAA PC PCT Radar

RAR RBV RCS pixel

Application Explorer Mission Application Technology Satellite Microwaves A = 3.75-7.5 cm Charge Coupled Device Charge Coupled Imager Computer Compatible Tape Electromagnetic Electromagnetic Radiation Electromagnetic Spectrum ESA Resources Satellite Earth Resources Technology Satelite European Space Agency Geostationary Operational Environmental Satellite Ground Penetrating Radar Ground Range Heat Capacity Mapping Mission High Frequency 3-30 MHz Instantaneous Field of View Infrared Infrared Line Scanning Microwaves A = 15-30 cm Multispectral Photography Multispectral Scanning Modulation Transfer Function U.S. National Aeronautics and Space Administration Near Infrared National Oceanographic and Atmospheric Administration Principal Component Principal Component Transform Radio Detection and Ranging Real Aperture Radar Return Beam Vidicon Radar Cross Section Picture element

SAR SLAR SMS

Synthetic Aperture Radar Side Looking Airborne Radar Synchronous Meteorological Satellite SPOT Systeme Probatoire d'0bservation de la Terre TIROS Television Infrared Observation Satellite TM Thematic Mapper W Ultraviolet VHF Very High Frequency 300-3000 MHz VLF Very Low Frequency 3-30 kHz X-ray Rijntgen X-hand Microwaves A = 2.4-3.75 cm SYMBOLS PHYSICAL ASPECTS A f h I LE mf m n

Tc L

E E

€0 E' E"

0

i

amp1itude frequency (s-l) height (m) above reference plane intensity of radiation (W) Latent heat flux, evapotranspiration (wm-2) soil moisture as X of field capacity actual gravimetric moisture content index of refraction crop surface temperature emissivity ( 0 - 1 ) dielectric constant (Fm- 1) E for vacuum relative dielectric constant real part of dielectric constant imaginary part of dielectric constant angle of incidence

375 U N I T S OF MEASURE

angle of refraction wavelength of EMR (m) reflectance % surface component of reflectance internal component of reflectance reflectance horizontally polarized radiation reflectance vertically polarized radiation

Basic units and symbols of SI (Systgme International d'Unit6's) : length meter m mass kilogram kg s time second electric current ampdre A temperature kelvin K luminance candela cd amount of substance mol mo 1 The two supplementary units are: angle radian rad solid angle staradian sr

SYMBOLS A S P E C T S A E R I A L PHOTOGRAPHY

B B*

air base (m) reflecting power of image components (W) focal length (mm) photographic density exposure (cd s-l) height difference (m) nadir point system resolution in line pairs per mm scale vertical exaggeration flying altitude

C

D E h N

RS S V Z

a

Y Ap

angular field o f view slope of D - E curve parallax difference (mm)

From the basic units the following SI-units are derived: pascal Pa =N.m-' pressure force newton N =Kg.m.s -2 joule J =N.m energy watt w =~.s-l power hertz Hz =s-l frequency coulomb C =A.s electrica1 charge volt V -1J.A-l electr. tension =V.A-' electr. resistance ohm siemens s = n -1 e 1. conductivity farad F =C.T1 electr. capacity magnetic induction tesla T=kg.s-2A-1 degree Celsius " C temperature Kelvin K The following prefixes and factors are used :

SYMBOLS T E C H N I C A L A S P E C T S

4 Gt a 9

a

a 0

effective aperture of receiving antenna (m) gain of transmitting antenna in direction of target (m) grazing angle depression angle effective back scattering area (m*) differential scattering coefficient (dR)

giga G mega M kilo k

lo9

deci

d 10-1

106 centi c 10-2 l o 3 milli m lod3

micro P nano n 10-9 pic0 p

376

INDEX

absorptance 37 absorption bands (0.4-2.5 m ) 48-50 absorption factor 25 absorptivity atmosphere 4 1 accessability of terrain 231 actinolite 56 additive colour viewing 153 aerial film speed 169-170 AERS 365

age of soil (interpr.) 207-208 Agfacontouring 153 airbase 158 airborne line scanner 109-110 platforms 112-113 airphoto-interpr. legends 219-222, 226

amphibole 56 anastomotic drain. p . 193 anisotropic crystals 22 annular drain. p. 198-199 antenna temperature 3 9 antivignetting filters 100 ARIANE 364

chloroplasts 7 6 chlorophyll 76, 78 colinear drain. p. colour vision 98-101 complex reflactive index 26 compound aspects interpr. 182 cones (eye) 94-95 Cosmos series 366 cotton leaf temperature 84-86 crab 160 crop calendar 269 drops (interpr.) 203 datastream 359-360 decibel 44-45, 322 dendritic drain. p. 198-199 density (film) 126 slicing 152 deranged drain. p. 193 detectahility 142 dielectric constant 23, 326-329 relative 23-25 diazo-film 129-131 dichotomic drain. p. 194-195 differential scattering coefficient

ASA 169

aspect analysis 182-183, 267 atmospheric correction 267 influence 1 16 windows 40-41, 45, 249250

automated classification 278-2817 backscattering maximum 36 basic aspects interpr. 182 batch processing 132 Bhaskara-2 367 biotite 56 blue grama grass 250 Roltzmann's constant 16 Brasil 340-343 Rrewster angle 3 1 brightness 1 4 3 Calatayud &sin interpr. 267-280 calcite 57 carbonate 58 characteristic curve (film) 126-127 charge coupled device 111 Chinasat 367

322

diffraction 32-33 dimensional stability (film) 128 directional reflectance soils 64-69 plants 81-82 dodging 128 Doppler effect 316, 3 2 1 drainage condition 205 density 195-197 drift 1 6 0 earth emittance 18-19 education, training 369-371 electronic energy state 20 ellipsometer 119 elongated bay type 194-195 emissivity 17, 39, 58-59, 70, 8 3 EM spectrum 14-16 EM waves 12-13 E-phase system 348, 349-350 erosion interpr. 208, 227-228 ERS-1

364-365

extinction coefficient 42, 3 2 5 eye, aberrations 97

371

facet model 33-34 false colour photography 105-109, 236-239

feature plane plot 133-134 feldspar 55 field atennuation coefficient 3 2 6 field work 223-225 tropical forest 225 filter factor 102 fluorescence 37 lidar 315 forest damage 8 0 forward scattering maximum 36 fragment sensor 366 frame aerial mapping camarea 157-158 Fraunhofer criterion 323 frequency 14 Fresnel reflection factors 29-30 f-stop 170 gamma radiation techn. 363-364 geographic information systems 360 geological structures 206-207 granite 58 granularity 127 grey tone analysis 218-219 ground penetrating radar 332-334 ground resolution 141-142 gypsum 57 Hasselblad camera 170 HCMM 290-291

histogram equalisation 133 hot spot 83, 1 6 1 hypersthene 56 image contrast 143-144 features pattern 146 structure 144-146 texture 144-146 quality 143 restoration 131, 152-153 index of refraction 25 inferred aspects interpr. 182 Infrared bands 368 imagers 289 photography 176-177, 235 radiometer 306-307 scanners 289 techniques history 288

-

instantaneous field of view 142 interactive processing 132-135 Intercosmos programme 115 interference 1 3 filters 1 0 0 internal reflectance 3 2 interpretation flow chart 183-185 ionic crystals 2 1 iris (eye) 9 4 IRLS application 305-306 isotropic crystals 22 kaolinite 56-57 Kenia interpr. 213, 215-218 kettle-hole drain. p. 197-198 Kirchhoff's law 16 Kodak-Path6 masking 153 Lambert's cosine law 33 Lambert's law 25 land complexity 228-229 evaluation 226-227, 358-359 Landsat imagery 148, 149, 272 MSS 259-260 notations 263-266 RBV 259, 262 status 263 land surface 361-362 landtype 186-189 land use 203-204 large scale 7 Laser 314-315 legal considerations 368-369 limburgite 58 limestone 57 limonite 57 line scanners 246-248 luminiscence 37 Mapsat 363 medium scale 7 metals 2 1 Meteosat 290 Meteor 366 Metric camera 364 Microwaves (passive) 307-308 MRSE 364 mid Infrared 253 Mie scattering 41-42 mirror effect 22 MKF ( S o j u s - 2 2 )

115

378

models 360-361 modulation transfer function 126-127 montmorillonite 57 morphogenetic analysis 1 8 3 MOS-1 366 MSS channels 247-248, 250 multispectral photography 177-178, 2 39- 2 40 muscovite 56

pyroxenes 5 6 Quantimet 137-138 quantum-type detectors 111 quartz 5 5 , 5 8 Quercus alba 78-80

radar nadir-point 1 6 2 Negev 305 net-radiation 46-48 Nimbus meteorological sat. progr. 257, 290 NQAA 290 non-selective scattering 41-42 normal angle camera 167-168 -

-

oblique airphotos 155-156 opacity 1 2 5 opaque bodies 37 organic matter content 251-252 orthophotographs 1 7 2 panoramic camera 170-171 parallax 165-166 parcelling 203, 205 parent material interpr. 207 pedon 4 penetration depth 326 permanent dipole 2 1 photographic film 104-105 photobase 158-159 photomosaics 1 7 2 physiographic analysis 18 3 Planck's constant 14 Planck's law 17-18 plant leaf structure 7 6 plastid pigment 7 6 polarization 13-14, 22-23, 28, 68-69, 81-83, 321 filters 1 0 0 , 102 political considerations 368-369 polypedon 4 power absorption coefficient 325 scattering coefficient 3 2 5 principal component transform 134-135, 276-278 pinnate drain. p. 198-199

anal. drain. p. 339-340 applications 348-349 bands 3 1 5 equation 321-322 flagpole effect 335 image characteristics 335-339 image interpr. 339-346 parallax 337, 3 3 9 polarization 3 2 1 resolution 318-320 shadow 335-336 vegetation backscatter 334-335

Radarsat 367 radial drain. p. 197-198 radians 1 4 2 radiometer 1 1 1 radiometric temperature 3 9 , 2 8 9 radiophase sy st ems 347 - 3 4 8 radiowaves frequency 1 5 , 347 ratio's 135-136, 2 6 6 , 2 7 5 Rayleigh's criterion for roughness 34 Rayleigh scattering 41-42 rectangular drain. p. 198-199 reference objects 1 2 1 reflectance (spectral) 4 8 field measurements 119-121 refraction 2 8 relative turgidity (plants) 84-86 relief classes 1 9 0 displacement 164-165 remote sensing centres 369-370 courses 370-37 1 scheme 116 resolution (film) 1 2 9 , 1 4 1 resolving power (eye) 97 (film) 127 reststrahlen bands 5 8 retina (eye) 9 4 retinex theory 9 5 return parameter rods (eye) 94-95

-

-

-

379 r o t a t i o n a l e n e r g y s t a t e 20

S a l y u t 366 s a m p l e areas 224-225 S A R 321 s c a l e o f maps 7 a i r p h o t o s 141 s c a n n e r i m a g e r y d i s t o r t i o n s 148-149 s e q u e n t i a l p h o t o g r a p h y 240-241 s h o r e l i n e t y p e s 193-194 S h u t t l e Imaging Radar 363 s i l i c a t e s 58 S i n a i 305 S k y l a b 257-258, 290 S k i n d e p t h 2 6 , 327 SLAR 316-317 small s c a l e 7 SMIRR 257 S n e l l ' s l a w 29,31 S o i l c o m p a c t i o n 304 concept 4 c r u s t i n g 251 d e p t h i n t e r p r . 208 map 5 m o i s t u r e 61-62, 2 5 1 , 329-332, 36 3- 36 4 r o u g h n e s s 64-65 s t r u c t u r e 63-64 s u r f a c e 206 s u r v e y s 230 s u r v e y p l a n n i n g 233-234 p r o g r e s s 232 r e p o r t 234-235 t e m p e r a t u r e 74-75 t e x t u r e 62-63 v a r i a b i l i t y 225-226 S o l a r i r r a d i a n c e 18-19 r e f l e c t i o n p o i n t 161 s p a c e h o r n e p l a t f o r m s 113-115 S p a c e l a b 257 s p e c i f i c h e a t 3 9 , 72 s p e c t r a l f e a t u r e s I n f r a r e d 51 f i l t e r s 1 00 s e n s i t i v i t y I R f i l m 108 s p e c u l a r r e f l e c t i o n 27-28 SPOT-1 2 0 9 , 3 6 5 S t e f a n - R o l t z m a n n ' s l a w 16 s t e r e o p s i s 97 S t e r e o s a t 363 s t e r e o s c o p e s 162-164 s t e r e o t r i p l e t s 172-173 s t r e a m f o r m s 192-193

stream o r d e r s 195-196 s t r i p camera 1 7 0 s u p e r v i s e d c l a s s i f i c a t i o n 137 s u p e r w i d e a n g l e camera 167-168 s u r f a c e r o u g h n e s s 323-324 Suri name i n t e r p r . 212-215 s w a l l o w - h o l e d r a i n . p. 197-198

T e l l - u s model 299-303 T e r g r a mode l 298, 301 termite mounds 207 TERS 366 t e s t s i t e s 117 T h e m a t i c Mapper 261-262, 281-284, 291 The N e t h e r l a n d s 3 0 4 , 342-246 t h e r m a l c a p a c i t y 39 c o n d u c t i v i t y 3 9 , 72-73 d e t e c t o r s 110 d i f f u s i v i t y 39-40, 7 2 i n e r t i a 4 0 , 59-60, 300, 302-303 i n f r a r e d i m a g e r y 291-296 m o d e l s 297-300 t h e r m o k a r s t d r a i n . p. 194-195 1 1 9 t h e r m i s t o r 119 t i l t 1 5 7 , 161 t r a f f i c a b i l i t y 229 t r a n s m i t t a n c e 38, 125 t r e l l i s d r a i n . p. 198-199 t r e m o l i t e 56 t r i m e t r o g o n camera 1 7 0 t r u e c o l o u r p h o t o g r a p h y 105-106, 174176, 235 T u n i s i a 281-284

U l t r a v i o l e t 1 0 9 , 178, 248 u n s u p e r v i s e d c l a s s i f i c a t i o n 109, 178, 248

v a l e n c e c r y s t a l s 21 v a n d e r Waals c r y s t a l s 2 1 v e g e t a t i o n c o v e r 201-202, 331-332 v e r t i c a l a i r p h o t o s 155 e x a g g e r a t i o n 166-1 6 8 v i b r a t i o n a l e n e r g y s t a t e 20 Vidicon 111 v i s i b l e r a d i a t i o n 16

wi de a n g l e c a m e r a 167-168 I J i e n ' s d i s p l a c e m e n t l a w 17

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