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LANDSAT lMAGERY AND SMALL-SCALE VEGETATION MAPS -DATA SUPPLEMENTATION AND VER~FléATION:,

A ,CASE S,TUDY OF THE MARALAL AREA, NORTHERN KENYA

by

KATHRYN ALEONG-MACKAY

Depàrtmen't of Geography - MeGill- University, Montreal

Quebec, Canada

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A Thesis Submi t ted to the Faculty of Graduate Studies and Res'eareh

in Partial Fulfillment of the Requi rements for the Degree of

Master of Science -'

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e Kathryn Aleong-Maekay, 1987 "

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Permission has been grantea' to the National Library' of Canada to microfilm 1 thls thesis and to lend or sell­cop~es .of 'the fil,m.'

The author (copyright owner) h a ,5 r e 5 e r v é dot h e r publication rights, and neither the thesis nor extensi ve extracts from it ~

may be printed or otherwise .reproduced without his/her wri tten permi ssion.

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L'al,ttorisation a été accordée' à: la Bibliothèque nationale du Canada de micro filmer cette thèse et de prêterJ ou de vendre des exemplal res du film. "

L'auteur (tl.tulaire du droit d'auteur) se réserve ,les autres droits de publication: l. nï la thèse ni de longs ext-raits de, celle":'ci ne Aoivent être imprim~s ou aùtr~ment reproduits sans son autorisation ecritè.

ISBN 0-315-38291-0 , '. , "

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• • ABST,RACT

Landsat imagery can , contr lbute to a ' fuller

,understandlng of the detalls . shown on sma ll-aea le

" phys i ognoml c vegeta~ion maps 'whic'h have b-een prepared uSlng

c.onve nt 1 ona l metnods. - The images provlde supplementll r y .)...

information ab6ut vegetation types and boundar le~L .

Simple, inexpenslve densltometric procedures permitted -' , , '

the establishment of spectral ..(

signatures for "seven ..

vegetation types wlilch are wioespread in the se,ml-àr id , area

of northern KenYè;i'. Anomalous '5 ignatures were found, to .,'

resul t from errora ,in typlng and boundary p1acement f'pr ,

several of the vegetat!'On formation complexes in the ~arala 1 , '

district. Ground' truth for the work· conslsted of pn .

<: assumpt,iQn .'of factual acquracy of the contents of the

vegetation map,.

Developing nat Ions ' can greatly' bènefl,t hom

densitometric-based pr9cedures whic.h provide u13eful

information about veg~tatlon coyer ln an effective manner.

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RESUHE

, L' ut111sation des, ,images "Landsat" permettent 'une 1

rIl.e 1 H-etl~e lnterprétat Ion des-,.déta ils ind lqués sui: les car tes ,\.

physlognomiques de ~ vé,gétation à pet! te échelle préparées

s'e lon les m6thodes convent 1 onnelles.', Les images fournissent , . 1

des renseignements supp16mentaires concernant les espèces de .' ( . vég~tation et les lIgnes de dé'marcation de ces dernières,

L'emploi' d'une , ", ..

procedure densitometrlque, a la fois

,simplé et peu '" couteuse, a' permi l'identification de~

. , ..----­signatures ~pectrales et leu~ applicat ion à sept éspèces de

,. rigi,on sem!-

,. gui se trouvent repandues dans la

.ar ide au nord du Kenya. Des signatures irré9ul~è~es, ~ . , ~

,remargu6es dans plusieurs concentrations v~g6tales dans la ;'

région de' Maralal. fure~t ,la cons~n~e des erreurs de

classement ~t de ~marcatlon. Afin d'6tabllr un point de

dé'part p4ur la ,

presente étude, nous avons pris comme

hypoth~se gue les d6talls. pr6sentes sQr la carte

v'9é't~tion 6taient pr€'lJa. ,

de

: Le;3 pays en vole de d~veloppement pourront bê"rié'Ucler '.

d'une ',proc6duré basle sur des. techniques dens ftomitr igues.

Une telle .procldure f~urn.iralt, d ',une faion' efficace, des

ren.J5e 19nement's pratiques su~ la nature du terra in. \,

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ACKNOWLEOGEMENTS

Throughout this study l was pr iveleged to b~.nefi-t from 'the practical support and ericouragement of many.~Lt th~refore gives me great pleasure to acknowledge, with:';cjratitude, the assistance provided by a nûmber of people. ra all, 'a, heartfel t

"THANK Y~U 1" '1\

1'0 Dr. John T. parry,' my supervisor, for his assistance tn acquiring the images and air photos, his suggestions on methodolQgy, and his. p,atient and carefu1 editing of the nùmero~s drafts. "

1 To the Canada Centre of Remote Sensing for access to their equLPment while in OttqWai ,and especial1y to the RESORS staff (Gale,. Louis, Terry and Dave) whose knotjledge of tHei r mater iai greatly ~acil i ta,ted' the 1 i teratu re r~v iew process-. ,,/ ,

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To Bill Bruce for his thoughtful suggestions' at th~ early ~tages of this research and hi"s sustained lnterest' in the thesis.

To David Mungai for access to his rainfa11 records for the 'Maralai area and his en1ightening porrunents on the climate ai hi~ country. ',-

Ta Di rk WeI; le for his help in translating the Badèr mon'Ç)graph from German. Danket

,-Tc Helmut Epp for information forwarde? to me .f rom Kenya.

" . Ta my friend RUI~h Métljor-Almond who introduced me t0 the \\(onders of ward process ing and thus helped ta s illJPli fy the whole process of writing and rewriting.

'Ta two generations~ of friends and co11eagues in the Department for their advice, encou r agement, pl actical help and personal support; aIl those conversations over eoffee and lu~ch were perhaps the most interesting aspect of graduate school.

Td my brother, Chr is, for his expert help with the graphing of the densi tomet r lC da ta.

To my Montreal family who put me up through the long monthe of writing. and rewriting and provided a home, away Erom home.

" Above aIl, to my husband, Don, whose constant enc~uragement and support, often across two conti~ents and one ocean, showed me the 'true meaning of commitment and caring; and to my parents and godroother who introduced me te the joys of learning and made i t possible for me td get to where l am" teday. This ls dedicated to you 1

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TABLE OF CONTENTS

Abatract ................... "'.f .................... ~.j,., •• ). 1

Resume........................ ............ ........................................... 11

Acknowledgemen~t5~ ........................ " ............................ ~ " • ...... 111 /.P , •

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Table of Contents ................................ , .......................... .

List , .

of Figures ............................................ : "' ...... ' ...... . ,

L 15 t 0 f l' Ta b 1 es, '/" ................... , \ .................. ,1 • .. .. .. .............. '1 l' .. .. 1 1 _ 1 1

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List of Plates ............. ~ ...... , ............................ '" ............ .. , . ~

List, of Appendices ............................................................. ,

.. CHAPTÈR 1 INTRODUCTION .......... "' ... , ......... " .. ~ .. 1.1 1.2

1.3 1'.4 1.5

" . Small-Scale Vegetation Mapplng Procedures ••..••.• Landsat and small-Scale vegetation Mapping:

Data sùpplementation.and Verification ....••..•. -Research Ob:JectJ. ves .. : ............ ' ... ' ........... . The Basls for Study .Àrea Selection .............. . Thesls Format .. "" .... """ ........... "" ...... "" .. " ..................... " •

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SECTlpN 1: THE BACKGROUND

THE MARALAL TRANSECT:

2.1 2.2 2.3 2.4

PHYSIOGRAPHY, CLIMATE AND VEGETATION .... .. ......

Physical Landscape ....•...... -:-. . . . . . . . .. .' ...... . So11s .••..•••...•.... , .•••... , ...................... . Clll'l\ate ••...•. ~ .••••.. If-;--..................... ' •••••• Veget!at 1 on "" ..... "",, ~ ... " " ....... " " " " ..... • ..d • ...... " .. " ..... " " ~ " "

2.4.1 _ Land Cover ." ....... " .. """ .. " ......... """" .... " .. "" .'."" ~.4.2' Land Use Bffects .......... " ........ " ....... " ........... " " " "

CHAPTER :3 THE VEGETATION MAP .... " " " " ........ " • e .. " .... " ............ ..

CHAPTER 4 THE, PHYSIOGNOMIC AND PHENOLOGlCAL CHARACTE~ISTICS OF SEMI-ARID VEGETATION

4.1 Pnyslognomic Characteristics of. Semi-Arid. Vegetat ion ........ " .' ........ " " ....... " ...... " .... " " .... " " " " " .. ,~ " " "

4.2 The Phenology of Semi-Ariet Vegetation ',' .•.•••..•.• ,.

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CHAPTER 5 LANDBAT AND SEMI -AR:tD VEGETATION ... ,. , ...... , S.l Landsat and Vege~ation: The General Relatioq~hips

.. 5.2 Landsat and the Seasonal Changes in" the spectral Cha;racter iatics of Semi-Ar id' Vegetation ....... .

5.3 Landsat and Semi-Ar id Vegetat ion Stud1es ...•....•

SECTION II: LANDSAT IMAGE ANAL'iSIS "

'CHAPTER 6 PENSITOMETRIC DATA ACQUISITION FROM THE 1 LANDSAT 1 MAGES ••••••••••.•••••..••• , ••••• "

6-.. 1 Introduction .... " ...... .' ......................... . 6.2 Selection of Landsat Images for Densltometric

AnSi\lysls """"""""""""""""".""""""""""""""""""" .1, 6.3 Consttuction of a Sampling Overlay .......... ",'" 6.4 Measurement Procedure . ,-...••.•. j ••• , •••••••••••••

6.5 proces'5ing of the De ris i tometr ic 'Da ta ........... .. /~-.

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CHAPTER 7 ANALYSIS OF THE DENSITOMETRIC DATA •••••••••

7.1 7 • .2.

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Introduction """"" .'." . " """" " " " .. "" " " "";J,, " " " """ " " """ Discr Iminàt Ion of vegetat'lon Types ln the Dry .

Season (March) """" .• " ',' " " " " " ,_, " '," " " " " " " " " " " " " Il ,

7.2.1 Dens!tometrlc Analysls and Featu~e Space Separat·lon .... .' ..... ",. ..................... ~

7.2.2 Band Rat 1 os - %Red ; %Gteen Transmlssi on ..

7.3 Seasonal Change in the Vegetation Coyer .. o •••••••

1.3.1 Vegetation Colour Shifts Assoclated wlth Seasonal Change ,4 •••••••••• ~ ••••• l' • •• ' •••••••

7.3.2 A Comparlson of %Red:%Gre-en Tr~nsmls8lon Data' for March 25 and September 21,1975 o.

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7.4 Trans 1 tion Zones - Ecotones ••...•• ',' ........... 0 •

'7.5 Summary of the Denai tometr le Data Analys is

CHAPTER 8

. . SUMMARY ~D CONCLUSIONS . " ................... ..

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LIST OF FIGURES

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2.1

2.2

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Location of the Maralal !ransect ..••••••. ~...... 13 , '

Physiographic Types of the Maralal Transect •.•.• ' 14 ,-

Cross-Tr:ansect Prt>files .•..... ~ •.... •••.. . • ...•• 16 .

Soil Categories of the Maralal Transect .:....... +8 Eco-Climatic Typei pf the M~ralal Transect •....• 22

Annual Precipitation for Weather Stations Within or Close to the Mara~~L Transect ..•..•.

~ .. Monthly Precipitation for Weather Statiops

Within or Close ta the Maralal ~~ransect -

Vegetation Formation Groups and Complexes

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of the Maralal Transect •.•.•• :................ 39-,

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Physiognomy of Semi-Arid vege~ation Types ... ~ , ... , ,,- 1

Landsat and th~ Formation of Fa1se Calour C0mpo s i tes .. .......... 0 • • • fil • • • • • • • • • • •• Il • • • • • •• 0

. ,Typical? Reflectatlce Curve for Green vegetat ion ..

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.' The General Relationships Between vegetation\an~ Soil Reflectanèes Ov~r a Seasona1 Cycle •• f •.••

The Macbeth TO-S04 Tran~mission Densitometer and its Filter Characteristics ' .................... .

Densitometric Sampling Overlay and Idèntificatiori Gr id. • • . . . . . ...., .- ....... ,e • • • • • • • • • • • • • .. • • •••• \ •••

Densitometric Data Collection Sheet •.•••••••.. '~. , ' , v Registration of the Sampling Overlay and the

Afrika Kartenwer~ Vegetation-Map ..•••...••••.. 'l,>

%Ttansmission Ternary Diagram of Ali "Within , Category" Densitometric Data for the Maralal Transect Landsat Scen~ 2062-07052 (March 25, 1975) ....... 0 ••••••••••••••••••••••••••••••••••

7.lb %Transmission Ternary Diagram of Ali "Wi thin Category" Data for Vegetation Types 41.2, 64.1, 67.5 and 14.0/.2 .... ~ .................•.......

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%Trans~ission Ternary Oiagrams of AlI "Wi thin çategory" Data for Vegetation Types 51.0, 52.0 and 52.1 .................. ~ .................. ~ .. 105

7.2a Red:Green Filter (IR:Red Reflectance) Scattergraph ,.. tror AlI vegetation J"ypes in the Marala"l Transect Landsat Scenes 2062-07052 d( March 25, 1975) ..... 112

7.2b Red:Grêen Filter (IR:Red Reflectance) Scattergraph for Vegetation Type.Sl.0 ....................... 114

7.2c Red:Green Filter (IR:Red Reflectance) Scattergraph for Vegetation Type 52.0 .••••.••••.•.•••.•.•••. 114

7.2d Red:Green Filter (IR:Red Reflectance) Scattergraph

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for Vegetation Types 41.2, 64.1, 67.5, 14.û/.2 and 52. 1 •..•••••.•.• t .......... ' .. : .. ; . . . . . . . .. 114

Histograms of Diffuse t>ensity Data Obtained from Landsat Scenes of the Maralal Transect for March 25 and September 21, 1975 •••...•••••.•••. 118

7.4a %Transmission Ternary Diagrams of Da ta trom'I Sample Cells 1 - 180 for the Marala1 Transect Landsat Scenes 2062-07052 (March 25, 1975) and 2242-0704L (September'21, 197-5) ................. 119

(.4b .%Transmission Ternary Diagrams of Data·from Sample Cells 1 - 180 for Vegetation Types 67.5,64.1, 41.2 and 14·.0 'for March 25 and Septembe,r 21,197.5 .•••..•••••••.••.••••••...••• 1,21

7.4c %Transmission Ternary Diagrams of Da ta from Sample Cells 1 - 180 for Type 51.0 Vegetation for March 25 and September 21, 1975 ..••.•....•• 124

7.4d %Transmission Ternary Diagrams of Data from Sample Cells 1 - 180 for Vegetation Types 52.0 and 52.1 for March 25 and Septeqtber 21, 1975 ................................... . t:t.~_ ..... 129

7.5a ~ed:Green Filter (IR~Red Reflectance) Scattergraph~ of "Within Category" Data for All vegetation Types from Sample Cells 1 - 180 for aIl Vegetéttion Types in the Marala1 Tranaect for March 25 and September 21, 1975 .•••..••••••.••• 135

7.Sb Red:Green Filter (IR;Red Refleetance) Scat'tergrapha "

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of Data from Sample Cells 1 - 180 for Vegetation Type 51. 0 for March 25 and september 21, 1975 •. 137

Red:Green Filter (IR:Red Reflectance) Scattergraphs of Data from Sample Cella l - 180 for Vegetation Type 52.0 for March 25 and' September 2'1, 1975 •• 138

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7.5d' Red:Greèn Filter (IR:Red Re(lectance) Scatterg'raphs of Data> from Sample Cells 1 ... 180 for Vegetation Types 67.'5,64.1,52.1,"41.2 and 14.0 for March" 25 and September 21, 1975 ••.•••.•••••••••.•••••. 139

7.6 'Transmission Ternary Diagram ~for AlI (the Type 14.0,14.2/51.0 Ecotonal Situa'tions ..•••••.••••• 143

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7.7, 'Transmission Ternary Diagram of AIl the Type 51.0,52.0/64.'1 and Type 64.1/67.5 Ecotonal Si tuatîons , ............. ~~ .... . -......•......••. 149

7 .. 8 Proposed Revisiofls to the Vegetation Details ,Shown on the Afrika Kartenwerk as a Result of the·Densitometric Analysis ••••••..• ~ •••••..••• ~ 155

C-l 1: 50 000 Panchromatic Ai rphoto Cove rage of the MaraJ.,al Transect •••••..•••••.••..•••••••••••••• 178

C-2 .. - Pie-Segments of the Airphoto Overlay ............. l

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2.1 Weather Stations Within or Cl~e to the Maralal • Transect ..........•....••....•••...•......•.•.• "

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3.1 Vegetation ~ypes of the Maralal Transect •.••• : •••. 40

4.1 Major Phenological Events of the Central and Western Sectors of the Maralal Transect .••••... 50 \

5.1 Landsat Multispectral Scanner {MSS} Bands ........ 55

6.1 The Relationship Between Density, Transmittance and Reflectance ................................ 75

6.2 Landsat Coverage of the Maralal Transect ..••••••• 79 • .

6.3 1975 Antecedent Rainfall Conditions Relative to the Landsat Scenes .• ,,p' • •••••••••••• '. • • • • • • • • • • • • 80

6.4 The Number of Optimum and Acquired Density

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M.easurements for Each Vegetation Type fr:om .•.• Each Landsat scene .•......... III • • • • • • • • • • • • • • • •• 91 t

Summary of Densitometric Data for the Various"'­Vegetation Types of the Maralal Transect Obtained from Landsat Scenes 2062-07052 (March 25, 1975) and 2~2-0704l (September 21, 1975) .'. 131 .

7.2 Classification of the Ecotonal Sampling Cells •••. 141

C-l Airphoto Coverage of the Haralal Transect ........ 177

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PLATE PAGE , ,

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l ,Landsat Image for the Maralal Transect for Ma r ch 25, 1975 ........ ., ........•.........•...•

Landsat Image for the Maralal Transect for September 21, 1975 ................... ~ ••. ' ••••••

- . -3 Stereogram of Sample Cells 277 and 287 .•••••••••

4 Stereoram of Sa~le Cell 245 .....................

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PAGl::

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Densitemetric Meàsurements of Landsat 'Scenes 2062-C1i052 (March 25, 19751. and 2242-07041 (September 21, '-1975) tif the Mara1al Transect , , .... 158

S Optical Density te Percent Transmission Conversion Table ......•••.•••....•.....•....•••• 173

c Airphoto Coverage of the Maralal Transect •.•...... 175

o Change in Percent Transmission Data for Sample Cel1s 1 - H~O of the Maralal Transect ..••••..••. 179

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CHAPTER 1

INTRODUCTION " .

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AIl developlng countries fàce the task of' formulatlng a

rational plan for the1r econom1c development." Such a plan

requlres an Inventory and assesment of the country's natural

resour,ces. Hence, resource mapplng ànd the establishment of

a rellable data base are top prlorlty Items for these

countr les. In add 1 t 10n, there 15 a need to monl tor the

dynamlcs of - resources 50 that management polleles can be

adjusted accordingly.

The natural vegetatIon of a country 15 one of its' most

important resources. Data on the type, 1 quant 1 ty and

distribution of vegetation present in a par~icular area at a

partlcular time, are important toola ln the management of

the area. Thus, a vegetation map ia an 'important planning

document. _ Small-scale mapa, at scales of 1: 1 000 000 or

~maller, provide an overvlew of a whole country a~d permit

an examination of the geographical distribution and types of

~egetation in relation to other 'natural resource~. ,

Many developing countries lack the capabl11ty to -""

effectively map their vegetation d,ue to such constralnts as-

the 5ize of the country, poo~ infrastructure, and a lack of

~r~lned manpower. Tradltional small-scale vegetation mapplng

methods, which depend on compilation from varlous sources,

c aerial , .,

photography and field 3urveys, are costly and time

consuminq. What ,is needed 15 a method whiçh can effectlvely

overcome these çonstraints and provide a slmpl~, inexpensive 1

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wayof mapplng vegetation o~,<:where:vegetatlon maps already " .

exlst, of verlfylng the accu~acy and supplementlng~ th~

detail provided ~<;>n those rnaps. This 15 especially important

when the maps were prepared sorne t ime aga.

\ Remote sensing can make a tnajor contrlbution ln up-

datlng ~mall-scàle vegetation maps and' verifylng the

boundar les and type detai 15. The un ique features of the

Landsat serJ.es of satéllttes rnake Landsat lmagery

partièularly uS.eful in thls regard. In thi:s thes ls a-

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partlcular case \ study' 15 presented for a small-scale

vegetatton mat> of an area of .seml-arld , ' \

northern Kenya.

Before the spec 1 f ic r~séatch object 1 vcs are outll ned t a /

br:lef _ assessment of .the problems assoc1ated wlth the

verifIcation of srnall-scale' vegetation maps 13 presented

together wlth a general indication of the geneflts to bo

gained from incorporatlng detalÏs derlved from Land:sat

llnagery.

1.1 SHALL-SCÂLE VEGETATION MAPPI~G PROCEDURES

Two - ma'1n methods currently ex'lst for constructlng

small-ecale vegètatlon' map~, (Kuchler, 1967). The first

method . 19 v la pr imqry mapping. This method requirc,s the , 1

acqulsitioh of a cover of ae~lal photographs, delineation of

, .- the apparent ar:eas of, vegetation homogene 1 ty on the photos,

and, then a. field survey to ,ver,lfy the boundarles and

ldèntlfy the vegetation units encl-osed wlthln them. Because

of the làrge area coverage requlred, prlmary mapplng p06e~ a

considerable problem. Aer lal photographs of ul')lform qual1 ty,

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~cale ~nd 'date are rarely aval1able. Even 'if such cov~rage

'fias aval1able,' utll1zation 'Wouid pose a" severe handlÜlg ,

ploblem due to the number of air photos Involved.· Further

compoundlng the sltuat-lon ls t~rhe-synchronlcity ~of _ the ,

photograp~y. Mos t sets of al r pho-tos cov~r lng ~arge areas

have been acqulred over an extended per lod of time '. In

add 1 t Ion, the reduct 1 on of th~ manuscr 1 pt ma p from the

compIlation scale to the s!llall scale- of the .final map ls'

bath difficult and cost'ly because 1t Involves generalisation \)

and re-draughting.

The second method of generating small-scale vegetation

maps 15 the more corrunon. rt involves the compilation of aU

previously ,publi shed vege ta tian maps 0 f the ar ea of

lnterest. Common legend elements are extracted for a

compas 1 te legend and the maps are complled ont a a common

base. This method 1s feas ibie only U large- and med lum-

scala maps have prevlously been produced for the 'entire -

study area. In addItion,' the legends' oF the maps being us~d

for compIlation must be compatiQle. The pr ocedure 18

," imposs~ble H sorne of the m.;ipS are based on difflcult 'or

floristlc categor les, whlle others use physiognomlc or

~colo9lc ~lasses. ,

Hap~ constructed ~slng th~ compilation technique are

subject , to much \

greater t',

error than . ,those 'produced. via

prlmary rnappi~g. VerificatiQn of the accuracy of complled ,

maptJ by the' t,rad 1 t lonal ~ethods r-equ ire aer lal photography

an~ costly field surveys. Th~ unlqùe features of the Landsat

MSS system provlde a more affordable means of verlfylng

3

" f

·0

"

...

, , "

, .

, ,

.... _ ...... - ...... _ .. _ .... _-----------------------these 'n:!dPs and supplylng ada l tiona,l det~ 11.

, . , '

, 1.2 LANDSAT AND~, SMALL-SCALE VEGETATION MAPPING: DATA SUPPLEMENTATION AND VERIFICATION

Since 1972, Landsat satellites ~ave been travelling in a

clrGular,. near-polar, sun-synchronous orb.1,t arou,nd the earth

(NASAy , 1976), The Landsat sensing systems* provlde broad , synoptlc coverage as they. view a 185 kilometre swath of the

, , ear th sur face, wl th a ground reso-l pt Ion of 79 square met res .

The Landsat Mul t lspectral Scanner \ (MSS) sense s

electromagnetie radiation in th t 0.4 to 1.1 um range, which

'15 . the most useful speetra'l region for studylng vegetation

(Curran, . 1981~. The narrow angular fie1~ of vl~w of the

system results in an image with 1 i ttle geometr le distortion

and un,iformly reliable levéls of, infor,mation in aIl parts of

the image area. Thé l8-day repeat cycle provides images at

different seasons , 'which permits the assessment of temporal

variations in ground conditions. "

. Landsat data products ln lmage;ry format are suitable <,

for comparlson with sma11-scale thematic maps. In addition

to, the digital products (éCTs - 'computer compatible tapes), -

such data are âvàllabre as ·black and w:hite' positive and \

" , negative transparencles' for each of the spectral bands at

the 1:3 369 OOO-scale,' b

and as fl~f(\ or prlnt enlargements at

scales of 1:1 00.0 000 , 1:500 600 and 1:250 000. 'It Is also

possible to obtairi false colour composites of thr'ee spectral 1)

.*' The description app1ies on1y to Laridsat 1, 2 and 3 r

Landsat 4 and 5 have a. lower orbi t, a 16 day repeat cyc1e, and expanded capabll1tles wlth thelr Thematic Happer.

( "

, '

"

bands ln ~he form of pilnts ~r't~anspa6encles. ,

The U. S • Goverriment' 5 oper~tlon of Landsat in the

"international public 'domaln" (Sabins, 1918), t.ogether' wi th

" NASA'{j programme of international coopera'tion, has resulted .... T " '

, -

"

ln world-wlde avaLl.abUlty of lmaqery'qf almost any reglon

of the earth' s surface to users ln de.veloplng: countr les.

This has been ,encouraged by the r~elatlvely 10w cast' of

Landsat prbducts, ranglng from $36 to $203 (Canadian

do lIaIs)· for paper p'r ints and trarfsparenc les at dl Herent

scales, (Remote 'Sensing in Canada Newsletter, \ol1nter 1985).

'Ttf~ , Landsat 'system provldes both -a synoptic view and a " '

unlform mapplng base. The scale of the Landsat image' 15 such

that the l ,~ .v

problems assoclated w1th the,reduction of a map

manuscx ipt . ,are effectl vely el1mlnated. ' There 15 the added

that un'necessary det;:all has already been

generallsed out Qf the image as~- a functlon of the spatial

resolution of the' M~S. The problem of patchwork al r photo . ~

coverage from dl fferent dates is also ellmlnated</oas Landsat

can , prov ide a single date total coveraqe, an esséntlal

element for regional studres of veget,atlon. In addition,

coverage of very large areas can be obtalned, processed and

presented to the user ln a much shorter tlme than ls

poss Ible wi,th ,Cènvent lo'nai map,plng procedures, part lcular ly

ln remote areas wher,~ 'access ls lim1te~l. The spectral ,

sensl tlvl ty of Ban~,s. 6 and 7 permi ts good deflnl tlon of

vegetat~ ve' patte~ns) while the repetl t 1 ve coverage allows

for regular updatl,ng of the maps (van Zuylen, 1978).

Landsat imagery at the 1:1 million scale have be~n'

5

"

o

,\ '" ,1

" utllized tp map and analyse vegetation at thls scale (Clhlar ... et al. 1978" Dlxon' 1981, Dr15coll et al. 1974a, Gwynne 1977,

Tueller et ,al. 1975, Williams and Coiner 1975). These

studles ~

showe~ that when used as colour composites and , '

judiciously chosen as ta season, Landsat lmagery can be

effectlvely' us,d as~a.mapping base for the preparation of

vègetation maps at the regional or'Formation level.

S ln'ce the Landsat MSS colour composite image is .' i

suitable for small~seale vegetation mapping, it should alse---,

be useful for verlfying small-scale vege'tation maps produced

by other means, . and for prov 1d Ing add i t iona 1 deta Ils wh 1ch , '

can help ln the r~fin~ng' ~nd_ rev'ision of eX!stl\ng maps. It

15 these specifie applications of Landsat colour composite'

irnagery which will be' Investigated i,n this thesis. ~~

1.3 RESEARCH OBJECTIVES

On the basts of the previous, discussion, the, general

.. objectives of this. thesis are -,

" ,

'1

to assess the role of Landsat MSS colour composites in verifying tne accuraey of an exlsting 1:1 million vegetation rnap which was prepared using the. compilation method;

to derivç addi~1onal or suppl~mental detall relat'ing to the physiognomy and phenology of the vegetation in a selected test area.

In order to achleve these \ objec~l ves, ~andsat lmage'ry,

attent~on will be glven to the followlng tapies:

1) the ~labora~ion of the "photomorphic" characterlstlcs of the vegetation l types within the mapped boundaries;

, \

li) the, identification Of relevant phenoloqlcal chara~terlstlcs;

6

1 .

c

c

.. -"

',' . " Ill) the deflnltlon,of the boundar~ f~cotcihal)

cha~acterlstlcs.

. ,

Much of the predent-day analyses of Lapdsat data

concentrate on, computer-based t~cbn lques ut III z 1 ng the ·CCTs.

Whl1e the use ,of Landsat data 'in digital format perm,lts muth .

more detailed study of the area or subject ~f interest.than 1

ls possible Wl th t~e pr Int and p~per p'roducts, the use of

ceTs. has now become relatlvely e'xpenslve*, especially whère

country-wide coverage is desired~ Small developing . nations ct ,

.cannot afford the costs associated with computer-based ~

techniques., In addition, they often lack the trained , ,

manpower and the facilites necessary to'operate and malntaln .

the sophlsticated computer 'hardware ana software. However,

1 t 13 these' very nations wh''ich can grea t Iy benef i t from

remotely sensed data, especlallIy where the areas of,lnterest, .

Da~is (19BO, pp. 1-2) ,adequatel,y

descrlbed the situation when he said that:

-

.. many ~sers of remot~ sens1ng data hane'a need for low technology means of utilizing imagery, due to low technological capabiIlty, low personnel re50urces, 11mlted flnanclal resources, or slmply low priorltles. This Is especlally· true in the develop1n5l natlop5 o~f the wor'ld. There i5 a demand for a • mi'aale-ground 1 -approach; someth Ing beyond simple unsystematlc manual Interpretation, but somethlng less èomplex than computer based methodologies."· ,

* The Landsat programme has been recently transferred to ~ , the Amerlcan prlvate sector and'commercial rates for Landsat

data 'PXOduct5 have béen establlshed (Landsat Data Users Notes, Issue No.35, March 1986). ' .

7

:

",

("'.. , l,

The ' ana/ys is of Landsatl~"I..sS data in imagery format

~sln9 manual techniques and instrumentation 15 a 5uitable

"mlddle-ground'''· approach, a ~practleal alternative to

1 utll1zing th~ expensive CCTs, particu}arly where broad-scale ,.. analysls is satisfaetory. Any developing country can afford

to purchase desk type equlpment such as densitometers. These 4

- instruments do not require cllmate-controlled environments,

nor ,do they need ma in-frame computers to handle the" d,ata

generated. In exploring such an approach, this thesis

assesses and

technology" .

demonstrates the ~)

capabll1tles

1.4 THE BASIS FOR STUDY ARE~ SELECTION ,\

!

o,f "low

fJ

Cr il' The long standing institutlonal linkage .betwen the

,Vniversity of Nairobi and MeGill university, whlch, has been

. providlng gradua te training for students from" Kenya·' si,nee

1970# influeneed: the chQiee of a study area from that

COl.1ntry.

Kenya 13 a developing natlo~ faclng the task of

assesslng and manaqing its natural ,resources, ~

part 1eular ly .

in its nor~hern semi-arid areas. These lands, whlcn "

eompr Ise more than two-t-h irds of tl)e, courytry, are reg Ions of

low popu~atlon denslty, due ma1nly ta the consttalnts

imposed ~Y low water 'ava'ilabl11ty (Ojany' and. Ogendo, 1973).,

For the most part, local, vegetation 13 characterlzed by

• sparse bush and grassland, and has traditlonally been used

by nomadlc pastor?lists.

Ther~ 15 concern about these,oem1-ar1d lands as they <' \.

,8

"

(

have been under severe envi~rnental stress throughout the

19705. The ~Sarnburu District holds special Interest because

of- steep ecological gradients and the fact that there- is

'potentlal confllct between dlfferent land-use practlces,

such as pastoralisrn, cash crop f~rming and forestry. Hence,

- ~a tran~ct wa~ selected in this area of the country which

Includes, a varlet y of ecocllmatlc zones (ranglng from arld

to sub-humld). In this thesis, the transect -Will be

referred as the "Maralal transect".

A number of vegetation maps exl~t for this area

(Chapter 3). ,

An up-to-date assessment of the accuracy of 1 •

these rnaps 1s essential for reglonal planning.

assessrncnt would provide an 'indication of the actual

such an '"

extent )

of those types which r;

are essential to the

pa5torallsts, and those whlch-need to be protecte~; for

" ex~mple, , the forests wl)lch act as important catchment areas

in this s'emi-ar id, climate.

1.5 T,HESIS FORMAT

The thesi5, is divided into two sections, Section 1:

Chapt~rs 2-5 and Section 2: Chaptets 6-8 ..

Section 1 provides'background data. In Chapter 2 there

15 a discussion of the general geographical characterlstlcs

of the transe ct (topography, so11s, èllmate) and a

description of the main vegetation types and' their

distribution within the transect. Chapter Three examines

the details 'of the' map chosen for this ~utdy - the Afrika

Karternwerk vege~atlon map~ ln Chapter Four there is a

9

7

/

."

1 , "\ ,

,

.\

o :

) discussion of the physiognomic and phenologlcal

character18tlcs of ,8eml-arld vege~atlon, ,a kliowledg~ of

whlch 15 nece5sary ln arder ta understaRd how the various

vegetatlbn types of the transect appear on Landsat imagery.

The reasons for Landsat's particular suitablilty for

vegetation studies 1s examlrted ln Chapter F1ve. In addltlon~

there ls discussion of t~e varlous phen,ologlcal change,s--...-..-A'

experlenced ln the seml-ar id zone an1:' the e f fects on'

vegetation signature~ as they 1

appeali' on - /

faise colour

composites. The results of some of the research conducted ln

anaiogous zones is examined and the implications are

assessed. . "

Section .Two describes the' method used to analyse the

Landsat imqges and the results of the analysls. In Chapter 6

the "middle-ground" densltometric method applied 1s

descrlbed. The selection of the Landsat images is dlscussed

along wlth,the procedure for systematlcally acqulrlng and ,

processing th~ denslty data. Chapter 7 analy,ses the density . data and discusses the results in the context 'of the.

research Il)jectlves', while" cnapter.· 8 "')

conclusions ôf the thests.'

\ ,,, " ..... ' \ ;

" /

10

presents

- "

'.

c -- (

-

...... , m

o "

-

o

CHAPTER '2 1)

THE MARALAL TRANS&CT: PHYSIOGRAPHY, CLIMATS AND VEGBTATION ~

..

The Maralal transect ls located ln the Rift Valley

Province of northern Kenya, south of Lake Turkana. rt ,

Includes parts of the Sarnburu, Turkana and Barlngo

,administrative districts,. The transect ls centered on the

town of Maralal ~which 15 about 270 kilometres north of

Nairobi (Figure 2.1) .. It stretches_from lON to l030'N and

from 36°E to 37°30/E, coverlng an area of approximately 8635

square kl10metres (157km x 57km) r

The types of vegetation present ln any area and thelr , ,

distribution are a functlon of the comblneà effects of ~he

topography, soi~_s and climate.. These three e,lements

area will therefore be examlned first in order

to provide a clearer understanding of the resulting

vegetation types and thelr distributIon patterns.

2.1 PHYSICAL LANDSCAPE

MaralëU trat:1sect Is topq,graph1cally diverse. There are

a varlet y of landforms from recent volcanics to extensive

peneplaln surfaces. The transect can "-

major pnyslographlc typ~s accord l,ng to '\

valley, Eastern Highlands, uaso-Ngiro

-Plateau (Flgur~ .2.2).

. , ,

,"

/J" ... _

12

be dlvided lnto four

ojany (1966): Rift

Basin, and For_e~and

" '

( ,

o

.' -

TANZANIA

----

HARALAL TRANSECT

OlSTRICT BOUNOARY RIFT VALLEY PROVINCIAL

BOUNOARY INTERNATIONAL BOUND~RY

fIGURE 2-.1 -LOCATION

,s , ..

œ

'. MARSAsI T

Landsat Scene 181 59'

KENYA-

. \

OF THE MARALAL

13

....

IND/AN OCEAN

TRANSECT

, \ , '\

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J {'

1 1 JI

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~"~ - .. ,«' .: k'l' 1/ • l ,0_-

/ 1 1 Il

IV

o • o 10

l .. RIFT VALLEY

'II EASTERN HIGHLANDS

rI! MIO-UASO NGIRO BASIN

,of IV LOW FORELAND PLATEAU

20 30

Id lomet-res

~ ,/1"

,.

<10 1

LAND ABOVE 1500 metres.

e 5iEP FAULTED SCARPS

LAVA FORMATIONS

----. INTERM.ITTEtn RI "ERS

"

J /

'/

, FIGURE 2.2 PHYSIOG RAPHI C TYPE S OF THE MARALAL TRANSECT

(aFterOOjan'y, 1966) ..

'\

-'

.. 14

/

. ,

, , .0

,-

, '

/

-.

• 1 "

, ' ...

(

., The Rift Vallel:

Formi ng part of the Great East Afr ican Rift Syst,em

(Dixey, 1956), the Rift Valley separates' the younger alld

higher volcanlc Tlati hlghlands west of the transect from

the (y

lower upland massl fs ot the Eastern Highlands. rr

North

and west of the Saanta Hll1s' the country drops s~eepIy, in

pl:aces even preclpitously, from a maxImum elevation of, 2585m

at Poror.\ The terrain 15 rocky and barren, ci iss'~cted by

gorges, and canyons, wh ich lead through, the Samburu scarp

into the Suguta R 1 Ver va Iley (Shack leton, 1946). The va Ifey

sides ar~ step-faulted scarps which ar~ separated from the':

valley floor by p1edmol)t plains. A numb~r of young volcanla

plugs and cones OCCUt on the valley floot. The most dominant r

of these 15 SUaI1 rlsing to 1526m.

The Eastern Highlands: ,

These massifs, \'1hich are composed of the reslstant'

"Basement System rocks, preserve traces of the oldest land

sufaces ln Kenya.' The Karlsla H111s, and the Mathew' Range

fotm two d iscont inuous, para llel ,zones t:re'nd ing nearly

north'-south across' the area. Thése old uplands, remnants of " '

, planation, surfaces, are, Identlf iable 1 n the generally

accordant summlt levels of ,the main peaks at about 2400m. As

seen ln cross-trans'ect profi1~s (Figure 2.3), ;re hlghlands

ln the central part of. the transect form a broad, undulatlng , '

u'pland area; in c~ntra3t to the ~arrowe~ and 3teepe~ Mathew3 v.,'

Range. The Highlands are drained by numerCU5 Int.erml ttept , '

tr lbutar les of the 'Tobe, Amaya, Barsa 1 0, l, Her1l1e aJ)d

'Sero~eyl Rlvers. ,

15 " .

• 1

"

Jô' i. ~LOHG . 1- 25'"

-METRES

2000

-}

i) 1000

SUGUT A RI 'HR

ALONG 1" 20' N

2000

, 1000

• 2000

RIFT VAlLfY 1000

r

ALONG l ~ 10' Il

( . 2000

1000

.. ALONG l' 05' N

2000

1000 '--~--""', .

. '

a ]'''30' t

LÙP ET PLATEAU

SUARE PLA 1 ~S

- "

(d)

SAANTA HlLLS

LOROGI PLATEAU

(

,/

. ,

'-

(

t.

The, Mid-Uaso Ngiro Basin: - Suare and I~ Ponyekl,Plains ,

Thi5' Basin 15 an Intermontane area located between the

Karlsla Hl11a and the Hathews Range' at an elevation of 9007""

1400m. The land surfa~e has been' lowered by eroslon ,of

~elativelY less, resistant metamorphosed s,ediments of the

Basement system.,' The" area 1s dralned by the B~rsalo1 and,.,

Seya river, systems and by trlbutarles" of the Ewaso N91r~

(wh lc~ 1 les to the south 0 f the transect).

The Low Foreland P1atea'u:

In the extre'me east of the transect, the .land "slopes

gently away from the 900m elevation. Relief Is very gentle

w1 th extensiv~' late Tez:tiary eros"ion sUirfaces. Younger lava /'

fiel~s occur locally .

,2.2 SOILS "

, As 15 natura!," the geo~ogy of the area has had a mar'ked

influence 'on the devefopment of the major soi1 types

(Sornbroek,et al., 19"82)., The twelve so'11 type5 df the area

can be qroup.ed into'. three categor ie5, related to ('1) Pre-"

. CarnbriCm Basement' System rocks, (li) Tert!ary volcanlc

ro~ks, and (IiI) recent floo,dplain sediments (Figure 2.4).

(I) So11s' developed from Basèment tocks tend to' form' , , " .

sandy' clay ,loa'tÙs~ , whlIè' tho~e der i ved from 'Tertlary

volca~lcs tend toward clays, and clay loàms. In terms of "

'. • .. ~ - f

plant dIstribution and 9rowth~ this factor of ~oil texture

is of cons lderable \ Impor~ancè. So"115 of a mor'é· sandy. texture , , ,

" axe ", characterized ~Y -plgh pe~~a.atri:1:"i~y and 11ml~d surface

Iun-off. Water p()Icolates lnt'o the ,sol,ls, to a depth, beyond

17 , ' , J

, 1

\ , ,

•

"

\.

.-

,-

o ,

",

" '

" ............... .. .. ............. Il- ........ ., • l ' ................. . ........... •••••• .!. t.

..... Il ................ .

.... .. • .. .. .. .. .. • .. .. .. • .. • .. • • • • ........ ~ ....... '-1 , ........... .. .. , .. .. .. .. • .. .. • • • • .. • .. .. .. .. • • .. 1 ........ ., .. t ............... .. . .. .... .. . .. . . . .. .. . . .. .. . .. .. .. .. . .. " ...... ~ .............. " .... .

.. " .. • • • • • • • .. .. .. • • • • • • .. " ... " .. " .. " * .......... , " ..... " •• Il .... If .......... l' Il .. " •••• , ................... . . . . . .. . . . . , . . . .. . .. .. . . . . . ........... ,'" ....... " ........ " ...... "

............ ,'_, •••••••• 1 ..... 1',.' ........... t') ................... .

1 : : : : : : : : : : : : : : : : : : :~: : : : : :'.: " .. : : : : : : : : : : : : : : : : : : : : : : : : : ............................ " .................... ~ ......................... . . . . . . . . . . . .. .. . . . . .. . . .. ",' ................. , .... , ... ,. .... ',' .............. . .. • .. .. .. .. • • • 1 ........................ , .... , • , ~ ....... 'Ir • 1 ............ .

• • • .. • .. .. • • • • • • • • • • • • • • • • • • • • • • 4 •••• 1 .............. 1 ........... l , •

• .. • • • • .. • • • • • • ... • • • • • • • .. • • • • • • • ,. ............................ 1 • 1 ...... 1 •

• •• • ..... .. • ," ,,, 1 ...... 1 ..... 1 ....... " • ., ................. , ,., ......... .

.. • .. .. • .. • • ~ ..... t ....... , ........................ ',' ............. , .......... ..

. :: : : : : ; : : : : ! :: : : : : : : : : : : : : : : : : : : : : : : : : : :.~ : : : i: : : : : : : ! : : : : : : ....................................................................... ...... ............. •••• el ...................................... .

• • • • •• • • • .. .. .. • • .. • • • • • • • 1 ......... 1 •• 1 ••••• , ............... .

, .......................................................... '" ........ , ............................................. 1 ...... .

1 • ..... .,. ............... 1 ............. 1 ........... , .............. "

............ 1 ...... 1 _ .............. ~ ....... ,. •• 1 ........... ~ •••

•• ........... , ••••••••• , ..... JO ......................... .

1 ................ ff .......... , ......................... Il ••

• • ,, ....... 1 ............................................ 1 l , •••

20 ,30 • 40

kllometres

SOIL PARENT MATERIAL·

t' • ............ ... " ..... ... . . . .. . . ,.

FIGUAE ?4

" .',

1 '.

TERTIARY VOlCANIC ROCKS

BASEHENT SYSTEM ROCKS

FlOODPlAIN SEDIMENTS-

SKElETAL SOllS ON REi:E~T l'AVA FORMATIONS "

. SOIL CATEGORIES OF THE MARALAL TRANSECT

( a fter Sombroek et al • 1982) , ,

;-

~

. ,

., 18

c:

"

.'

c

the influence of direct evaporation and i8 1

avallable for

plaint grawth, '-, especlally deep-:r;ooted forffi8, such as trees,

bushes and perennlal gra88es. Where the 5011 has a hlgh.-clay

content, water - , and root, p~netratlon are less ef fectl ve,

resultlng ln the favouring of shallow rooted and ephemeral

pl~nt specles (pratt and Gwynne, 1977).

Soi,ls developed on 'Basement System parlent mater laIs ln, ,

the Mathe~s Range and the Kar isia and Saanta Hi 11s tend to ,

be 'somewhat excessively dralned, shallow to moderately dèep,

"stony and reddish brown ln co 1 OU'1,t • The 5011s of the eastern

and southern footslopes of these mountalnous areas are well-"

dralned" Jve~y deep, friable, and yellowlsh red to dark

reddlsh brown in colour'. The 80115 of the Mld-Ua80 Nglro

Ba'8in and of the Low Forelar\d Plateau tend to be well- -. "

drained, moderate ly deep, and dark red to yellow~sh brown'! ln

colour. r

, , "

(II ) An examinati on of the so11s developed on Tertlary ,(;

" voieanlcs revea1s that those of the 8tep.-faulted ~carp8 of l ,

the 1 Rift valley are generally r well-dralned,'. shallow,

strongly ea,lcareou8, stony, and '" dark reddish brown ln ,

col our . In man~, 'Places t,he y- tend to be saline. \,. ~_ t, !""

The 50115

of t'he adjacent Lorogl Plateau whlch developed on basIc

19neou:s rocks .are also well-dralned but extremely deep, and "

CI

red' to-dark reddlsh brown ln col our . o.h the Lopet plateau

northward the 50115 are al30 well-dralned, but are sha'llow ( <

-and brown ln colour. In the Rift Valley, those 50115 whlch

developed on ashes and other pyroc1astlc materlals of young

vOlcanoes, such as S11al1 and the vents north' of the ., ,

œ

19

<,-

Tobe

'1

'r

o '.

CI i,

o

River,,_ tend to be excesslvely dralned, shallow to moderately /

deep, strongly çalcareous, and brown to dark brown ln

colour. The most' recent lava formations in the Ri ft Valley

are excesslvely qràlned and have developed lnto extremely

rocky land.

(III) The 501ls of t-he thlrd category, developed on

floodplain deposlts, tend ,to be very deep, well-stratlfie'd

" and strongly calcareous. In the Sugut'a valley they tend to

,1

"

,">

. "

" ,

be poorly' d~ained since the sediments here were_ formec;) from

vax lous volcan lc rocks and pyroclast 1 cs. HoY/ever, ln the ...t .: 1

Barsalot-Seya floodplalt}s, where sediments are derlved·from

dlffer.1ng rock tj>'pes, ,the so11s are well-dralned. They are,

greyJsh brown "to llght 011 ve brown ln -éolour ln the Suguta

"Valley, b~t darlc ",brown to yellowl~h brown ln Barsalol-Seya.

t.3 CLIHATE

The 'majot aspect of cllmate that affects plant gr~Y/th , -

, 15 the balan'ce between ra infiil1, evaporat Ion and

temperature. In part,icular, i t i s the length and I-ntens 1 ty

of ralny and dry seasons, -and the var lattons from year to

year that are of considerable lÎTlportance.

The Marala 1 transect 1s loca ted 1 n the âr id and seml-" .

ar id iands of Kenya (Omlnde, 1971). Due to the var latlon ln

top?graphy, mean annual p:teclpl tatlon ranges from 250 to

1000 mm, 'While annual potentlal evaporatlon rates of bet'Ween

1800 and 2200 mm are exper ienced (Ojany and Ogendo, 19-73). .:;

Hean annual temperatures range from 14· C in the Highlands to

30°C ln the Ri ft valley.

20 , ,

, ,

, 1

According to Sombroek et al. (1982), the transeet can

be dl v lded 1 nto f,l ve agro-ellmatle or ecol<?g lcal_ zones.

These are basieally zones of molsture aval1abll1ty whleh'are

"deflned u31ng ratIos of average annual ~alnfall to average " ,

annual eraporatlon, followlng the- ,:Jystem devi,sed by Pratt,

Greenway 'and Gwynne (1'966). The fi ve zones range from sernl­

~~rn~d (zo~e "III) t~ ver.y arld (Zone V~I) (Figure 2.5).

The key factors 'affecting rainfall distribut-ion in the

transect are topography (Jackson 197/, Brown and Cocheme

1969) and synoptic alrflow patterns (Walter' :1952, Kenworthy

and 'Glover 1958). The maIn characterlsticB of the transect '5

rainfal~ pattern can be summar ised as follows: •

(1) rclatively low total amounts; ,(11) great varlab1l1ty ln ,

the amount and t'1ming' of the ralns from yea~ to yeari and

( ill) spatIal var iatlons in seasona l d istr Ibut Ion wi th

marked dry seasons. 'Ralnfall data from the six weather

s tatlon!i Wlthin or close to the transect illustrate -these, "

character lsties, Tabre 2.1 shows that the rnean annual

preclpi tatlon for aIl, but one of the stations 15 les5 tha~

750rnm, the minimum' ralnfall requlrement for rno5t forms of

,crop cultlvation ln East Afrlca (NleuwoIt, 1978), \ However, " 1

/

"

cansiderably larger ralnfall totals (950 t'a 13'00 inin) are

recelyed ln the mo~ntaln areas,

a marked orographIe effect,

reflèctlng the existence of { ,

An exàmlnatlon' of the \ annual precipitation totals

recorded from' the mld-1960s 'to the present (FIgure 2.6) i' •

11lustrate5 'the' great year to yèar variablilty in the

transect. precipitation ln the central aJ;ea and ln the

21

, \

m

o

. ,

o

l' •

" \ .

VI

KapedO ~ Mfssion\..!...)

.K1nyang Hea 1 th Cent re

- "

VI

40 , 1

kllometres

--------------------------------~~--------------~------------~------------------~_._--~~-: r : Eo , AVERAGE Al(HlJAl AVERAGE AtItlIJAL

, r/Éo " 1

Q ZONE: CLASSlrlCATlOH : RAIHfAlL POTENf l~l 1 : VEGETATION 1

, (Hl : EVAPORATION (elll :' , ..

______ .. ____ .... J.. .. _____ ..... _., ...... _______ • _______ "" __ "''''''' ______ ...... ______________ ... _ ... _____ ........ ____ .... _ ...

" ,

'III .Se.I-Hulld BOO - 1400 1450 - 2200 ~o - ~5 Dry forest .nd, KOI st lloodllnd ~

IV Se.a-Ilulîd ta bOO - 1100 15S0 - 2200 40 - 50 Dry ~oodl.nd Se.I-Aqd .nd Bushl.and

V , Sfl\·~rld 450 • '900 1~50 - 2300 25 • 40 Bushl.nd

YI At uf 3ÔO - -550 1900 - 2400 15 . 25 Bushhlld .nd Shrubllnd

_ ,VIl Very A\-Id 150 .' 350 2100 - 2500 ~ 15 'Desert Scrub

. -.'

\\ FlOURE 2.5 'È:CO--'CLIMATIC TYPES OF' THE MARALAL TRANSECT

(after Sombroek' et ~. t 198~)

22

, 1

1 •

"

uall.1

fU1'III .fAfIOI. finIt 01 CLon tO fil !UlLIL rwSICT

_._--------_ ... _-------";----------------_._-------------------._ .. -----.---------------_ .. _ ... ---------nanôl .UI 1 LOCl'lIOi Il 1 molD 1 1t.1f1'f10i 1 IIW Ult'M. 1 IAlIflLL lO'Ul.S

é J flUSICT ,PIIIOD 1 (1) J PIICIPIflfrll J mUST i JIU 1 LODS! 1 YlU J J 1 J (ul J (ul

---------------;-------------------------------------_ .. _ .. _-------------.--_ .. ---------_ .. ---------.... --------[~ptdo "1S51u '. West Il.pD, leam CntIe ,Vut

160 HS

HU 62U

m.l lm m.l un lUO.'! lm 405.5 Hn

-- ....... _.--- ..... - .. --. - .. -- ----- .... -; - --- ...... - ... ---.-.----- _ .... ---_ .. _ .... --__ ....... __ ..... '"'._ ...... __ ..... _ ....... __ ... ___ t. .......... ______ ..........

poror Police Post !irilil District

off lee

, Central H6H'

Centt-il r:11""6 .. 1'.

24U 628.4

1950 632.1

1018.2 1977

1052.3 1911

369.5

458.9

H72

1916 .............. ~ ................ __ ..... _---..... """ .............. _-_ .... -.-. -..... _ .. _ ............ -... "._---.. . Juba &ut - U'9-H ~ lUS 712.3 1301.6 lm HU 19" ltchr's Post lut 1966·U 865 ~U 682.5 m. 150.1 HU - -, -----_. __ .-----------~------~~---------~---------------------~----~--_.------~-------~--------------~---------

r

Hathews Range (Physiographic Type Ir,' Figu!e 2.2) 15

generally more reliable ln these hlghland,s whlch rise , to

over 2000m. , \

The plots of monthly --preclpl tatlon data for the 1966-79 ~

per lod (F-igurc 2.7) 111ustrate the dispar i ty 1 n the seasona 1

distribution of raln across the transect. A- very dlfferent'

ralnfall pattern exists betwe~n the eastern and western

'sections of the transect. In ) the eastern section, a

di.:stlnctly bimodal rainfall pattern emerges \oIi th the 'rains

peakln9 in the March to April period'and again ln November.

These rains are often referred to as the "long" and "short"

ralns respectlvely. DrY'Reriods may total six mont~1 though

the longer dry perlod does not usually last more than four

and a half months, from early Ju~e to, late Oètober.

This ,rainfall pattern 15 the result of the behavlour of

the Intertropical Convergence .Z'one (ITCZ) (Sansom, 1965).

23

-

/

o ,

N ~

c.

~300 1 1200

1100

1000 .

900

E E 800!

~ 700 t <1:600 l-(l.'

UO

500 w a:: (l.

400

200 1--

100 ~

L-

"

. ',f

't!\6

WEST

Kapedo ( 760m 1 - 196& 79

KlOyang ( 915m ) - 196&7B,

".

1

1 "

~ ~ .. ~

o

K,nyang

1300 -

ïë • 624-S -,' 600_ !

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

Kapedo­

"i. «Ô.6 .--

CENTRAL

Poror ( 2410m 1 - 1966-79

Maralaf ( 1950m 1 - 1966-79

r-=--t=I:a--" --. --111---

!/'

t

1300 _

o .

EAST

Wamba ( 1465m ) - 1969-79

Archer's Post { 865m 1 - 1966-79

--

-

-

--t Il

Wamba

'i • 712.3 i

Maralal "i-6321

'\ 600_ Poror, X" 6284

300_

-

--

Archers Post i' .. 3559

-

-

-66 676169 70 71 72737475 7e n 1819 66 67 68 69 7t) 11 72 73 74 75 71J 77 78 79 6ô 67 68 69 70 71 12 73 7. 75 7a 77 111 7.a

YFAR YFAR YEAR

FIGURE 2.6 ANNUAL PRECIPITATION FOR WEATHER STATIONS WITHIN,OR CLOSE TO THE MARALAL lTRANSECT (after parry and Williams. 198&) ,

--:

l,

,r, , ~,

, ,

, .'

1.

• .. 1 ~ ,

The o,scl,lllatlo~s of thls low pressure trough back and forth

,~cross the equa tor .dur Ing the year resui t ln the generai "

cIrculation of the reglon' belng dominated by seasonally

changlng wlnd directl'ons:- the dry cont i nenta 1

northeaster Iles in' the Decemt?er '\ ")

moisture-Iaden easterlles in April;

to Mareh per lod;, the

the dry.southèastèrlies , ' ,

.between 'May and septemher; and a convergence of the

northeasterlies and southeasteriles in October, giving ri~e

'> to rain.

Y'ear to year differences in the extent of dlsplacement

and the w idth and 1 ntens i ty of the -I TCZ resui t ln

conslderarble 'var iapil i 1 ty in the timing 'and duration of "

the rains (Walter, 1952). . For example, exceptionai

preclpi taUon \-/as experienced by the area in 1977-78 due to

the displaeement of the ITCZ northwards; whereas in the

early 1970s -'widespread' drou'ght conditions resulted when

there , was Il ttle penetratIon of the ITCZ into northern and

eastern Kenya (Edwards et al., 1979). Between 1973 and 19'76, ,

Archer's Post experfénéed a failure of the 1ate season rains

resultlng ln major drougnt.

In the west and central sect~ons of. the transect, the

bimodal lialnfall distribution i5 'combined wi th surges of the ,

humld Congo ~. ,

Westerlles, -'-·-par.tlç31~arly in the -~

July to

September per lod when they react). we Il into the centra~

hl<jhla'nds (Hllls, 1978). A minor westerly sorge frequently

occurs ln, Apr 11 and May wl th assoclated orograph le ralnfall

when th!s uns table a lrma33 ls forced u-pslope ln the Kar Isla

25,

-, .

... _-. , ,

\ j

;

" ~

~

1'\)

.0),

; )

, (

ft

E

z o

1-

ct 1-

... u YI

a:

g

- 300

200

100

300

Q.2Otl

100

, ,

1 : l , lBS{) hl .i.e! (,1) , l '/1 7'; / , /4 l', Il 7t 7<J

, LANOSAT COVERAGE, ~ .. 1-

KAPEDO 1966 - 79

PORO~ 1966 - 79

WAMBA 1969 - 79

1~ 67 68 69 10 71

~ p

12 73 "" y e A "

~1'

76 76 78 10

'.

o· \J

r-:l . .,

~ 1 r . 1 1 . J

J l!1bO ()I ua tf.) 10 '1 1'l 13 _ 74 1f> 7G 77 lB 79

KINYANG 1966 - 78

MARAlAL 1966 - 79

ARCHE~'S POST J966 - 79

1966 67 68 8;)

~

70 11 ,

_JI

"

72 73 7" y E A R

75 76

r

71 78 ."

FIGURE 2'.7 MONTHLY PRECIPITA~~ON FOR WEATHER STATIONS WITHIN OR CLO~E TO THE'MARALAL TRANSECT (after Parry and Williams, 1986)

t/

e

~

c

- -

and Saanta Hilis. The end result of the~e surges ls"a

unlmodal ralnfall, pattern for the west and central sections

of the transect, with 'precipitation beginnlng ln March or

April and contlnuing until september; resulting in a dry

season of four to five months.

2.4 VEGETA:rrON

As stated at the ,begi'nning of this châpter, the

combined effects of the cllmatlc, , (\

physiogr~phic and edaphic

7lements have determined the e~lsting vegetation types qnd

their distribution pattern wlthin the Maralal transect. The

vegetation over much of the'area 15 prlmarily bushlana of

v~r ious types wi th forest at h 19i:ler aIt l.tudes. Where

,grasslands exist they are secondary in nature and are

generally fire-maintained. The sourees of the ,following

desctlption are: Bader (1979), Edwards (1940a), Edwards and

Bogdan (1951), Heady (1966), Kenya Rangeland Surveys (1970),

Ojany and 0gendo (1973), and White (1983).

2.4.1 LAND CaVER:

Dry, evergreen forests cap the n~jor hills and ranges

of the transe,ct (Eco-c limat lc ZQne III, Figure 2.5). The ,

d~le~ forest, spe<;:ies, such as Junlperus procera (cedar),

o PodocarpUS-m!lanjianus, and Olea af:çlcana (olive) are the

forèst' dominants.', The d~stributlon of forest Is dlrectly

related to aspect and elevation, relative to the molsture-

laden easterlles whlah blow across the transect ln'April and ~ .

October. Orographlcally produ~ed p~eclp~ta~ion of 900 to

t'

27 J, ,

, " , \

, '

- " -, J , "

Q

, \

·0

1400 mm 'results in forest growth malnly on the eastern , ,

slo~ès. The coole~ temperatures at these altitudes lncrease

the ra!nfall"s e ffect! veness by reduc lng potential

evaporatlon rates. In addi t-lon, the frequent occurrence of , "

mounta~n mists and extensive cloud cover results ln the

maintenance 'of a molst environment encouraging forest

gr<>wth. _,;rhe lower elevat 10(ns of the Mathews Rancre are legs

hUm!, .resulting in a more open montane forest i~terspersed

vith ~rasiland species such' as cPennisetum' clandestinum

(Kikuyu grass) Ànd Cynodon (star grass), whlch occur as

glades.

On-yet lower slopes, thé open montane forest gives way

to an evergreen or seml-evergreen bushland domlnated b~

thorn trees of the Euclea specles and Tarchonanthus

camphoratus, forming an ecotone between'the dry montane

forest and the deciduou~ bushIand and thlcket of the Iower

elevatlops (Eco-cllmatlc Zone IV, 'Figure 2.5). In parts of

the transect thls evergreen bushIand has been extensively

replaced 1 by Impenetrable thlckets, prlmariIy' Acacia

brevlsBlca, wlth very sparse ground coYer (Kenya Rangelùnd

Surveys, 1970).

At Intermedlate élevatlons (1200-2000m), where

precIpitation is in the 500-750mm range, partlcularly ln the

cent~al reg-Ion -of the transect, an Acacla-Themeda

association 15 widespread (Eco-cllmatlc Zone V, Fig~~ 2.,5).

This vegetation type occurs on the Lorogl Plateau and. aiso

as a beIt more or less encircltng the céntral hlghland area.

The woody dominant 15 flat-topped Acacia (3-12m hlgh~. The5e

28

, ,

t'rees, are scattered in _ a tall, even grass caver of Themeda '

trlandra one mette high. \

Il:,. gerrardii, & hocki i,

, J

Common Acacia species are

& nilotica ,

subsp , sublata, Q

Il:,. senegal·, and & seya!. .These trees may attain'heights of

up ~o fifteen metres, but much of the grassiand 1s occup1ed ,

by small, thin acacias up to ,l.Sm ta'U, such as the ant-"

galled ~ drepanolobi um (Whistll ng Thorn) and lh. 'Seya 1

(Whi te Whistling Thorn), particularly on the black, non-

-sali ne 1 crack Ing clays or "black co t ton" 50 ils . Exte ns iwe

open areas oceur where Acacia is little in evldence

appearing only in small groups or as isolated trees (Edwards , <

and', Bogdan, 1951). Balanites aegyptiaca (D~sert Date)

occuples the drier frlnges of the Acacia-Themedl"l community

(Ojany and Ogendo, 1973).

The gra39 dominant, Themeda triandra (Red Oat gras~), ,

15 a tufted perennial which grows to l.Sm taii and oceurs on

both red and black soils. Th~s grass oceurs upder conditions

of lmpeded drainage and irregular 'rainfall with periods of

drout}ht, part ieular Iy on the undulating plateaùx, and

mountaln flanks where f~res are a regular occurrence. The

greater part of the root system of thls species ls ~eveloped ,

. in Jhe sur face layers of the soU, thu's ailowing 1 t to

survive even- under low ralnfa,ll conditions . , (Heady,' 1966,)'. " .

Sub-dominant grass species Include Hyparrhenla, SetarJa,

Eragrostis on roeky ground, 1

and Diqitaria (Flnger grass) on , - 1

3011s of v.olcanlc orlgln,' which tend to be hi,ghly saline and

" alkal1ne. Intensive grazing has gradually resulted ln the

replacement of, Themeda . tr iandra wl th the coarset'~

29

• r !

/ '

o

unpàlatable grasSé~: Pennisetum schlmperi (Wire grass): ,and

Eleuslne . ja~gar 1 (Manyatta grass ).-~

Along the northern margln of the Loi'ogi Plateau, forèst.

occupies the we tter vailéy .bottomlands. ~he d'ominan t s~;ec les

are .Juniperus procera' and Podocarpus.gr?cillor. The' drler

int~rfluves "are grass-covered. At- e~elfatlons below iSOOm,

,'green-barked, umbrélla thorn Acacia sp'ecles, aiso occur

( Ba der" 1 1 9 7 9 ) • domi narit grass ~ 'rhemeda tr tandra, ... The " 1

1 exper ienc i ng severe, compe t 1 t ion a t the, present tlme from the

mQre agg~esslve seml-evergreen Croton dlchogamus and the.

acacias· (especially li::.. brevlspica), whlch' occur as

Impenetrable thlckets, ,particula-:!:: ly where there are 'well­

dra1ned 'slopes wlth deep fertile red s011s (Keriya Rangeland

,Surveys, 1970).

In 'the, lo"wlands of' the transect be lOI! lS00m,. and in n ,

. areas where annual precipltati6n ,~s less t~an .,'655,mm, the, 'l ,

vegetation degenerates to a dry thorn bushland (Eco-cllmatlc - 1

Zone VI,- Figure- 2.5). The woody spe-cles consist' of' a

di,spersed asnemblage of mostly dec1duous, th<frny .bushes and , . .

sh,rubs, 3-5m hlgh. Acacia -and 'Commlphora specles are nearly

always present. Thes.è are generally mul tl-stemmed,: bush~s or

small 'bushy trees, branching' fiear the base and spaced 4-9m

apart (Edwards and Bogdan, ,1951). ,Over extensIve areas r,

, wldely s,cattered:' spindly trees 6-9m hlgh, project thr?ugh"

the thorn growth. Thè dominant specles 18 Acacia tortilis ' ' "

subsp splrocarpa l pa):"t lcular ly on cillca reOus 50113 and ln

fIat., al1uv.1al valleys. • This specl~s can tolerate ~alinl ty

and a wlde range of 3011-water cond 1 t lons .

J 30 , " , . -,' l' • <\ , ,

, . . ,

_ 'J

" -

'C

, 1

",

l '

J

eJ

" ,

"

"

"

, '

The' common bushes an,d \ "\ ~ " - ,

small trees of this thorny , ,~

buzhland ar-e A. merl1fela, whlch can form 80-90\ of the bush, " - "

cover, Balanl te:s ~peci~, and the evergreen Bosela 'èol: laceai'.

and TeFminaÙa which are fou'nd along water courses or ln dry', ~ ) ;"

river beds. On r~d 5011s" , Commiphora species up to 4m h~gh , , '/

become 'the,dQmlna~. 1

thé lea~,hery-léafed Bosc la presentE>' a Cjreë,f\, appearance

amo,ngst thé trees (Eètwards, 1940~-). ~ ,- l ~., ~

Between the bushès. - 15 a sparse gro,~nd-cover of . ( ~ ... ..., '" ,.., . .

'scattered,. tuft~d per~nni~l grass?s à,nd lo~ shrtlb~ wrth much. ' , , \ '",... .... . \ .. ~ ... )

exposed > .bàre ,ground. The,re ~is' an ephemeral flush of full '. ,

-. , 1

grou~d cover gnly, ,after fhe r,c;{ins. The 10w shrubs are of t~., " , ''!

>'dwar:f' aat-egor y, "\ " q~ ,

i,:e,. ,l~.ss~ tn.an 70cm ta~l, and these are 1

, . domi,nated ' pa~tlcul.arly', b::( ,s,~ecles of" In'g1:gàfera spinosa.

,O'th~î: ,.dwar t' shrub spea:'ies whl,ch occur '"are Ser i&ocompos 1s-, ' \

'" , . " ' (commol\ on sha 110w ç.alcareotis '50 ils), and Duosperma on stony '~ ... ~, 't ,~ ~l r,

-~, locations .. succu~ents occur more 'or less everywhere but they

are rarely plentiful (White, ,1983 >..~' Due to intensive grazin9 , ' ..

." , ~

~ressure; these dwarf shrubs now, oceup-y much 'of th~'g ttlorny,·

bushland, esp'eclally gn the Ii ponyeki Plains; and much of .

'" ,

the bushland has become. thlc~et 'in nature, ,particula:çly -ln \

the Lorogi foothllis' (Kenya Rangeland Surveys, 1,970) . •

The perennial grasses are usually less .than -one metre , l

h!gh, and are dry, brittle and vlrtually. dead much of the , ,

year. , They are dominated by , Chrysopogon a'uche 1'; 1. var.

gu<tngueplumls,,' and '. j 1

i.nc1ude' Cenchrus '. , , " )

Fox~a il) , 'and Enneapoqon in' ar id or

perennlaI, . ~

. sporobofu3 spicatus and the

.. i

31'

œ

ciliarls (African ,

ro~ky sites. The

an~al, Aristlda

'"

'.' ..

"1

, , ~ , :.'

o

'.

.' " "

- '-

mutabi ~ lê, (NeesHe Grass) are generally foùnd assoc 1,ated wl th

Indigofera spInos,a (WhIte, 1983)'. 1 •

\,

In . area.s where the me~n annua~ rainfall ls' less than.-, ...

. 250mm; as ln parts of the Rif,t Valley,-, semi-desert scrub ls

characteristic (Eco-climat,lc Zone VII,' Figure 2.5). This

, aréa. ls much l1ke t~at previously' descr ibed except that

plant llfe is much more restrlcted. Whlle the dominant

s,J?eciens are simila~1 ' they are". hpwever; more stuntéd and

sc'antier. The cl1mate ls very arld and too severe to support

large; woodi plants or perennlal gras~es: Ground caver 13 . ' . very thln 'wl th much of the sur face ,be Ing bare. Apart from

" dwarfed trees (under 2m) and 10w, stunted shrubs (.often

.... , d~a:rfed) 1 the sparse ground coyer consists of annMal gras~es

' •. "" ,y~ (such as Tetrapogon spathaceus) and herba, . wh ich appear for

, ..

'oniy a brief, pert'od, fol'lowing the ~

ralns. The per lodlc

availabili ty . of abundant water favours these eph,emeral /

,\

gr~sses, >

saiL has a p-artlcularly wher'e' the high clay

content.

. The woody dominant. of thls 5eml-desert scrub, 19

, A. ·ie6~clens subsp misera,; whlch 15 wldely' ,spaceq..,. and

'exlgt's' ln a leaflesa, drought-dormant state much of the

year. The dwarfed, much-branched shrub Baleria 13 qulte

common in the Rift Valley, especially ln rocky places. Alsa

found in ~ocky locations are candelabra-llke Euphorbla along

wit~ aloes and other- succulents. The dominant succulent 15

of the Sansevieria specles. It often occur5 clustered at the •

base of bU5hes and occasIonql1y forma dense stands (Ed~ard8

and Bogdan, 1951).' VletJed from 'a dls~ance, ,the -c.~omlnating

32

f

c

, .

,

.colour of -the landscape 15 ye~lov-brovn: bare ground showlng

throuqh tHe th! n cover of plant5. such tree5 as -do occur,

are conf1ned to' the major tiver'chaflnelS and alluvla+ flats,

where dense stands of Âcacia, dominated by li:.. tortil l,s, are , (

" characteristlc (Bader, 1979). "

2.4.2 LAND USE EFFECTS:

Th,e , . natural , . v~etatl0!1 - of the transect. has been

affected ln parts by hov the land 15 utlllzèd by the area's

lnhabi tants. The· Indlgenous ~eople- who lnhabl t thls area are

t'he Samburu tr lbe (Spencer, 1 S7 3). Over, the centur les 1 .. , these

. people have developed a nomadic pastoral way of llfe as a \,

surv'l val mechanism agalnst the constralnts lmposed by the

seasonal variations ln the'area's rainfall and vegetation. ,

Their economy depends largely ,on Ilvestock ,(cattle, ~sheep ~

and goats) to provlde the basls of the tradltional pastoral

d iet - mllk, - meat and blood. Donkeys are used malnly for

trànsportat Ion. Agr lcul ture 18 pract.1sed only to a very

limi ted extent,' ma Inly for subs lstence, vI th the crops grovn

belng malnl,y 'sorghum, millet and - malze (Hjort, 1976).

Grazlng of the'subsistence I1vestock Is thus the maIn form

of land use ln the area. However, severe overstocklng have (

resulted ln the reductlon of 'grass fires due to overgrazlng.

The absence of f lres has led tb the rapid lnvas 1 on of bush

and shrub species into the transect's grasslands (Kenya \J Rangeland Surveys, 1970).

overall, the pattern of land use ln the transect has o

been greatly influenced by the seasonal changes ln ralnfall.

33

œ

o.

f ,

"

The blmodal ralnfall pattern previously descrlbed cause5 a ,

marked seasonallty ln the, qùant"lty and quallty of avallable

forage wlth the result that these people-mlqrate across the

area durlng the year ln search of better pasture and

perennial water sources for their animaIs. Durlng the rainy

seasol}s the~ general p<attern of movement Is one of dispersal

from the settlements to grazing camps ta take advantage of

the flush of veg~tatlon growth following the rains. The main

areas of wet season grazlng are ln the dry thorn bushland

country prey i ous ly descr i bed .' The dry periods see a

concentration of peopleca.nd animaIs in settlements near the

river~, lak~s, water holes and wells, and Jn ~he upland

areas ,'of the Acacia-"Themeda commun1ty, . partlcularly ln the'

qentral h1ghland area (Amin li al., 1982). In the forest

grazing' ls conflned 'to the lower slopes ~'f the mountai'ns and

sorne of the forest glades. t_

The pod~, fruit and leav~s of the' seml-arld trees and

shrub spec1es, espec1ally the acacias, serve as important

dry season feed and browse for the 11vestock. In the ,case of 1 .

li:... seyal, the bark 1 s extens 1 ve ly used, , ~h lIe the branches

of Balanlte-s aegyptlaca are utll1zed by the cattle ln the

'dry season only (Pratt and Gwynne, 19J7}.

34

1 _

( CHAPTER 3

THE VEGETATION MAP

A review of existing vegetation maps of th'e s'tudy area

~hdwed that these ranged in scale from 1:7 mill~6n to- 1:3 \

mill~on, and are part of reglonal~maps for East, Afrlca

(Bro'wn and Cocheme J:969, Llnd and Morr Ison '1974 ~ , Morgan .

1973, Pratt' and Gwynne 1977, Trapnell and Langdale-Brown

~962).

Other maps in the indicat,ed ~cale range are a byproduet .' , .

of specifIe vegetation studies. 3hese studies could be

grouped lnto thr,ee ma in categor les:-

1) detalled fforistie/botanical descr iptlons either of partlcular vegetation types or of partlcular region~_-(Agnew 1914, Barkham and .Ralny 197~, Battlscombe 1926, L' Bogdan 1958, Bogdan,and Pratt 1961, Dale 1936, Dale ~nd Gteenway 1961,· Edwards and Bogdan 1951, Fane~ 1957, Gillett and HcDonald 1970, Herlocker 1979);

2) general physiognomic descriptions of' proad vegetation types, whlch in some cases include flor1stlc detalls -(Bader 1979, E~~ards 1935 and 1940a)i

3) eco-agro studles undertaken for planning or land management projècts -

.. (Braun and Mungal 1981, Edwards ,1940b, . Kenya Rangeland surveys 1970, Sombroek et al. 1962).

Two vegetation maps' at the 1;1 million scale cover the ,

Haralal transect. These are the work of Kenya RangeJ,and

Surveys (1970), and the Afrlka Kartenwerk " , series (Bader

1979).

An examlnation of thes@ maps revealed that the

Rangeland ,sur vey vas of llmlted value to the thesis for two

reasons: 1) lt ls restrlcted to the' samburu District, thus

35

, '

œ

, '

, -

-.

",

/

o

,-

- cover inq only two-'thfr:ds of the Maralal study trangect~ and ,

Il) i-t was des ignéd to -assess 1,'~nd .. _u·se potentla 1 wl th the

result that O~lY; vege't~$on types of .. ec~lOglCal' slgnlflcance l'

were - identlfi~d and mr8ped. On the other hand, the' Afrika ~ w

,-This was due not Kartenwerk map,was partlculariy 5ultablè.

, ~J ~' ! .... 1 J _ \

, , '

, ,only to the map t s scale, " but' a150 to 1 ts cons truct i on wh i ch f

1s based on physlognomic criteria, ~n attrlbute of

. vegetation which Landsat records éffectively (as will

dlscuised ln thi follbwlng chapters).

The

(tlader,

Series

Afr ika Kartenwe,rk" vege ta t ion map of Ear t Afr Ica

1979) was prepared as part of the Afrika K\rtenwerk l

of the Deutchen Forschungsgeroeinschaï~! whlch 1

1

undertook the .mapplng of "varlous geographlcar featutes

(rahglng from topography to transportation ~eogra~ry) ove~ a \

large area of e'ast central Afr Ica (lat1 tudes ' 32° W-'~8~1!;, , ,

o 0' longitudes 2 N-2 S), at a scale of 1:1 million. Thus, not

only ls the entire transect covered, but the scale 1s

direct1y compatible \oIi th that of Landsat 1 mag'ery , ' /, '

The map \oIas publlshed ln 1979 and constructed uslng a

varlet y of data sources including pre-existing vegetation

maps, at,vario.us scales, 11terature assessment, air 'photo'

analysis, and extrapolation from three reconnaissance field

trips (betwee~ 19~3 and 19~8) ~hrough the central part of

thelr study area (sorne distance' t·o th~ "south of the Maralal ,

transect} . A detal1ed mono,graph accompanies the map,

explalnlng the classlflGatlon scheme and descrlblng the , \

vegetation types \oIhlch oc~ur ~ithln each clasd~

The sy~te~ adopted 1:n 'the Afr ika Kartenwerk study 18

36

"

(

"(

"

·de:scr ipt ive. As ment 10ned \f'

above, it is based' on purely o

physiognomlc criteria. This had a number of advantages:

(i r it avoids the problem of '31lccessional relatlonships and

climax types; ( Il ) vernacula~ terms and flor-is tIc

deflnitions are omittedi and (ili) 1t permlts a degree of

unlforml ty in vegetation description and thus allows val id

comparisons between different areas.

'The criteria selected to produce this map were those

that were observable ,ln the field, and which could be

accorded ecological signiflcance. Growth form types were

emphasized. For woody vegetation these included such

features as density of stands, type of ,bark, fa,rm and

duration of leaves, and ~he presence or absence of thorns

and succulents. For grass vegetation the important ,

attributes were height, density, leaf form, and life

, expectancy. '

At the gross level of the classification nine .

vegetation, types were ident~fied, based on thesc cr'iter la

together wlth alti.tu~e and position of the ground .water

table. These are deslgnated "Large FO-rmations" and given a

one-digit notation. Four of these are foupd in the Maralal

transect:, (1) Forest [il, (il) Areas of- small-plnnate-leaved -ligneous thorn plants [41, (111) Areas of 'ligneous thorn

plants and succul~nts (51, and (iv) Grassland with lov

ground water table (61'.

Large Formations are further subdivided Into "Formation

Groups" (two digit notation). In some cases, a,reas were 1 ;

de~19nated "Formation complexes" (a three digit notation)'

, , 37'

1)

0'

~

o.

because they were composed of a mosalc of two' Formatl~ns

whlch were tOÇ> smal1 to be mapped indlvldually at t.he

1:1 million scaie. This scaie does not le~d- Itself to

detalled mapping and the smallest map units that can be

delimi ted are in th,e 10 - 50 square k llomet're s ~range.

The occurrence of these units withln the 'Maralal

~ transect àre shown ln Figure 3.1, and the descriptions ~re

'summarised in Table 3.1.

There, ls a strong correlation between these Groups and 1 f'

Complexes and the transect's vegetation as descrlbed ln

Section 2.4. Formation Group 14 corresponcls to the dry

evergrcen montane foreet capplng the highlands. Groups 41,

51 and 52'axe very similar except that the percentage of

vegetation Gover is less ln· Group 51 and even less ln

Group 52. These Groups correspond to the Acacia-Commlphora

dry thorny bushiand. Groups 64 and 67 correlate wlth the

Acacia-Themeda association.

To summarlze, ~he Afrlka Kartenwerk vegetation map was

selected for further investigation ,for the ,following .

reasons: (1) good correlation with other accounts of

occur'ing,' vegetation; ~ ii) mapping sC.;lle; and (iii) use of

physiognomic criteria in classification.

" .

, . , , ..

'38

, l·

'C L.

"-

.'

"

, .

FIGURE 3.1

VEGEfATION FORMATION GROUPS AND COMPLEXES OF THE MARAL~L TRANSECT (after Afrika Ka~teowerk; Bader 1979) ~

() . '1.

'. , .... . '\.

) . ,

r " ~

"

39

t.

"

, ",

,1

..

o

. ,

TABLE 3.1 YEIiETÂTllII TYPES Of M MRALAl TRMSECT (based on Afrika Kartenverk, Bader 1~79)

-------~-------------~~----------------------------------------------------------------------------~-'rORItATloH • GENERAL DESCRIPTION rOR"ATION DÉSCIUPTlON or COIIPlEI 6RfMjp or THE rOR"ATION : COt\PLEX OCCURIM6 lM TIl IIU"BER GROUP : HUMBER i, I1ARAlAL TRAM§CT

-------~----~-----------------~--~-----------~---------~~._---------------------------------~-----------14 Single or .ultistoried evergreen

.ontane forests vith hlgh , proportions of laureHeaved;

sClle-:leaved' or broad-needled trees.

Areas of thorny shrubs or trees vith siail-pinnate leaves ln ope~ or dense stanas, norlally vithout ulbrella-jike crovns; stei succulents oft~n present.

'­.> , ,

. "

14.0

14.2

41.2

As descrlb~d for 14.

Montane forest, often open, lost~y ~ich in scale-leaved trees and vith thallus-epiphytesj ~nterspersed vith tufled grassland

)

vith open stands of siali-pinnate-, ' leived thorn trecs.

Dense stands of soall-Ieaved or , thorny shrubs interspersed VI th

s •• ll-plnnate'-1 eavelt,.ll gn~ous thorn plants; llttle,(ultlvatlOnj intersperse~ vith nore open are., rlch ln grassj .Iong the vatercourses gr oves of green~arked siall-pinnate-l,aved thorn t~ee~ vith ulbrella-Ilke crovns_

~ --------~--~----------~------~----------_:_------------~~-----~----------------------~---~~~----------~--- 51 " ... Areas of lignebus thorn plants and' 51.0 As descnbed for 51.

52

succul.ents' ln dense or open stands; grass (over nor.ally sparse or or allost non-eXIstent, dO.lnated by .annual Sj Interllttent 'vatercourses follovlng the eTosion hn!!s frequently fnnged by llgneous plants.

Sale as 51.0 l'XC l'pt that the sta~ds

. ar e '()pe~ and ver y open. 52.1 Vegetition virtually .bs,nt

(on lavi or sand) • , '

------------~---------~------------------------------------~--------------------------------------------64

67

Meas of tufted grass, noually 64.1 -dense and up to 1. 2 .. hlgh VI t·h or . vl~hout slall-plnn~te-leaYed ligneous thorn plants.

\

\ , ' Arels of tufted 9rass, nor.ally dense

,and up to 1.21 hlgh vith,indlvldual scale~lelYed .onl.ne forest triai.

67.S

As d!SCrlbed, vith opln or dtnst lov and g.lle~ siail-pinnate-le.ved thorn shrubs; groves of green barked sull-Plnnale- . lelved thorn trees ln the valley bottolS ne.r the ground vater.

"ontane forest .t the flinks of th, valleys; oth.rwisl tontine grls,land. ,

, -------------------------------------*~---------~----------------------------------------~-----------

, ,

'- ' 40 l :-

, "

a

\

(

1 ..

>

"

" , . , ,

CHAPTER 4

THE PHYSIOGNOHIC AND PHEN,OLOGICAL CHARACTERISTICS OF SEMI-AR~D VEGETATION

The Afr lka Kclrtenwerk d~scr ibes the' ~eget,at!:on' of ~ t~e

Haralal tran~ect ln terms of It~'physiognomy and as such, .

th~ map gives 111ttle indication of the annuCil pheno'logical

changes which occur within the varidus vegetation types. In

semi -ar id areas these éhanges are qu i te ' dis t inct and

extreme. They ar·e the result of the physiognomic adapfatlons "

of the plants to their harsh ~nviro~ment. In arder ta

understand what le seen on the Landsat images, one needs , ' , ,

sorne Idea' of how seml-arid' vegetation types z;eact at

p~rticular tlmes of the year as these reactions will affect

their reflectance and hence, their appearance on the MSS,

image. This chapter examines 'the, \::, physlognomic ,

charaeter ist les of the semi-arid veg~tation ~~pes dlseu~sed ,

-ln Seetio}\ 2.4 and presentéd in the ,vegétatfon map. ' It aise

Indlcates what h~ppens,to the vegetatlon'ln response to the

annual precipitatiop reglme.

,,4.1 PHYSIOGNOH'IC CHARACTERISTICS OF SEMI-ARID,VEGETATION

Seml-arld vegetation' can be described as, moisture-l '"

, ,llmlted. There âre general'ly 'few broad leaved speciès,' and

the dominants ~re 'xerophytlc ~hrubs, drought, reslstant

succulents, thorn" plants and ephemeraI grasses. Trees in

!Juch are~s 'cannot competè ~ffectl v~ly beca~se th~,"" upper soil

la'yers are lntermi t'tentiy mo1.st while the deeper layers are

, " - , . "

'41

(,

l'

T a

l ' ,

, .

, \

,~, 'Lf .. ....."

, J

,~ -. ).. -,.

.,. ,

,"

continuously dry (Coupland, 1979). plants ln such an

envlronment, adopt one of two main survival strategies: .'

(1) drought evas'ion in the case of th'e annual species, and

(II) dr?ught tolerance in the caSe of perennial ,speci~s

(Goodall et li., 1979). The mechanlsms involved in these

,aQa~tations also serve to p:rotect the plants from heat

s,tresS'., \ ,'.

(I) Drough t eva's 1 on ls charact_er lst 1 c, oi plants growi ng

"ln ~reas possess ing we!'l def Ined' wet and dr.y seùsons. Plants

in these areas, undergo intensive growth and complete' the ir

life cycle, or at least their reproductive cycle, purinq the

brlef perlod of ,water supply and pass the dry peri.ods o( the , '

year ln seed fOl!m or dormant, and as- a result seldom

experience severe moisture stre~s (Vpli.èrs, 197'5). This

strategy of suspension and reactlvatlon of 1 g~owth 'ln'

$ynchrony \ilth' the seasons ls observed in the species' "

Acacia reflciens su~~p, ml§era, whlch Ù~ found mal'nly ln the

~reas design~ted ,as 51.0 and '52.0, on t.he Afr~ka l<artenwerk ..

(II) Il) contrast; drought t61e,rante involv'es two maln

types of plant, adàp~at1on - those which P?s,tpone 'dehydratlon , -

those wo.lch l(ncteas,e the _c~>1ant' il tolerance, to

dehydration. 'These adaptatlon5 -lnvQlve motphological and

physiological modiflcâtions which all'ow the plants to end,~re , ,

teçiuced mo isture ava ~ labl n ty Jor COr'l5i.derable ,per i ods 0 f

tlme wl thout becomlng se,verely dehyd:ratèd (Tutner and

Krarner, ~980). These plants commonly 'have a,n' abundance of

- fibroU3 tissue to prevent drooplng ln drought. Under extreme ,

stre::ss however, , '

even perennials' that are adapted to drought

, '

li hl' il

\

"

, ,

/0,

are ultlmately forced to ta~e evaslve action, elther by

,dropplng thelr 1eaves a.nd ,I;>ecomlng q~'le5cen,t, or byadoptl,ng

an, annua l hab i t.,

other adaptations Inc1ude very smal1 leaves , (e.g. fu. i

ilèll1fera and fu.., reflclens), i ,

whlch serve ta reduce leaf , ,

surface transpiration àrea. 'Leaves may als,o be· few. in humber

,(e.g. A. seyal) and èlthe~,waxy'or 'pubescent. A thlck waxy

cutln, \ . '

comm,on 1 n ,the dute rmos t 1 ayers ,of s uccul e n ts 1

,enlarged ,flestw stems, , a'ct as à mechan'lsm for de.all~g wl th

the intense heat and l.ight .~y ;t:ed,ucing the plantis

transpiratlon and enhanclng its' reflectlvlty. The presence

'df Iea f hair s (pubescence) slows air movement thus ,reduc i rig

"èvaporatlon. Pubc'scence also 'lncreases the L

r e f1ect l \te

surface enabllng the plant to avoid ,pot'entially lethal h19h

,lea.f' . temperatu~es b-y r.edu~ing 'light absorl?,tion, and 'hence

photosynthesis 1980) • . , The decr,ease ln , ,

pho'tos'ynthésls .. reducet:! ~he da! ly water 10ss by decreas Ing

the transpira t Ion rate. "

~e3s dally watet. 10ss, al10ws the

plant,. to extend l ts 'growt~ into' the dl;,Y season. Sorne'

";x~mp1es of vegetat Ion specll~s common ln th'e transect wl th,

1 leaf' pUbescence are

. Tarchonânthus camphoratus,

, ,of, 'tlle dwar'f-snrub specles.' 1 JI _ l ,

Bosçla 'coriacea, i Comm!phora, '\

as we Il as h me Il qe'ra and mo.st l ' '

Mf.my of tHe Acac la spèc ies are , ' '

,.pub~scen't partïcu'lar ll' on thelr young branches; , , ,

Many ~hrub specles, such as the sucçulents, e:xhlbl t "

vertical leaf· or branch or lentation ln order to 'decrease the

8ol,ar r-adlation load and thus Ieduce' overhea,ting , and"

\ ' 'molsture loss. This phen'om,enon 1s a150 5ee'n ln grass specles

'\

œ

43 \ .

l'

\' .

. , where a éommon response to water defici t is leaf rollil')g ."

unti 1 the ~argins touch • This resul ts in a marked reduè,tion .. ~ ...... . ... ~ ..

in" èffective leàf area and also a more vertical leaf ,

<.orientation". There is a ].essening of the radiation load 'on'

, , , the plant, r~duced transpirat ion and i~çreased efficiency, 'of ..

, ... Sh~ddin9 of ~ If, • 1

leave~ and other aerial plant parts in - ,

orde'r' to reduc 4 transpiring surfac~s ,during periods of soil·

drY,ing ,i's ar,other" survi'val meci1anism, as seen in the 1.

. " ,

Commi:phbra spe~ies a'nd A. mellifera .. Leaf shedding generally , ,

begin$ WI. th thé older leaves, and progresses t'o ,thE: youf.1ge r ,

ones Îwith moisture "i:Înd nutrients' bel, ng' t ranalQ~a ted f rom old 1

'to new 1eaves bèfore the former are shed.

Ano'the:r; meçhanism of drought evasion' char'acter is tic ,0 f " ' ..

".', many annual plants is "t'he deveIopmén~ of. ci f ibrous root

'\ " ,

sy,stem, which is wide-spreading and shallÇ>w, and thus'

\ ", , ef'fect iye1y t,raps percolating sot1' moiseur:e. He r e, mos t root

-activi ty is conf~ned to the upper lOcm of 'tHe s9i'il. t G10ver

et al. '" 1962) 01 1.0 ni'any perennial plants' the d rough t "

res'is tant .

more is one, o,f a (jeep and extensive IIiechan i sm , l ,

"

system , of '.

suèculent roots, permitti~g water $torage for , ,

Q those per iods ,when no moisture ,is avai~~ble from the so~1. .. r,

~.... , . In sorne case roo'ts ·can extend down t,o depths 'of' 2m', 'al thou'gh

Il

" the bu1k of the roots will be ~etained near the surface "

,( Prat t:' and Gwynne, 1977 J . These plants can' therefor e grow '" "

over long per iods and ca.n ~,fl0':'l~r and ""seed 'in' the dry sea,9ons .. . (e.g. the Themeda-triandra gra~s species' fou'nd in the 64.1

, 1(

o and ,97.5 areas of the tran~e,ct). Such p:ants are frequently

44

-.

c:

, ,

..

,c-o '

., f

<,

succulent with thick~" scIer ifi,ed ~nd exfoliating root barks -..

(Kummerow, 1980). Euphorbia and Aloe are gped examples.' Wi ~h

grass ,species, the vast' mass of, roots below ground often -,

weigh more than the stéms and leaves'above" grol1nd (Brc>wn~

1972) .,

A' fea ture of, many of the 'East, Afr ican grasses, " 'such as , ..

r 7'hemeda-triandra, èhrysopogon aucheri, _,Eleusine jaegari,

Enneapogon, 'and Eragrostis, .

is:' the tuf ted na t u re of the i r

g.rowth. The above-"ground p~rt~ often ferm tuss'ocks wi th bare" "".

g'ro,und inbetween (Lundho'lm, 19,76). :~hese t"ussocks usuGllly

have very, dèn'se cèntres 'wi th the' leaves forming a mass

crowded 'at the base of the tuft. l 'rhe leaves Qf tusSOCk~ are

aften cenvolute and br istle-shaped or, if fIat, they are " • ~.- 1 1 \ '

narrow and' hard, (Edwa"rds and 'Bôgaan, 1951) • Lind and

Mort: isen (1.~74) postu~ate that this tufted character is

probably due te the al teration ot, dry and wet seasens which

'cause competitièn for moisture when there is rapid gr,owth

,fbliowing the tains .. ' The t~fted growth habit increases th~ir • l ,1

efçiciency' .in making maximum 'use 'of light rainfa,ll as,' the , , ' 1 ...

, aer iàl parts act as water \cé;ltchment.s and collect rain. from a

\

'large area -and channel' it down the stem so that it reaches . , . ,the ground around the, plant 'in al?pr,eciable" quantities

p

(Glover ,.èt al.l

, 1962). Thes,e grasses are spr;ead by mean~ of , .

, 1 , . (,.

underground rhizomes, (e. g. T,hemeda-triandra) , or -by above-" l '

gro.und 'stolons (e. g •. Sporobo'lus),

dactylon, Digitar ia).'

or both, {e:g. Cynodon

1 "'

The adapta,t ions of semi-ar i9 vegetation' to <,

its

,~nvironment resul ts in distinctive physiognomic profiles in

45

,( , .

th~ ',Vegetation ~ypes which deveIop. Profiles of sorne of the'

typical vegetation types_ found iri the Maralal trans6ct are

'~llustrated ln Fi~ure 4.1 a to g.

In East Africa the term, "bushland" 'is used ti denote a

ta~gled mlxture of sn\all tr~es, bushes and shrubs ~ratt and

Gwynne 1977, White 1983). The trees are always eonspieuous

wi th a single or layered canopy, and genera lly they do not

exeeed lOm ,in height. Bushes are between 3 to 7m- tall and

usually multistemmed'., Shrubs ma::t vary in helght from 10em to

2m or more'. 'Twenty per'cent 0;1:: more of the land Is eovered by , !

or b).lshy tre'es and' the ground.-k.QYer ls very po or . .. FJgure 4.1 a to d ,1 llustrate v~r 10us . bushland types simllar

tô the Acacia-Commlphora domlnateQ dry, thorny bushland

(Afr lka Kartenwerk Formation Groups 41,' 51 and 52

, F iguré/Table 3.1) , wh leh ls found 1 n areas of the tràn~ect

generally below 1500m.

"Figure 4.1a shows a typlea 1 bushland where the plants

are . ',r/ios tly of a bush)' or shrubby hab i t, \011 th a ,very sparse

ground cover' of tufted perennia~ grasses.· FIgure 4 .lb shows

a bushland whlch 1s becoming thlcket ln nature.. The figure

shows the profile -of the Tarehonanthus sp~c les (comman on

the lower mountain slopes of 'the transect). FIgure 4.1c

lllusttates a profile domlnated by succulents s.uc~ as

Euphorbia and san3evier~a. Figure 4.1d shows a profile wheré

the snrubs are dwarf' ln stature (under 70cm), as occurs' on •

. . tl1e Il ponyek 1 Plains and in the dr lests parts of 'the

transeet. The' plant pr/oflles lllustrated are the shrub

Duosperma and the tufted perenn lai Enneapogon. The qround

46

li

C·,

,"

IIl('tres

~­x

(a) (!)

(b)

(c)

(d)

(e)

, (f)

2

. • cD. h

'-~ .ft •• n .....

4 ~ SEMI -OE~ERT SCRUS. l ' • ,

'1 .. : , ..• ,~~E,;, ........ i ... ~;z.._,..;X., ..... r" ......... "!.. "

y~;:':\ ,~~- -,~t:·

L

~.;t 7 Je,?

*

'b 'rd!'

, '

-, ....... n-z.!JE..

FIOUR'l!" 4.1 PHYSIOGNOM:f OF SEMI-ARIO, VEGETATION TYP~S (eda~t(!d .irpm 'Pratt ~ !!l., 1966)

47

c.

, ~

-0

."

;

, sur face ls barren and 1arge interstices exlst bet;wee,n the . shrubs and the tuft~d gr-ass.

'Figure ~ .1e lllustrates the se'mi-qesert scrub which 1s

character istic' of areas where annual ra ln'fall Ls le5~ than

250rnm, as ln par'~ of the, Rift Valley (Afrlka K,artenwerk

complex 52.0, FLgure/Table 3,,1). The profile her~ shows a

typlcal w1dely-spaced woody dominant (fu.. reficiens 3ubsp

m1ser.ë) wlth a ground cover of short q.nnu~l grass, whlch

appears for only a brief timeilfollowing the ràlns.

Where the woody cover 15 betw!en 10 and 40%, and the

... land 15 domIna ted ,by an herbaceou5 ground laye~, the .

vegetation is categor ised as grass'land, which 15 then

further-' subdlvld~d - on: the basls 9f Its woody component.

Figure 4.1f ~ho~s the typical prof~le: of a Tr,ee or Wooded

Grassland, suc::h as the Acacia-Themeda assoc iati-on, wh! ch

ÔCCUJ:;S in the central highland area,of the transect and on

the Lorog 1 Pla ~eau (Afr lka Kartenwerk Format ion Complexes

6(.1'and 61.5, Figure/Table 3.1) .. The flgure 111ustrates the

, prof !les, of A.:... seyal and the dense-'canopied l2:=.. gerrardl1, ,

",,1 t.i} an unders tor~ of perennial grass (Themedà-tr landra ) .

Figure 4.1g shows a ,profile of the much smqller

è.:. drepanolobium (Whlstl1ng Thorn), common on the poor ly'

dralned "black cotton" 5011s, standing in . a very' open

arrange1'lent above. a layer of coarse perennial Pennlsetum

grasses.

48'

(

, .

, ,

4.2 THE' PHENOLOG·Y OF, SEMI-ARIO VEGETATION

Over much of the transect the pattern of veg~t,àtion

growth is essent'ially seasonal, being much influenced by the>

area's rainfall distribution pattern. The major ph-enological

events occuring in this tropical semi-arid habitat are shown

.in Table 4.1. The rainfall pattern'shown ls the 'unimodal

distribution' which, is exper.ienced in the west and central 1 •

sections of the transect. (In the eastern section qf the

transect, whe.re the 'annual rainfall distribution 15 bimoda~,

the phenological events descr ibed below follow the sarne

sequence, but are replicateq twice during the year.' One

sequence begins wi th the accu'rence 'of' the "long" rains in

i'Apr il which are f~llowec1 by, very dr~ candi tion~ from June to

. September. Another "sequence takes place wi th the start of

the "short:! rains in November followed by' a' Oecernbeli to

March .... dry period.)

, Dur ing the long dry, season, g'ener.ally from November or

Oecember to March, precipita,tian lS negligible. This is' a

per iod of dormancy for much of the area' s vegetation, The

grass' seeds ate s,et and most of the above-gr.ound par t;s

have died and qr ied back', The resul t is a high proportion of

standing brown matter .. ,The dominant colours" of the 1

vegetation are grey and orchre (Burton,' 1972), The bare

twigs ,are grey' while the branches may be f estooned wi th

grey-green leaf less cre,eper stems, Brown ( 1972, p. 22)

describes the general situation:

49

m -

U1 o

.0 .' .;

." ,

, . ~

---- MONTH OF THE YEAR NOV CEe -JAN , FEB MAR PriENUL,OGICAl EVENT *

PRECIPITATION NEGLIGIBLE "

1

ANNUALS SURVIVAL IN SEEO FORM

" ; , -PERENN~AlS DORMANT

\ ,

-VEGETATION

,

PHENOLOGY BUSHlANO DORMANT -

- , - 1

~

, . , , ~ SEED PODS

-VEGETATION:

brewn, g~ey, echre

lANOSCAPE COlOUR "

green (evergreens)-

ORY SOILS: reddish, yellowish -

. HUNAN ACTIVITY Herds moved te upland grazing araae,

wells, watering hales

FIRES - LlGHT . SEVERE .

* Landsat scene

TABLE 4.1 MAJOR PHENOLOGICAL EVENTS OF THE CENTRAL ANO

. \

tJ' , -"

,-•• >

"

"

" '.

~-

-

APR ' MAY JUNE JUlY AUG SEPT OCT ", )Jo

HEAVY . , LIG'HT

~~ -

G~RMINAT.ION, FLO~NG, GRQWTH SE~ , . 1

FLO~EfHNG, LUSH RAPIO G~O~TH LEAF ROLLING ORYING

\ , \

/ NEW GROWTH OF LEAVES AND BRANCHES LEAF FALL - GENERATI;ON OF

, FIBROUS TISSUE , " ' <

GERMINATION- té:W Fnl) t:RJ+tlJ -v

VEGETATION FLUSH SENESCENCE

GREEN BROWNING

. OARK~NING OF SaIL ~LOURS .

-

Navement to_law~ànde where there is Fresh ~eed fur li vest-ock / .

NEGLIGtSLE ,

-':)

W~STERN SEgTORS OF THE MARALAL 7RANSECT

c

c

; "At the height of the dry season, alt~ough seeds and pbds are abundant., lUtle 9reen mater ial ,

'survives. Most of the trees have dropped their shrivelled leaves r and the, grass 'stems, though tall, are hard and t~ugh." '

Tl)e red colour of the d~'y solls' developed on Basement System , "

" rocks (or on the Lorogi Plàteau 'and thè ~ step-faul,ted ~ift

Valley scarps) 'are clear.l,y- visible.

Du~ Ing the dry period the perennial, -p~ants, though , 1

dormant in 'most cases,.- are still very rnuch al i v~ throughou t '

thei r extensive u.nderground root systems. Fi re's are· edmmon

during this dry periode

_ With the coming of the rains during the period April to ,

August, the annuai vegetative "rebi'rth" oceurs. As humidity . ,

'increases wi th the ~pproaeh of the rainy season, many plants'

burst into spectacular bloorn. This ear ly fl.owering permi ts

wind and ins'eets t.o- po11inate these plants be!=ore the first .

~ ~ heavy shower~ destr6y the flowers (Burton, 1972). The first

,

f

rains lead to a .p~riod of intensive vegetative growt·h !ili th

the flower ing of the perennials and the germination and

subaequent . flowering annuals. The norma11y

unobstrusive grass ,cover and many 'small herbs rap'idly qrow

a 1uxurious, protein- and carbohydate- r ich sea of \ .

greenery (up to 2m tall) 1 sometimes burying the -smaller

bushes (Morgan, 1973). The rapidity of the vegetative growth

is due primarily to the dense mat of roots close to the soil

surface which quickly utilizes any available precipi tation.

There is a "green flush" of new leaves on trees and shrubs,

especially in the Acacia dominated bushland. Thorn _ bushes

51

fi

~

1

' ...

0'

1

, ,

qulck ly extend long green branches upwards. Seed pods > whlch . , ,

have been lylng on the bai:e earth, swell and germlnate. The

heavy , clay _ "black, cotton" so11s qu~ckly absorb molsture

through their deep cr~cks (secondary permeabillty), the soil

tnass expands and the sur face hèaves i nto low mounds. The

calcium carbonate hard-pan layer which oc~urs about lm below

the' sur face 15 lmperv Lous and' sa," pools 0 f wa te r, a few

centlmetr,es deep, may collect between the mounds and remaln

for an extended period of time providing moisture for plant

growth' (Morgan,' 1973). During the weeks of rain .JUany

,specles! particularly the annual,grasses,

reproductive cycle.

complete thefr

As the end' o:f' the ralny season appr oaches, showers

become' fewer; llghter, and are separàted by longer rainless ,. '

perlods,. 'Many plants seed., ,while bushes and'trees start to

lose their leaves in an effort to reduce water 103s ln the ,

c'omIng dry season. Sorne trees and bushes take on br illant

rea and yello\i1 colours prior to leaf-faU. The perennlal , .

gr asses becorne tough ~ and wl th senescente, the above,-gr ound , .

parts t,urn to "standing hay'~ and t'ake on a, brown coloratlon.

In ,othèr plants, ,lncreasin,g amounts of fibréus tissue ar~

generated to prevent droopfng in the éomlng dry 3eason J

(prat~ anld 'Gwynne, 1977) • Much of the vegetation ls el ther

dead or remains dormant throughout the long dry pè'rlod

untll, wl th the next rain perlod_, the cycle', beglns anew.

It 1s generally dur Ing the -dry season that f ires occur.

The fires are Ignl ted by l1ghtnlng or are set by the

1ndi~enous pastorallsts to stimulate the gr?~h of new

52

, '

(

< <

$h~ots for the ir Il vestock (UNESCO, 1979). Ear ly in the" dt Y \

season the effects of flre are not ~èvere, because sorne of

the vegetation 15 stl'll green and moist. As the dry season~' ,

progresses, f ires become more severe,' espec ially where th~re

113 a dry, st;lrlV'elled highly combustible grass cover to 'fuel

the f lames. Fires are l nfrequent where the, gro~nd cover <'is

very sparse, as in the bushland and th1.cket communltles.

F 1re can directly Inhlbi t the spread of woody plants by

destroying seedl ing3 and 3tunting "the growth of immature

plants. It may encourage the spread of more palatable

" grasses (e. g. Themeda-tr landra) where SQil moisture Is still

ava ilable, by removing overma tur~ 0 lder . grasses and 1 i tter

CEnr1ght, 1983). The passage of these fires frequently

destr'9Ys the ab9'v~-groundl p'~rt8"of grasses! and shrubs .. (

H~wever, grasses are 1ess ~~\Cfed than trees and shrubs due

'to the extensive system Of".,~li lzomes beneath the sur fac~

'llfhlch survi ve and produce f1k esh s,hoots when condItions

, f . Improve with the com1ng of the rains (Burton, 1972). Trees

" survive the fires by ret'ainlng sorne moistuI:'e ln the1r ,above- '

ground parts throughout the dry season. In addl t Ion, rnany . , ,are protectec} by the ir tough, thick, corky' bar'ks which are

'" falrly flre r!1~,stant., "Althoug~ the trees'

may be' 'scOrChe~('he upper ones survl ve. I{\ \' {~1

lower. branches

•

" "

S3 .,. ,

œ

\ ,

o

•

\( CHAPTER 5

LANDSAT AND SEMI-ARIO 'VEGETAT,ION

. Landsat false co~our composites have proven to be very

useful in vegetation studies du~-to the, sensitlvltl' of the

MSS te beth vis i bIe' and infrared re flectance. In thl,s thes i s

false·· colour compos.i te t'ransparencles of the Mara la 1

transect are t{le ma i n data base and 50, sorne unders tandi ng

of the structure Qf the false colour co~pos 1 te and the . '

rend i tlon of semi -ar id vegetation is neces5ary. In thls ,.. c 1'/'

chapter the ,Renera-l relationships between vegetation

refle'ctance Ind the Lands~t imag~ wll1 be examlned, ànd the

varlous phenological changes dlscussed ln the' prevtous

chapter will be related te seasoh,al changes in the Image

appearance.

,C, 5..1 LANDSAT AND VEGETAT.ION: THE GENERAL ,RELATIONSHIPS

Th'e. most useful', reglon of the -electromagnetic spectrum

.for 'studylng vegetation 15 the .0.4 to 0.9 um r?nge (Curran,

~981). The Land5at l:1SS w~ deslgned to operate ln these

wavelengths. Energl' reflected bl' features on the earth's

surface

th'rough

15 recelved through an optlcal system,

a fibre op~cs array _an~'" selectively

passed

fl1tered

according to the Landsat bands (4: O.5-0.6um, 5: 0.6-0.7um, 1

6: O.7-0.8um, 7: 0-.8-1.1um) (Table 5~1). The phY51~al

properties of the feature determlnes the ,amount of the

Incomlng solar rad'lation which 15 reflected ln each

wave Iength. ' The -reflècte~ rad latlon of the fea ture, whlch

, " , , '\' ~ ~

54

"

,\ ,. '1

c

\. ,,'

" .' ,

, . , ,

" ,TABLE 5. 1 LANDSAT HULTISP~CTRAL' SCANNEIC (MSS) BANDS

---------------------~---~---~----------~-----------~- ---" , . 1 SPECTRAL J'DOMINANT 1 COL OUR ON MSS BAND 1 SENSITIV,ITY l, REFLEÇTING J -r..AND~AT, IMAGE

1 (um) l' WAVELENGTH" 1 . ---------------------------~---_.~----------~----~-------i _,

4 0.5-0.6 GREEN' aLUm \

!) 0.6-0.7 J RED GREEN 6 0.7-0.8, N"EAR rNFR~ED RED 7 0.8-1.1 l ' ,NE~ IN~RARED ' RE'O '

-----------------------~-~-------------------------~----~ l '1 •

, f 1 ,

15 further modlfied by selecilve atmospherlc scattering ln , l ,

'the shor'ter wave:le ngths, 'eatabllshes i ts sp~ct~)a l ' s1gn~ ture.

When an object Is strongly, reflective ln' those wavelengths " <

to whlch ct partlcular ,decte,C!tor Is :>e.nsitivet Lt wlll appear

brlghter or more tadla~t ln t~at p~~tlculat.H~S band and

\il11 be exp:r:essed, in, llght tones on the Landsat image.

Landsat ls capable ~f detecting 64 different intensity

, levels of reflected energy" but i ts spatial resolution Is 1:

,"

J'

; ,

limited by the,instantaneo'us field,of view of the scanner

(79m by 79m),' wtdch 'ts 'r~'pre~ented on th~ Landsat image as a 1 _ ,

picture' element or' pixel.' :rhe 185~185 km ground area covered , .'

by 1 J •

L~ndsat scene cons18~s of a re~ular t~p dimens ional-a

array ~f 2340 scan 'lines, ~ " 1 l

each conslsti-ng of 3318 pixels, ,

arrang'ed ln 'theJ'r proper relatIve pos 1 tions with respect to , ,

the correspondt~9 s~rface location (Short; 1982). The result ,~' ~ " .

j • t., JI

la a ge.0graptllcally. accu~ate po_rtraya l'of "the area. " .

9f: ~ blbe-sensitive band precludes the 1 The' absence, { ~ . "," ,

preparation of, norma~ color compo~i te images from Landsat l • " jI"

data. The "standard" La~d~at colour composite image has the

.spectral' ,cha;acter ist;l~s ,of' :a..n, Infrared , ,

a~d 15 ref~rr~d to ag,a "false colour , , ,

l'

, .' " , , "

, "

. , , '

, ,

" 55

. " .. ',' , (

..

color photo~raph,

1

'composite". "False'" ,

{.

:

"'lI -" fi -..,.'t

, ,

, ,

o

, ,

" ' ,

"

l'

,colour is necessary to depict radiation beyond. lhe

wavelength ~es~onse range of the human eye, i.e; those'pa~ts

of the near infrared to which the MSS system fs sensitive. ,

Thl,!,s, in a ,false colour image, the apparent colours of the

film rlo not correspond to the coloufs of. the original scene .' " as, perceived by the human·eye (Figure"S.l)., Those portions

of ,the scene reflecting in the green wavelengt:hs (0.5-0. 6um)

are expre~sed in blut:-- on the image, réd reflect~nce (0.6":"

O.7um) in green, and the near infrared (0 ... 7-0.8, or', 0.8-

,L1 um) in red. 'l'h,e Landsat MSS faise colour ~ompos.it·es are :'\1 ,

generated u:::d:l1g three of the four MSS bands, that 1 s, Bands

4 , 5 and 6 or', Bands 4, 5 and 7.

cLandsat ls part'icula'rly useful in vegetation studies .

becauS'e of the :="ensi ti v ity o~ i ts var ~ous wavebànds ta plan t

ref 1ectance. shows a typical reflectance 1

curve Figure,S.2

for green vegetatïon as i t relates to the MSS band?

Ref lecta'nçe, tran~~ittance a~d absorption by leaves . , depend

on the concentrat~o:n ot; .leaf pi,gments a~~' wat'er, ,and the'",

lea!= f s' iritern~H cell structure. 1 In tne' r ange o~,' wavel~ng~h~ , \

'0.4-0.7um (MSS Bands 4 .~nd 5) leaf refle,ct'ance is ,quite low

10%) due to the - . influenèe of Ieaf pigments,

especially ~iliorophyll wi th i ts, high absorption capaci t\y for,

the short wavelertgth energy requi'red for photosynthesi$,

(Knipling, I9,7à). There' is a redl;lced levei of absorpt iO,n by 1

'the pigments in the' O.50-0.6~ um range and this accountn for

'the perceived green colour of leaves (Gates et:. al., 1965).

In the O.7-i.l um (MSS Bands 6 and 7) near-infrared' range,

the p~gments have no effeot on in~oming radiation, ,and: leaf

" , ,

56",

-

'C " ,

'.

l ,

,.. ,

\

c-I

'. , 1

, .

. '

, . . ' - '. ,

----------------~~--~----------~--------------~~-'

.' '

nLM' ~RANSPARENCY .' "0

\.( __ ,_'RE_O __ ...L-~' -_'·.;.,.GR~'E~EN_ ....... __ B~l~IJE_~l 'R~SUlTING.'IMAGE COlOUR

,t, 1 t _ -t ,

Y'EllOW YEL~OW CYAN , MAG EtH A CYAN MAGENTA } ::~::;:: :;:E~;;:R:ND l'

COLOUR 1 NfRAREO ' {

FILM ~YPE R~S~~NS~ CYAN MAGENTA YEllOlf REIoK)VEO OURING ,PROCESSING,

't , , t f' 1 ,

1 BAND 7 BAND 5 BAND 4 ,

~ A

~ED SURF AC E REFl ECT! V!TY 1...-"':';';~:':';':'::""'-'-"";"""";;:';:':"_--1~"';;';"';";;;":""~

..

, .

" /

\

'. , , ,

" " -~ ,

.

PRI HARY COLOURS

" AOpITIVE SUBTRACTIVE ,1

, , RED '. CYAN

, . GREEN MAGENTA

BLUE YELLOW ,

"

FIGURE 5.'1 , 1 J \ '. , "

1.ANDS A 1" A!m THE FORMATyN OF FALSC ,COLOUR COMPD~I.TES (at"tor. ~e'nde oth and Yoat, 1974) --, , ,

• • ".. "A

..,.~ J.' 1 •

" 57

m

'I .'

.' 1

',\1., \

./

, \ ..

'.

\ .

. , :

,'.

.'

, ,

-: "

.' )J " ),

\' .. , \\~ .. ~ . ~~.

• r

1

ref 1ectance , .

~ 1'1)

(,

increases substantial t y to 30-70% of the /

total

~ncoming radi~tion, with ies~ than 5%. absorption of the· - • " 1

incident energy: This i9,due to' the leaf. ' s internaI ce'lulat" . strûcturé, the discontinuîties in the mesophyll

iayer t~oolley i971, Gaus.man t974{\ and b). The high infrared .::;;

ref1ectance, from healthy plants ·overwhelms the green

" reaponse and this e.x:plains why green plants do not appear

, ~:. 1

blue on the Landsat image. -1

The reflectance properties ,QE '.a si~9J.e leaf discused

above ~re basic tb an'~ndetstandin9 o~ ,the refle~tance'of an

entire plant and hence of a vE(g'état.lon 6ari~py, with sorne

.,modific~tions. Knipling ,(1969, 1970) and 'Colwell (1974b) . .

'have shown that vegetation canopy reflectance i9 generally . -

less tha'n single leaf reflectance due to the fallowing

factoJ:'s:-,

. i) the variable arrangement and orientation of leaves;

i i) leaf t'r ansmi t tanc'e; ,

iii) the effects of nonfoliage canopy cq'mponents, such as stems and branches; , (

iv) the background characteristics of the s~il and litteri 1 t n

v) shadowsi

vi) ,the variations in the illumination angle depending on the t ime of day.

The result is that the level of visible reflectance frpm a

~egetation canopy, is about 40% of tha~ of a single leaf. ,

Infrared reflectance is about 70% of that of a ~ingle leat.

Thé infrarè,ed' ref1ectance is not 'reduced as much as that of ,

the visible dve. an'enhancement effect of/multiple scattering

between the leaf layers of the vegetation canopy • . . . "

58 . ' . '.

)- ' .

• ~! •

. "

"

, '.

'"

'\

r

w, u ! 30 t­U W .J

~ 20 a:

04 05

LANOSAT MSS BAND

SPECTRAL REGION

, .

06 07 lOB 09 10 11 12 WÀVLENGTH (um)·

4 1 5 ·6 1 7

VISIBLE REFLECTIVE INFRAREP z w e NEAR INFRAREO w cr:: ex ~

, '

DOMINANT FACTOR CONTROLLING

LEAF REFLECT ANCE

LEAF PIGMENTS

, . CElL STRUCTURE

/

l '1

'FIGURE ~.~ ,TYPICAL REFLECTANCE CURVE.FOR GREEN VEGETATION (af"ter Hof"rer and' e~uBr', 198")

-' \ 59

"

m -

;., ~I,

! '.

"

, ,.

o ,/ 1

5.2 LANDSAT AND THE SEASONAL CHANGES IN THE SPECTRAL CHARACTERISTICS OF SEHI-ARID VEGETATION

The spectr~l cnatacteristics ~f v~getati?n ln seml-arid n

areas are contro11ed by the physlognom1c adaptat10ns~ a10n9 "

with the qistinctive phenologlcal· changes which o~cur duting

the year (Chapter 4·). As was descrlbed ln SectIon 4.2, seml-:

vegetation undergoes periods of active gr owth,

. senescence and d ormancy in response to', the ralnfall l

distribution during the year. Because of the discontinubu5

nature of sem1-arid.vegetatIon, espec+ally in the bushland

communi ties, the reflected energy sensed by ·a spec.tral

?, SCanner aboard an aircraft ,or spacecraft 15 a c~mposite. of

reilectance from the vegetation (live and dead), the solI,

, \the 11 tter (fallen dead plants and plan~ debr ls whlch, tend

to accumulate ln the bare" Int~rstlces), and any bare rock, , "

dependlng on the tlme of year:. , The dlfferent contrlbutlon~

of the soil and veget~tion spectra to the overall la~dscap~

reflectance durini·the changing seasons wl~l ~nfluence the

dominant colours wh lc~ appear. on the, Lé1r:tdsa t . l~ge. These , '

will vary from thé brl,ght_ 'red hues of, the' g'rowlng seas'on to

the green and blue rues of'the dry sea~on, dependlng on 5011

exposure and the proportion of ljve to dead vegetation.

ACTIVE GROWTH PERIOD:' Durlng active growth the spectral 1

, ' . .

feflectànce 15 domlnated by the h1gh IR reflectarce fro~ the'

vlgourously .growing vegeta.,t ion. The, reflectance curve for

the transect would thus' look much 11ke that shown in

. Figure 5.2. As the vegetation matur~s the overall . "

refleatance wquid lncrease with th~ Increas1ng vegetation ,

6Q , ,

C,

. ' ,

, ,

-.

.1

cover, den~ity, and vigour. OVéral1 visible reflectance

would decrease d~~ ~o the ~tro~~er absorpt~on in the blue -

(0.43-0.49uÎn)' and the red C.0.63'-;o:70um) .. regJoJl~ of the

spectrum, caused by the development' of - leaf chlorophyll.

'Thua, reflectànce in Bands '4 and 5 will be low relative ta

that of Bands 6 and 7,' where 'thère will be ,increqses in the

IR ~eflect~ance' leve~s with the development of the number of

cell-wall!ai r space interfaces ~ discont'inui ties), in the

mesophyll layer (Gausman 19~4a and b).

puring this p~~~od, the vegetation caver wouid

~ignificantly reduce -__ ~ reflectance ,fro~ i..- { , ~ _ ,

s6~ponent. MSS" Band 7 wOu~d ret~d the highest

and-red would-be the dominant imag colour. l , ' • ~

" .

the 'soil

reflectance

'.SENESCENCE: 'As the gro\ol~ng season c,ornes ta, an end the

. perennial ve~etation begins to senesce, and morphological

and physiological c~ax;tges occur wi thin the leaves. The ""

decreas~ng availability of wat-er with the approaching dry

aeason 'resul ts in the plants .10sing thei r~ vigour due to

dessication. With the· lOBS of vigour the y are unable to .r l ,

manufacture chiorophy~~_at a sufficient rate to replace that , .

whfch ia coristantIy being decomposed 'in the leaves. Wi ~I:lout '\ ,'" j

the abaorbin~ ~apacity of chlorophyll, there is a shift in ~

the visible ~efl~ctance_peak' towards the red portion of the

sp~çtrum as other leaf pigments (which are mainly the-

yellow, orall:g_e and red caroten'oids) become unmasked and the

'f9lia9~ turns yellow, red and 'brown (Kumar 1972, Murtha

i9~2). The ~nd . result is an overall increase i,n visible

. "

61 \

m

tO

" "

, '1

(

reflectance. '

te~f dessication causes cell walls to lose thelr

turgidity and collapse, resulting in leaf r011ing, wilting

"and proppin~. Dessication initlally results in increased IR

r~flect~lOce in the O.7-LJum'range (Bqnd~,"6 and 7) dtie to

the increase ln the ,number of' discontinui ties as the 1

mesophyll layer collapsea (Knipllng 1970). However, as \

sehesc~ncê continues, th,re 15 decre~sed canopy,cover and

totally collapsed inte~nal leaf J,ruct\lres, which results in

decreased near-IR reflectance at very advanced senescence.

Reflectance from - the 301.1 component become5

increasfngly signi~icant in total l~ndscape reflectance with

advance3 in senescence, due to ,the decreaslng vegetation

cover'. On the Land3at image green and blue, will bec9mè the , , , ,

dominant colours as vegetat~on senesces and th~ red ,

_çolora~ion, due ta IR refl'ectance, The .' ,

1

Increasingl~ exposed ~nd drylng red soi1s will contibute

more green to the i~ge.

DORMANCY: The dry seasQn brings a period of dormancy to , -~

the perennial grasses and the deciduous bushland. It 15

durlng ~thls ~erlod that 5011 reflectance becomes ~ost

slgnlflcant in the overa11 landscape reflectànce, and may ln

fact 'be,come the dom~nant component, especla~ly where

vegetatIon cover 1~ now low or non-existent (e.g ~here

annuals flourlshed durlng the rainy season). Durlng thls

per lod, there Is very Il ttle contras.t bet~een the dead and "

dormant vegetation and, the solI, aB the spectral signature'

62

(

. \

, \

( \ '

for dry vegetatIon close1y resemble5 that of bare 5011

(Hofter and Bauer, 1980).

In general, reflectanca from ba~e 50il, surfaces

Increa~es wlth increasing wavelength throughout the vislble

and the IR wavel~ngths. The amplitude of the 5011 ,

reflectance is détermined 'by a numbe~ 9f interacting ~oil

propertles (Bauer et al., 1980). In terrns of tne relatively

per-manent phY5icai "chêrracter l~t:.1cs of the 50 il, ,tnere Is a

decrease in, SOil()cefl~ctance wi ~~ : ~ncre'as~s "''tri'" Ol;g~n~c -

matter content (beyond 2%) arid increases' in- 1ron, oxide

content. There 15 a ~apid èxponent laI irrcrease' ln 5011

reflectance between 0.4 and 1.0 um with soil , )

,pa~tlc1e size and Increasing amounts of silt whlch result ln

a smoother 5011 surface. In terms of tempo,rary influences;' , '

tnere is a decrease ln 5011 ref1ectançe wi~h 'increasing

molstu:r:e content~ , '

\

FIgure S.3a lilustr.ates the-, seêisona 1 shlfts ln'

.vegetation reflectance a~ di~férent stages of fhe ,gro~th

cycle,' from active growth' thr'oùgh :to advanced, senescence;

~hile the interaction ~f the v~getatlon and 5011 componen~s

~ln ~he,total scéne reflectance, at different stages ln the ,

annual cycle, can be a5sessed from Fi~ures 5.3 b,to e.,

,5.3 LANDSAT AND SEMI-ARID VEGETATION STUDIES

Hany of the techniques applied ta seml-arid vegetation ,. '

studles utl11z1ng Landsat,data, employ techniques whlch were

developed ln temperate range land 'environments. Here, the

most slgnirlcan~ development has been the use of varlous,

63 "

m

o

'.

, ~'

\ \ '

o

(a)

"

o ." 1 i 1 i , 0.5 '0.6" 0.7 0.8 0.9 1.0 1.1 , .

WAVELEN4TH (um)

VEGETATION SOILS

....... ACr.LVELY GROWIOO WET \ -t"l' .' ---- SENESCING .. -_. DR,Y • ... ~ ... DO~MANt

(b} (c) (d)

j •

LANDSAT MSS -BAND 4 5 6-7 4 5 4 5 4 5 6-7 SEASON

VEGETATION

DRY SEASON

DORMANT

..

FlRSJ RAINS HEIGHT OF. RAINY SEASOH

FLO!!'.:RI~. NEW GRQWTH' ACTIVE GROWTH

VEGETATION REF'LECTANCE SOll REFlECTANCE

FIGURE 5.3

THE GENERAL RELATIONSHIPS BETWEEN VEGETATION AND SOIl REFlECTANC~S 'OVER A SEA50NAl CYCLE

END OF RAINS

SENESCING

~ (.fter Knipl1ns 1569, Murtha -1982 t Tucker 1979)

64

vegetation greenness indices to determine a va,~iety of ,--

vegetation parameters. Most of these' indices have been based , ,

on a near-IR to red refiectance ratio (Lapdsat's MSS 1 •

, 1

Bands 7/5), or sorne variation oÎ this. The devel~pment of

this ratio has been based on the fact that these two bands ,

yield the" mosf information on vegetation resourées " due ,ta -,

the differences in absorption and reflectance in the red, and

near-IR waveiengths for heaithy green vegetation. Thus,

while· single band analysis is u~eful for determining

vegetation condition, the ratio is a use fuI measure of

relative vegeta~ion greenness and productivity (cover and

. density). More importan't, use of this ratio normalizes the

effects of soil background and litter in ~anopy reflectance

(Colwell.1974at Hoffer and Bauer 1980), ' ,

Slnce the ratio is'a measure of vegetati6n amount' and . , productivity, the relationship between, the ratio and

vegetation 'amount is not static'. Q

. The amou,n t of red

reflectance has an inverse relationship 'with vegetation , .

maturity. In addition, red reflectance varies more than, . ,

near-IR seasonally (McDaniel 1978). Ratio values will cha~ge

with changes in canopy cover and density, resulting in

i~creasingly higher-values when vegetation is de~eloping,

wi th decreasing values once 'vegetation starts to' senesce.

Thus, multidate Landsat analysis, especially of time­

sequential imageSI aIlo~s greater interpretability of an

area's vegetation. For example, Carneggie et al. (1974)'

/found

1 was

that the, MSS Band 7/5 ratio,

highly.correlated with changing

65

œ

when plotted over time,

vegetation production

•

D

---,---------------------------/"

and growth. The peak of the r'atio curve wa.5 'found to

dolncide with peak fallage p.r·adué.~·ion, its 10w polnt occure,d

at or jus~ befdre germination, aQd the ratio curve began to .

fall off wl'th the per10d .Of, d,rylng. Once' the r.atio cu~ve "

levelled"off, vegetation was either dead or dormant.

Although the simple IR/red ratio 1s useful as a m~as~re

of relative vegetation greenne5s and amount when 1t 15 used ,

ln multitemp~ral stud1es, it 15 subject to èrror due to the

effects' of solar elevation tl~ffexences. To eliminate these

effects, Rouse et ~. (1974)' suggested that the differences

between Bands 7 and 5, normalized over the sum of Bands 7

and 5 was more accurate. This normalized ratio was termed

the Vegetation Index (VI). liowever, in or der t'o avoid

working with negative ratio values, an arb1trary constant of

0.5 was added to the normalized ratio and a square root

transformation was applied to the whole. This was termed the

'" Transfq;rmed 'vegetation Index. Other vegetation indices whlch

, . ha~è been derived include a Green Vegetation 'Index

whlch utilizes transformed values from aIl four MSS

(GVI)

BanQ.~ (Kauth and' Thomas, 1976); a"Perpendlcular Vegetation Index

(PVI) and a PVI6 which takés lnto consideration so11 J " 1

backg-round .

information utili~ing Bands 5 and 7 and Bands

5 and 6 respectlvely (Richardson and Weigand, 1977). .'

However, Tucker (1979) ~ound that the Band 7/5 ratio, the , '

squa,re root of Band 7/5, the Band 7:5 difference,' the VI and

the , were very s imllal: fOl: estlmatlng aIl TV!

photosynth~tica11y active vegetation.

Host of these vegetati9n indices were' obtalned in

, 66

C

c

temperate environments on experimental plots and man-made

vegetation patterns (e.g agricultural 'crops), where the

vegetation density was high and relatively uniform in

compo~i tion *. There is sorne question of the usefulness of.

these techniques in semi-arid area~. In these areas, as is

the case in the Maralal trans,ect, the vegetation .cbver ls '. ~

variable in composition~ spac~ a~d ~ime (Sections 2.4 r 4.1

and 4.2). Gi ven i ts physiognomic character,. tlie reflectance'

from semi-arid vegetation will be greatly influence~ by its

non-green components (e.g. limbs and branches), the non-

living ground cover (litter); and the soil .b~ckground. This

i5 particularly so during the dry season' when the

reflectance from th~ vegetation can be considerably less

than that from the soil. In addition, the contribution of

shadow to the composite reflectance will be more signiti~ant

(Graetz and Gentle 1982, Otterman 1981a'). .... '

S,ince 'the. woody·

canopies of semi-ar id vegetation are often single-s,tor ied,

leaf area and density may be Iow, even with the occurrènce

of leaf over lap (Lane, ,1982). Even though reflectance from

individual leaves is high during the 9ro~ing season, the , , .

total energy reflècted from areas of sparse foliage will be

much less than where veg.etatioh is dènser. ,

Griffiths and Collins (1981) have suggested that for ~

dry semi-arid vegetation the role of Landsat imagery may be , ,

\ limited becau~e of the composite ,vegetation and, soil

\ background reflectance. What is 'seen on the false c'olqur'

composi te imag'ery May be soil-type var iations ,( as oppose,d ,te

in vegetation canopy cover or composition )', , due ·tQ'

, "

67 , , .

"

. "

"

, '\

"

. "

, ' , 1

, '

, ,

.'

o

.'

the low reflectanc~ ,of dry ~e~l-arld vegetat~on ln a~l MSS.

bands, the sparse nature'of co~er, and the hlgh,reflectance

1irom the dry 50115. In splte oL t,hese difficultles, }hey

conc~&ed that Landsat imagery was'adequate,for b~oad small--;;Y/

sca1e Imapping purposes ln three situations: (1) when the ,

vegetation type association with pa~t~c~lar landform or 50il

uni t's" was known; ( i i) when the' vegeta t i on canopy cover was

greater than 40%; or (iil) when the vegetatl'on ~ype, remaip{d

in a green state to sorne degree during the year.

Bonner (1979) reached the sarne cdnclusions. He

Indlcated that i t was possible to map general1sed ,vêgetatlon

,cover types from Landsat false colour compos i te 'is:nages,

','particul~rly when the vegetation types displayèd - cllstlnct

o ,

, : image character Istic5 o'r sharp contrast 1 ng boundar les.

, Allan and Richards (1983) have note~ that ~n fals~

col,our compos ite lma'ges, ,when plant growth 15' not vi gorous

and chlorophy,ll absorption is low, such as .during senescence

and dormancy, vegetation may appear darker in colour than

the'surrounding,bar~ soil, especially If the 5011 15 dry and

hlghly refl~ctlve. . t,

Landsat 'data appear to be morè closely llnked to

percent

specles.

Arizona

Landsat

percent

physlca1

ground cover than to vegetation composition or

-I~ a study of'ephemeral and perennlai rangelanq ln . .,. ,a~d Montana, Bentley et èU. (1976) showed tllat

data, was much more sens1 tl ve to variations in the

grouOd coveled by live vegetation than to ;t~tual

and specf;ral dl fferences among t"he plant s~ecles.

Brown et al. (198~J also found that Landsat ,data was more

, ,

4

" 68

1

\ , ,

•

"

c

"J(

c cl

, . ,

"

, ;

',1

l "

1 .stronglY cor'related wlth the amount of vegetation pr:esent , .

1 rathèr ' than vege~~t~on composition. Likewisè, Graetz and

" ,

, ,

Gentle L1982)' 'in their study of a semi-arid shrub range land

i,n Àust;:ralia', con'cl~ded' ~hat cover and not biomass was the

mpst, impo'rtant var lable 'when consider ing sparse 'vegetation

cornmunit'ies (cover values ot',35% or les~)~'

In terms of

are less useful ~

the I~re,d' ,r~t,ios:" 'the ve~e,tation indices

when v~getatfon ls' 'composed of, a high , " , .

proportion of, standing brown ,m'at ter, dùe ta the 'fact that ., ,

Band 7 values decr.ease whi1e those,of Band 5 increase with

, increasing amounts of b'ro,wn matter. Thus, the same

vegetation i;ndex, , vi\lu~ in a mix'ture of brown and, green , .

biomasa , could' represent, a wide variety of 'actual ra~ge (

: Ç~:)fldi~~.i,ons. , In 'addit'ion, , ; çover values é\re once, again

('. $ 1

S ignif icant , 't

. ' in t~e' ratios': 'Colwel1 (19J4b}. conciuded that

the' '.'relationship between "

the IR/red ratio :and cover is . , , L '

,gener',ally, un,reliabi~ if ,cover is below'25%." McCoy and', Witt

(1978 ) suggeste~ a' ~~gure 1

of , 20% ,for' areas with low , /

veg,etation cover. Further, in lo~ to med~um vegetation

co~er, Band 7 appears tp be di9nifi~a~~ly les~ se~sitive ta "

Fover differences than Band S" (H.\elk~ma,· 1980). The work of ,

Graetz ând Gentl,e (1~82) ;rè,~èaled 'that 'the IR/red ratio is' 1

~ \ '\ '

indepenqent of changes in the caver 'of perennial shrubs,' ( " 1 r-.(

when they are i,n a non-vi'gorous g~owth stage~ Similarly,· \ > \ l'

Rouse ,et aL', (1974) concluàed that ihe' ~atioing concept in

general'

d\lring

, , ,

may ~e of li'ttle vaYue in ,semi:-arid' areas, " except 1 4(, Il " ~

the rainy season when the flush ~f annual vegetation ,

oecurs and in regions where vegetation cover is permanent.

69

œ

..

o

'" t '

'"

''''-" ,

., . '. , .

-, '.

..

o

Ftom the above discussion, it f:an be concluded that \

~ Some, caution i8 necessarj',when applying Landsat datà te the

analysls of semi-arid vegetatibn, situati~nri. However, even

~n such situations, Landsat can still be useful, when

conside'1"ing· vegetati,on on a broad-seale, sinc~ the MSS data

can be correlated with percent cover. Woile the use of ratio

indexes may be more limited than in temperate lands, 'they

can still eontribute to the analysis of semi-ar id vegetation

'by pro,v;iÇiing' sorne ide a of ,the extent and productivity of

seasonà-l' gro,:,th' 'in differ"ent ,?,egetation types. Also, ainee

tn,~:dr ,~se l1o'rmaliz~s" tl)e' effect of ~oil background and ",

litter, , they .... can ~permi,t a,'mç,re ',~ccurate appraisal of the " .... ~ ! ' , r, <,. , .

a'c.tu~l ~mount C?f 'vegèta tio~ .pres~nt, p'a'rt. i,eula~ ly dur i ng the , ,

ràiny ,seas~on.

'.

, -,

',' "

. .

"

, - "

\

"

"

,"-

, . "

1 •

70

t

•

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(

'.

'1 "

,,-

(

, ,

'-

"

SECTION II:

'..J

T

l'

v' \

.. , "

\ \

LANDSAT IMAGE- ANALYSIS

li

'.

71

/'

"

, .

';

, . . '

CHAJ?rER 6

DENSITOMETRIC DATA ACQUIS l TION FROM THE LANDSAT IMAGES 1,

6.1, INTRODUCTION

Den5it,ome,try has proven ,to' be a simpl,e yet effective

aI;>pr oach in the exami na,tion of vegetat i on on bot,h' è:olour

Infrared < CIR) aer la l photography and Landsat co}our

çomposlte imagery. ,The pr'ocedures are simple and well-s)Jited \

to third world 51 t~at1ons ,wnerp more e1abo.rate equlp~ent and

,techn iques are oft~n inapprop:t; iate. Manua l pr ocedure,s have

the advantages of ,loW' cast and flexiblll ty which allow the

researcher to address a range of problems.

For, example, Ashley and Rea <1974, 1975) and Hill

(1979 ) ut i lized manual densl tometr le techniques on

multitemporal imagery (MSS Band 7 and 5) at ~he 1:1 million

scale .ta assess seasonal vege taUon changes ln the dee lduous . ,

forest zone of eastern U.S.A. and ln Australian ~a8tureland

respectively. Seevers and Drew (1976) made use of

densl tometr le measutements of Bj?nd 5 Imagery to investlgate

vegetative biomass in Nebraska range lands . Curran (1982)

employed a dens1.tometer ln the analysls of' aerlal' and field

crR pho~ographs to study the relationship between

reflectance ratios, green biomass and productlvl ty in

southern Eng land. Marchetti and Gare la (19 SO) were able to

discr 1 minate J

between __ diffe rent vegetation categories

(cult1 vated and natural) us ing CIR transparencles at

1: 6 000 scale.

Drlscoll ~ ~. (1974b) developed a seml-automated

72

, .

c

, lnte rpreta t ion system' conslstlng of .a mier odensi tometer

co'nnected to a str Ip chart x;ecorder to Identify plant

communitles in the Colorado mountains on CIR photographs at

scales .ranglng from 1:800 to 1:13 900. Everltt et al. (1980)

aiso utllized a mlcrodensitome~r equipped with an automated . .' /

" scannlng devlce ln the differentatlon,of saline from non...!

" saline rangeland, sites in southern Texas using 70mm CIR fi'lm

'at three different scales (1:19000, 1:42 000, 1:80000). A,

siml1ar system was used to examine rangeland sites on

1: 12 0 000 scale CIR photos of the sarne area (Ever Ht et tl., ,

1965). Jordan et al. (1978) employed manual densitometr le

methods to classl f'j terrain cover types in a mixed grass anQ

forest reglon of Kentucky uslng rnultl temporal IR and

\' multispectral aer laI photographs at a scale of 1: 24 lQOO. l t

was found that areas as small as one hectare could be

accurately classl f 1ed accordlng to, cover type.

Gwynne (1977) used densl tometr le methods to measure the

degree of "redness" on Landsat 1: 1 mil 1 ion scale eolour'

compos 1 te transparenc1es of southwestein Kenya. Using a red

fllter, which effectively el1minated a1l transml ttance below

0.67um, he was able to quantlfy the IR reflectance for the

area' s,vegetation. From these observations he derived

seasonal "greeness" maps by expressing the acqulred data ln

terms of a flve eategory scale, from "almost no green" (1)

to "very green" (5). \ \

Den5itometry 15 a very useful tool for analysing ,

vegetation on co lour composl te l mager y . The pr imary

73

, 'o} ,àtI

"

- ,

advantage of measur1ng image densltles 15 the' ~b1l1ty to

quanti fy the expo'sure cl i f ference's on' the \ Imagery, , thereby

removlng subjectivity fram the interpretation

(Kirchner, ,1980). , ,

proceS3

The values of transmission density obtalned from a

Landsat image i néi,irectly represent the spectral re f lect i v i ty , ,

of the ground surface imaged ln the sCene. Upon èxposure and , .

development the' three layers of a co lour film ~orm ye 11 OW, " , .'

magenta and cyan dyes . respectively (Figure 5.1) . The

ùeve lopment process is such that the dye will not form U , "

the layer to wh1ch It 1s coupled wa5 exposed. The dyes act J,

as absorbers and each removes proport ional' amounts of the , f,

add 1 ti ve pr Imary col ours (blue, green and red) when exposed

to whi te l1g}:lt. For example, an ob j ect ~~ f lect i ng ln the

near-IR wi'l.l reglster an image\ on the film lay~r with the

cyan dye resulting in the suppression of this dye but the

release of the yellow and magenta dyez ,from ,the other film

layers after processing. Whèn these two subtract ive

pr 1mar les are exposed to wh i te li ght a red image results, as

shown diagra~atically in Figure 5.1. The amount of dye , -

released ln each layer 1s Inversely proportional to the

amount of original exposure ;reflected from the scene ln each

waveband, a~d it il? the modu'1ations of the dye density whlch

deterrnine t;he 'arnount of absorption by each layer (E>ease,

1969) . The inverse relatlonship 15 such that dens i ty val ues

approxlmate the logarithm of the lnverse of the spectral

reflect1v1tyas shown ln Table 6.1 (Scarpace, 1976). This 113

expressed ln the equa t 10n: -.

74

, l,

(

"

Op =' log Op = log l/Tp ,10 . , 10

, \'where Op = Optical Densit'y at point p. Op == Opacity at point p. Tp == Transini t tance a t point p.,

~I '

TABLE 6.1 ,"

" ,

'\

THE RELATIONSHIP BETWEEN OENSITY, TRANSMIT'l'ANCE AND REFLECTANCE (after ,Smi th and Anson, 1968 r

, , '

DENSITY 1 OPACITY 1 % TRANSMISSION 1 T~NSMITTANCE . 0 r % REFLECTANCE ,

0.00 0.30 0.60 1.00 2.00 3.00 4.00

1 2 4

la 100

1000 10000

100 50 25

.' 10 l 0.1 0.01

1. 00 0.50 0.25 0.10 0.01 0.001 0.0001

When any spectral band 'of Landsat ,imageH i5

considered, the density of the image at a particular J

location is inversely related to the reflectance for that

location.·' Areas wi th high reflectance will have a low

,density and light tone on the image, and vice versa. At any

location on a Landsat image there will exist sorne

combination of yellow,' magenta and cyan dye concentrations

recording the reflectance from that location. The use of the

spectral wavelength selector filters of the den's'itometer ,

makes i t possible to generalize the spectral signature of a 1

particular area, by separating the film response into its

. three\ compo~ent parts (Mace, 1981 h ,

Image den~ity is re1ati?ely simple to

\

\

\ - \

measure with a

standard densi tqmeter. For this study a;n densi tometr ic 1 \

75

, 1

. .J.,' ,

-' ,

" '

0" V

measure.ments were made us 1 ng a d 191 ta 1 readout Macbeth

TD-504 Transm1ss 10n Densitometer \011 th a dens! ty range of

0'-4.,0, equipped w!th Wratten Gelatin Filter.s for red, green

and blue spectra (fllters 92, 93 and 94 respeettvely)

(Figure 6.1).

, 6.2 SELECTION 'OF L~DSAT IMAGES FOR DENSI TOMETRIC ANAL'fSIS

Althougp Landsat imagery of Kenya has been ava llable

slnee the initial orbi ts of, Landsat 1 ln 19'72, eoverage has

been ir-.regular, selective, and of variable qua11ty. Because

of the fact that until reeently there was no ground

:teceiving station in Africa, it was not possible to have

real-time transmission of the data acgu1:ted by the MSS. On-1

board sto,rage of data Is 11mited by the capac ity of the

tape-recordera and thus, only a limited number of scenes

were actuallyaequired (Ouedraogo, 1980). There have been

technical di fficuI ties and fa i IUles wllh the tape recorders

on bath' Landsats 1 and 2, further complicat.1ng the problem ,

of image acquis i t 10n. The limi ted 11 fe of the wlde-band

video tape used ln the r.ec"orders has resulted' ln qual1ty

deter loration ln the images generated and in~dequate ,

coverage, partleJ.llar'ly of repeti t 1 ve. sets of images, due ta

NASA' s reluctance to expend the rema 1 nlng hours of recordlng (

t!me on anythlng short of major dlsasters.

The Maralal transect ls covered by Lands'at Scene 181. 59

(Figure 2.1). Eighteen images were obtalned by Landsats 1

and 2 during the 1972-79 periode There are two images each

for 1972 and 1973, seven for 19'75, one each for 1976 and (j

76

c

/ ~ , 1

92 - Red - (TO·504)

:;)4 - Blue - (TO·504)

.' , I"J

IllU.(R"'\t tv .. ~

CI:, LI

93 - Green - (TO-504)

1 1 _············ 111 ••••••••••••

1 ............. .

--~ L---J-J============ ; . . .......... . i 1 '11===11111

1 ••••••••• 1

----...... t .. ----~J·······i· . \ , ...... . l

, .•••••••• ..,. ..... . ., .... . î"' ••••

106 - Visual- (TD-504/A/M)

FIGURE 6.1 MACBETH TO-504 TRANSMISSION DENS lTOMETER AND ITS FILTER CHARACTERISTICS

77

'Ù , '

-, tI

o

1978, and fi ve for 1979 . No images were acqulred for the

area ln elthe-r 1974 or 1977 . of the 18 avallable images,

only eleven were sui table for intêrpretation, pur poses

because of sueh factors as ex't,enslve cloud coverage and poor .

quallty of one or two bands making them unsultable for color

compos 1. tes.

Details of the eleven Landsat images selected for

prellminary analysis' are given in Table 6.2. These images

were supplied by the EROS Data Center as color composite

transparenctes of MSS Bands 4,- 5 and 7 at the 1:1 million

scale. Bands 4, 5 and 7 W'ere ehosen for the colour

composites because of the greater spectral sensibivity of

Band 7 compared wi th that of Band 6.

An examinatlon of these eleven images showed that the , '

- . s lx images wi th 30%' cloud caver were unsui table for fur ther

analysls since much of thls cloud, cover lay over the hills,

mountal n ranges and hlgh plateaux of the tran,sect, 'resul ting

in a considerable loss of potential Informatl,on about the

vegetation types existing in those locations, Of the five

remaining seenes wi th 0, 10 or 20% cloud covet, the 1973'

frames were rejected since both were imaged in the same

month, and there was no sul table pair (wet season/dry

season) for 1972.

Images with acceptable quallty and minimal cloud cover

were obtalned in 1975 and fortunately, a dry season/wet

season palr 1s aval rable (March 25/September 21). These are

• we Il-su 1 ted for analys Ing ',the vegetation pa tterns of the

area and the seasonal dlfferences ln growth, due to the

78

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TABLE 6.2

LANDSAT COVERAGE OF THE MAR AL AL TRANSECT (Path 181, Row 59 )

----------------------------------------------------~-----------

SCENE I.D. SUN SUN % CLOUD BAND QUALITY IMAGE DATE ELEVATION AZIMUTH caVER 4 5 '7 YEAR DATE

--------------------------~--------------------------- ----------1048-07163 56 82 10 5 5 5 1972 SEPT 9 1120-07172 53 - 1.26 30 2 5 ,5 NOV 20 .

"

1174-07165 47 124 20 8 .8 8 1973 JAN 13 1192-07~71 48 118 00 8 2: 8 JAN 31

.20,62-07052, 51 89 10 5 5 8 1975 MAR 25 2080-07053 52 '77 30 8 5 8 APR 12 2134-07052 \ 48 56 30 8 8 '8 JUNE 5 2242-07041 ,/ 54 90 10 , 5 5 5 SEPT 21

21448-06522 42 122- 30 8 8 8 1979 JAN 9 21466-06525 43 117 ,30 8 8 8 JAN 27 21592-06574 47' 58 30 8 8 8' JUNE 2 ------------------------------------------~---------------------Band Quali ty: 2 = p.oor, 5 = fair, 8 = ,good

minimal cloud cover and the six month tlme interval in imaqe

acqulsit~on~ In addition, , the Afrika 'Kartenwerk vegetation

map was p'repared dur:lng the mld:-1970s at approxirgately the .

same time as the acquisition of the Landsat images."

The ralnfall' data for the transect in March and

September 1975 are listed ln Table 6.3,together with the

detalls of the antecedent ralns. In the dry seasoni prior to

the, acqufsltlon of the March 25th image, rainfall was , .-

negligible. The resu1t is a very dry situatfon with dormant i

vegetation throughopt the transect, with the exception Qf ,

the mountaln :forest areas. In contrast, the September image,

was acqulred at the ta Il end of the wet season whl'ch ~

a f fected the west and central sections of 'the transect

('l'able 5.1). These areas experlenced considerable

79

œ

l'

\ \

>.

'f) .' t. /

'.

preclpltatlon.,wlth the resultlng f~ttsh of vegetatlve grow,th.

Thus, the March and September Im~ge3 provlde 'de.ta-lls of 'the

vegetation at tWQ very distinct pheno1ogical periods- ..... ithin

the same year.

o ,

TABLE 6.3 ,

1975 ANTECEDENT RAINFALL CONDITIONS RELATIVE TO LANDSAT SCENES

. . 1 HARALAL TRANSECT WEATHER STATIONS

DATE 1 KAPEDO 1 KINYANG 1 POROR 1 MARALAL 1 WAMBA 1 ARCHERS IMISSIONI H.C. 1 P.C.I 0.0. 1 1 POST

JANUARY 1 0 1 4 12 1 7 16 13 FEBRUARY 1 2 1 3 3 1 . 0 3 0

* MARCH 25 1 16 1 7 11 1 0 1.1 0 1 .\ 1

JULY 1 194 1 71 190 1 120 53 17 AUGUST 1 87 1 117 144 1 180 0 1

* SEPTEMBER 211 29 1 98 100 l ' 33 34 15 1 J 1

-----------------------------------------------------------Preclpi tatlon f igur:es in mm for: the month

* - Landsat Images

80

. ,

(

c·

, ~... -

, PLATE 1 LANDSAT IMAGE FOR THE MARALAL TRANS~CT FOR· MARCH 25 ~ 1975

.(Scene~I.o. 2062-07052)'. ~ •

. . '

PLATE 2 LANDSAT IMAGE FOR THE MARALAL TRANSECT FOR SEPTEMBER 21, 1975

(Scene 1.0. 2242-07041)

81

"

o

, \

6.3: CONSTRUCTION OF ,A SAHPLING OVERLAY

To ensure a' cons,lstent . ,and systematlc method 1

of

càrrylng' out Qens l tOllle,tr lc measurements on the March and , l,

September' images ~hich wou1d al10w va1id inter -1 mage

co'mpa'r~s<?nsl ,a transparent overlay, contalning a sampl1ng

gr.1d coyer Ing th~ ~nt1re study area, was constructt;h. At the , ,

1:1 million scale, subdivision of the st.udy area into

sampling units of equal size resulted in a 300 unit sampllng ,

, gr id. For' ident i f icat i on pur poses , these squares wel:e

systematically ~um~ered from 1 ta 300 in the manner outlined

ln Figure 6.2.

The main problèm' in the use of overlay gr Ids on a

'series of images ).s rëgistratl0,n. In order ta arrange for

precise reglstration from image ta image," four control

po lnts . were identi'f ied and eare fully marked on the over lay. , . ~n arder t~ qualify as control points the features,

Identlfied in,' Fig~1re 6.2, had to meet the followlng

cr i tel: i a : -

1) the y had to be cléarly visible on bath) the Landsat images and the, topographie maps of the area;

11) they hild, to be permanent features with Il ttle 'possibllitX for change ot shape or positioll, from s~ason to seasoni

lil) they had ta be spaced strategleally with respect to the\tran~ect, one ln the north-east quadrant, another in the south-east ètc., ta p~ovlde for exact fi t.

The overlay grld was rnodlfled for the 'acq.ul'sltlon of .

densltometric data by ident1fylng the position of sampllng

cells ,'within each ~rid square with clrculàr ar~as sllghtly

larger than the aperture size of the densitometer to allow

82

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."

Il 12 9 ,.

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1-

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tin lb! lin -, .... ,- ..

'-1'-" - ,- ,-

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rit

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rio ~

~ .. 1 ••

~ " l" l' . ... 101 • la * ~

~ ri m Il

r' !

.Al

,

CONTROL fEATURES

Outl1ne of SOaH Crater

1 1 Ou~1tne of Lava Flow

1 II Out 11 ne of Llva Flow

IV Dratnage Une of the [",uo Hgt ro R\v.r

'.

,f

. ' .. ,

'1

L ., " r, • • , .. fI' .... ~ .. ~ r r ~ r .. ',.., "".1' ... \' \. 1 • • t •

f _' ~ .... J '--',' -., .... ' ...... 1 _1 ... --... .. _. _. _. _. __ ....... _. _" _. _ •. _ ..... _ ... _ .......... ,. .... ,. .. r ., L' L' , '1 L r r ') L' r '1 r ,.. . r 'l' rI' j' r ',,, \ 1 II' · , . . . - , 1 \ l' '1 ' l '1 li '1 ' l ' ~ , ' ..... , ........ ''''-j~I;....' .... ,J '' .... l''-I ... da.-I ........ jh._,,~.: ... 4 .. i.J.J • . A" J

C· L L ' 'If f r" l' "l ' "l'I' 'l' '" 'l' ." '1 II' ."., . '1 '1 '1 '1 '1 '( JI '1" , . ~I'-' .. , ..... 4, ..... ~1"-': f ;... •• d_f .... 4i .... , ....... ; ............ ,. " .. 4 ,.4 ·.4 ... , .J  J

Cr' C' [' C' r' L" ! ,. l1 r ' - ." ." 'l' 'l' '1' .,' " 'l' '" ' ., '1 " '1 '1 'Il r " 'i '\ t..- 1 , ..... h ... II .... 1 ~f,_ .. L, t..i ......... 1 .. ; "-4 ........... , ........ 4 .4... .J .. .J .. ~

r~-~'" ~.r . _.,. " 1· ... 1ir ';; ~~ .... ~ .... ~;' ' •. ~.

l,J l ... ......, ..... ' ,--....... j ...... , ........ _~: __ , _.'-"'1-.._._. ___ ._ ... _ "._~ .. _~. t. > - ., - - ~

r'\r,..... C [' r-' r") ,..\,. l,r ,r '!r '1' 'il'j' ''' '1' '1' 'l' '1' . '1 '1 1 l' 'l' l.l .. l ..... ~,LI _ ..... Iio. ... I,~"I_ ....... lio.rI , ... j ............ , ............ l~ .. _.J • .; .. , .. 1..ll..lL ... I 4

CC C C - C' Cl "'1 "'-'1 "', ,... ,·("r 'IL'I' 'l' 'l' 'l' 'l' 'l' ., ., '1 '1 '1 '1 "L 1 'l' If ! ~/ "- ~I _," lii..fI ......... "-. '-, "' ....... ~/"' •• ~ ..... , ...... 4 ... L ... ., C C r ~ r ',"- r r', r L' r' P • l'l"l',' 'l' 'l' '" 'l' 'f' " .. " JI " '1 "JI ',J,' , .~IiI.J~ ............ '1.- _, l' fI ''''-' ..... "'-4 ........ ~.,_" .. J _ .4 .... "'. A 4

C r'" ur' r • r .., r ' r - ,. ': r . ~ , l" L' 'L \ Il'I'l'/ ,. '/' , 1 ' '/' :'. . "" JI' l " ' 1 J, ' , ' 1 ., u ~ wu....., .... ~ .... _, 1 1 •. fl ......... ' .... ~ •• _ .. t..4 _ ...... ...... .J ~. <II

OO ......,,....,c~O- ...-.- ............. _ ............. - ...... -- .. - ..... - .. ' ..... ". ':- l'

tr... ~~~~ .......... ~..JL.....i ... JI ................ __ .............. ~'._,~,_ ..... _, ....... ! ................ ,' __ .... ~ .... ,. ,\. .

" J ..

'IGURE 8.2 Ot: .. llrO .. !~AIc: ,AMPl,.I'NO OVERLkY-ANP IO~NTI,.ICATION GRID

\'

83

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.. • 1

)

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o

"

::.

for pos1tlonlng beneath the probe of the instrument. The ~

. aperture 51 ze selected for the densl tometr lc a'nalY31s waa'

,': .3.0mm, and 50 the diameter of the overlay sampling cells hàd

. ta be slightly larger than this. Letraset dots of 3.1 ?,mm

"

~

.'

r

,'dlameter slze were burnished onto the over1ay ln the exact;

'center ' of each gr id square. li 3. Omm d lameter aper ture si ze , '

was conslde.red adequate for the purposes of thls stud'y given . the scale and resolution of the Landsat, Imagery. Itr,

represents a samp'led area of three k i 10metres in d iameter on

,the ground. 'l'he f Ina1 f orm 0 f the over lay con ta Ined the

referenee control features, the samplLnq cells (dots) 1

for·

the densitometric procedu're, a'nd thê 'four ~orner points of

the transeet ta allow reg lstrat 1 on w1 th . 'the, Afr lka

Kartenwerk vegetation ~ap • . ,

""

6.4 l'iEAS UREMENT PROCEDURE ,

'-., . .

:acQulrë 1 The followlng procedurê was used to j

, , 1 .,..

ldensl tome tr le measurements' fram each of the Landsat images: ,

1) The sampllng overlay was placed over the Landsat image , .,

and the control, features were matched to the!r

corresponding location 0'0 the image. /

'2 ) - ~he~n exact correspondence was, achlèved, one edge of t~e " ,

over lay was carefuly secuted to the image \011 th a str 1p

-_ of mask i ng tape, t-hua a 110w1ng the 'ovet l~y to be

fllpped back and fo:rth as :required for maklng the

,dens l tome t:r lc measurementa.

3) To make the densitometric measurements, the image - .

(wlth the q,verlay ln plaCe) was posltloned on the staqe

o 84 •

1,

. , ,

c

1

(iJ

f:>

c , -

of the TD-504. ~ Thè image was then adjusted 50 that the

sampling celi that was bein~ examined wa~

positioned, exactly ove-r thé apertu e, i. e. it was

completely covered by the reference dot and no light " ,

from the in~trument .source was visibl~ àrounc!t,the edge.

, 4) The image was s~cured to the dens~to~eter st~ge with \ . ,

strips of masking tape~ . - , .. 5) ~, A 'densit.y readïng was·made using the visual fiIter with

the, overlay in place. 'This figure' wa.s r~qorded" in.

6) ,

column 2 of the data collection sheet (Figure 6.~f. "

The o'verlay was carefully folded' oac" . and, ~ th~

densitometer probe ~.,a~ 'br:ought ~nto direct ~ontact w1 th" .

the image, A set of four densi ty readings weJe made ~ ,

through the visual, red, gteen and "bIu'e fiit'eis;

holdi~g dOwn the head of the PFobe whilè simultaneousLy i

rotating the filter wheèl.

The overlay was flipped back over the image\ and a

reading was once again taken'through the overlay' with - ~

"'" the visual ·filter. This figure 'was checked with that

taken a t Step 5, to ver i fy tha t ther~ had been, no , , 1: ~. - •

movement of the imàg~ during -the readi.ng, pro,cedure,_

~') The i~age was then ~hifted 50 that the next s-a.mp~e, celI

was i. plac~ ov~r the aperture ~nd the procedure

, (steps 3-·7) was. repeated to obtain a see of readings'

for this sample:

thé image column by

" "

,~

,

and sa on

column.

-"

\ 85 "

~.

from left 'to" ri9ht , acrqss

. "

- .

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.... ~ J

',G,'

','

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e

;- PA(';E 1-10. r

IMAGE NO: - . IMAGE' DATE: ;;.

., FILTED. READINGS

SAMPLE OVERLAY ~ COMMENTS C~LL IN PLACE OVERLAY REMOVED "NO , ,-. VISUAL RED 1 GREEN 1 BLUE 1 VISUAL

" . . "

1 , ,

2 1 " c -' ,:]1

3 "

, . 4

n, , ,

5 ,

" '. '0

" -fi

r .' - J

'7 " " ,

8 -\ 'r ~ • 9 1

10 \ , . , :

11 , '..

" ~ ..(

12 . 0 1

13 , , !), , ~ .

14 - . , ,', .

15 , ,

1'.6 , .

~

J

17 ~,

• "

l8 " . 19 --- ,

• " c 2Q c , . 21

0 ,22 -" •

( 23 r

· . · ,',

, , . r 1 ~

;, ~ , , • r .. . · , -,

1 ,. , , .

'" .- ': ,

, , J l

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FIGURE 6.3' DENSlTOMETRIC DATA COLLECTION SBEET ' . ,\

" - 86

" ' , ,-

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1

, "

Densi tometr le measurements were made on the March 'and

September images at aIl the sampling cell positionsi' except . ,

fo'r situations where the cel~ was " con taminated'" by cloud or' - 0

éloud shadow. These cells were classified as "non-readings".

s'ince poth image,~ had only 10% cloud. cover 1 the 'non-readings

" were very few, resulting in th'e acquisition of 282 de~'si ty' " c' _. \.

measurements (94%) for the. March image and 297 measuremen ts

(,99% ) for the Sel;>tember image. AlI the densi tamet.r ic

measuremen ts are, tabulated' in Appendix A. / '

"' ,

6:5 . PROCESSING OF THE DENSITOMETRIC ,DATA

.1 ' In or,der to make the densitometr ic data meaningful ~and

'\ '

to allow-d±rect inter-:image comparisans, a normali'zation

procedure , is necessary to minimize the effects of

atmospheric scattering and ta standardize the images. Tc

achieve this the densitometric data were processed in the

following manner.

\... Frequency distribution histagrams' af~ data obtained ./

with' each filt.er setting were constructed for each "image. . ~,~

Examina'tian of these histograms revealed that one sample ---cell, (no. 62) consistent!y registered the highest

:> densi ty

'" ' readings in the visuar and red fil ter categor ies for the 1

entire da ta set of both images. For the March image these - ,

" readings were 2.36 (visuai filter) and 3.09 (red filter),

while for the September image they were 2.71 (visuai ) and ~

3.30 (,r!?d). Density readings for this cell were also among

,<~ th~, highest in the green and, bl~e f ilter categories.. This

re~ponse results' from the fact that the whole area covered

87

Il (

J ' 1 ~ J;?,'

, ,

; .'

=z

"

by th 1 s cell consl s ts of recent lavas whlch are unvegéta ted.

Since the se laVas are basalt8 the reflectance ls "very 10w ,

l;...&sulting in the very hlgh denslty readings. The readl~gs

for th i5 ce 11 weI: e used to normal1 ze all the da ta sets ln

the fo llowlng manne r .

G i ven t he ~lava ,'s blac)< ' colora t ion, the reflectance

I: espons e should ~ nll and' he nce,' should r.egister at the ... '. maximum 'deITs i ty :r;eading of 4.0 . T.he fact that the .denslty

r ea'd'ings are less than 4.0 indicates that ~- ,

error factors,

produè'ed by a .processlng or system error and the ~ Hec ts of

d~t or hazè, have been i'nhoduced' i"nte the denslty data

, seb~. The contributton of proce!3s1ng 'and system factors was

, ,

~ assessed fro,m the red fliter data which are representative .

of IR' iefleet~nê:e. Sinee the r e,flect ive 1 R wave lengths are,

Yessentially' fre"e of atmospheric 5catte~ing effects, the

dl~fèrence between the red fil ter readlng for ce Il 62 and

4.0 wfls assumed to be due t~ system or processing factors' .t

'whlch fntrÇ)duced' en~rgy lnto the f10w prof lIe and boosted

these readings to 3.09 for March and 3.30 for September. The ,

addlt'1on of ,

0.91 densl ty uni ts to aIl the March data and \

0.70 ~o th,e,September data set would correct for th1.s error .

. This corr~c;:tlon however, would not aceount for atmospher1c (

sèattering which has a dlfferential effect accox:ding tp

wavelength.

atmospher lc scatterlng correction factor wae

determlned by adaptlng the technique descr Ibed by Sabins

. (1978)1 and Jensen (1986). Unl1ke the reflective IR, the

"vl{s1ble wavelengths aie strongly affected by atmospher le

88

c •

.. , ..

'" , ,

•

\

scattering. The lack of high density values in the visible,

Le. the' blue and green filter readin9s, was att.dbuted ta

the i,llumination~contributed by Rayleigh scattering. Hence,

for eaoeh image, ,thè cor rection factor for sea t ter ing was

calc\lla ted as being equi valent to the difference between the

maximum green, ,bIue and vieual densi ty values (to which the' il '

processiog correction factor had already ... been added) and the •

4.0 ,dens! ty value. For the March data these addi t iona1

correction factors were 0.55 for" the green filter data, ,0.95 ,

for the bl\le, and 0.73 for the v isual. For 'September the"

factors wece 0.54 for the 'green, 0.88 for·,the blue, and 0.59

fer the visual. In, this way the ef fects of atmosph~~ lc

scatter ing on the data are minirnized. A haze correctipn

factor is not necessary on Landsat images acquired after '1

1979, as this ls being routinel.y applied at the

pre}1)rocessing, stage (Short, 1982).

,)$'he cor rection factor for system err,Qr plus the

atrnospherlc scatter ing factor producéd the total correction

factor for each fil ter category for each image da'ta set. "For

the March data these factors Iwere: 1.64, 0.91, .1.46 ,and 1.86

applied to the visual, red, green and blue Eilter data " "

1

, respecti vely •. The September equi valents were; 1.29 (visual),

0.70 (red), 1.24 (green)' and 1.58 (bIue) • Adding these

"./. factors to the, density readings norma1izes the data and

allows meaning~ul inter- and intra-image comparisons ta be

made,. The cor rected data for each of the four fil ter

oategories aÏ'e listed in colwnns 7 to 10 of Appendix' A. Only , "

these da ta were used in the subsequent analya~s • ....

89

\

" ,

, '

\ .

'0 , ' .

The corrected densitometiic da~a were' stratified

according to vegetation type by registering the sampling

overlay to the .1.: 1 million J\frika Rartenwérk v~getation map . . (F1gure 6.4). ln this way it was possible to determine the

vegetation ,category for each of the sampling cella. ,When

the sampling cell lay entirely. within a', particu.lar

ve9~tation category it was assumed that the density reading 1

was representative of that vegetation' type. Howevèr, when

any port~on of the sampling cell lay astride or touched a

vegetation b0uG~ary. line, that cell was treated as a

transition or ecdtone and was disca"rded for the purposes of ,/

"wi thin ll veget'a't iorl category analysis, ,but set aside for

1ater use in analysing the vegetation boundaries. The

vegetation category as~igned to each samp1ing cell is

indicated in column 2 of Appendix A. Table 6.4 shows the

actual number of réadings acquired for each of the seven

'vegetation categor les and ecotones, from each Landsat scene.

Vegetation, types 14.0 and 14.~ were"grouped together because

of their simi1arity, and a1so because of the smail numb~r of

sampling ce11s available for each. ,

The stratified data were dea1t with ~n ,the fo11owing

manner. 'For ~ach of the scenes, the corrected 'densitometti,(::

readings obtained'through the red, green and blue fiiters

were converted from optica1 density valués ta percent

transmission using a conversion table (Appendix B). From .. \.-

these figures the total transmission 'and the % red, % green Il

and % blue transmi~sion were ca1culated for each sample cell

(Co1umns 11, 12 and 13.of Appendix A) •. ''1'b~ decimal values of

90

'r

,,,

1

~

"

o

.-

-

.... -...; ... ~ ••• ••• • ••••••• ••• •••• •• ••••• • •

FIGURE ,6.4

-ta. ' ,.

-REGISTRATION OF THE SAMPLING OVERLAY AND THE AFRI~A KARTENW~K VEGETATION MÀP

"

'.

"

.~~ TABLE 6,.4 ~~ h _ 4

THE NU~BER OF OPTIMUM AND ACQUIRED DENSIT'l MEASUREMENTS) FOR EACH VEGETAT'rON TYPE FROM EACH' LANDSAT SCENE

'. .., 1 • .. ' . t .' 1 mllA UITUnll VlGlYlTlOI UPIS . 1 ICOtOll 1. 101 , 1 fOUf, , SlIPLi 1111111" , 51.1 1 52.' 1 SZ.ll 67.$114.".2 1 41.2 1 64.1 1 1 cnu , J ' __ 1 1

1 1 1 1 1 , 0"1191 10. or 'J'III , 1 1 1,1 1 s~ 1 , 1 , ClftCOlt .UlLI ClLLI 1 lOI 1 S9 2 1 181 13 , 1 2" 1 ,. 1 " ' t r. Del DG. 'IP. 1 , . , ' , 1 1 , , \ 1 '_1 1 1

, . 1 1 1 1 ,

1 nu. ,w 25 1915' " , S, 1 2 , Il 1 , , 1 t 1 191 1 .S t 11' III. 01 ï ,

" l , , 1 , ,. 1

\,111111'" IIP 21 1'75 , 1 •• , S9 1 2 , 17' 11 , 1 S , 2.3 , ,. 1 ']

1 1 I~I 1

91 , '

1 l' '

,

.,. -,

o

0--,

','

,f

the calculated percentages were rounded o to the neare:5t

Integer:- - These. per;centages weze the'n treated as sub~et:5 and

. plotted on ternary d iagrams . Ternary ~ d lagrams are weIl ! L

suited for three band denslty ord1nation, but have not been

w1dely used. The technique followed here is based on that of

Parry (1975). This procedure allows the recognition of

clusterlng, or the lack of It, ln the data. It also perm1ts

~n apprec la t Ion of the separa-bi 1 i ty of thé . d if ferent

spectral signa~ures.

The March and September data were also plotted Jn a

pair-wise combInat ion on scattel:graphs, which relate "the'fed-: ,

and the green dens1ty readlngs.' By graphlcally ex'pressihg

tzansmittance as a ratio of red (IR zeflectance) ànd green

"" " (zed reflectance) , the spectral s,lgnatures car;t be -

- qua 11 ta t ive 1 y ana lysed wi thou t. the difficulties othe zwlse \

Ciaused by 5011 background and variable illumination . •

• , "

, " -

,ç

.'

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-, '

1

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- '-".

" ','

92

1

--r

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/

"

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, ,

CHAP'I'ER 7

ANALYSIS OF THE DENSITOMETRIC DATA , .

7.1 INTRODUCTION

The - - ~ . object! ve of thls study 1s to -explore the ways ln

wn-lch Landsat MSS colour composites can assist the user of

~jlmall-scale vegetation maps hy 5upplying supplementary

..information and by provldinq a means of verHylnq the

accuracy of the .vegetation types shown on the map and the

posl t 10n of the boundar les. The approach that 15 fol1o~ed 15 \ ~

"low-technologY". It 1s approprlate for developlng 0 are~s

where manual proce~ures can provide a simple, effective and

lnexpensl ve method of a1)ê11ys1ng the more a ffordable Landsat

transparencles.

SlJt1ple densltometrlc analysis of Landsat col our

" , composite lmagery can conttr Ibute slgnl flcantly te the ' f)

understandlng o~ both the pattern and the phenology of th~

~

natural vegetation ~f a,n area. The information derived from

this type of analys1s ls a valuable complement to that

provldèd by a small-scale vegetation map. This chapter is an

exploration of sorne of the ways in wh! ch densl tometr le

analy~ls can contrlbute to the analysls of the vegetation of

the Haralal area and analogous env!ronments. The

densitometric data ge~erated using the procedures ?escrlbe~

ln the previous chapter: will be evaluated in three ways:

( 1 ) 1 t wUI be assessed ,wi th regard to 1 ts usefulness

ln dlscrlmlnatlng between the var ious vegetçatlon (:.,1 ,

type.s

present ln the area. This Involves an examlnat 10n of the

93

, '

•

o

location of the "wl th!n category" data on both the ternary

plots and the IR:red .scattergxaphs to determlne the gene~~1

. spectral reflectance character isUcs ..,r: h of eac vegetation

type. (

(11 ) The "wi th! n category" data will be examlned to

assess the value of thls type ,of analysls in followlng the

phenological trends exhlbi ted by the dlfferent vegetation

types.

(11i) The sites whtch appear from othe P densltometrlc

"analysis to be ecotonal will be assessed to determlne •

> whether this character lzatlon 15 ac:p:urate.

,1

Analysis begins wi th the dr,y season image (March 25,

1975). At thls date the antecedent rainfall condltion~.

create a uniformiy dry state of the ground throughout th. 1

entire transect, whereas the situation on Septernber 21, 1975

18 compl icated by the ml x of dry cond 1 t Ions ln the

transect 1 S eastern sector coupled with wet condi tions ln th,e

west and central regions. In effect, the March image

provldes the basellne for the analysls of ~bsequent

phenologlcal changes ln the varlous vegetation types.

" 7.2 DISCRIMiNATION OF VEGETATION TYPES IN THE DRY • SEASON (MAR CH)

,- 7.2.1 DENSITOMETRIC ~ALYSIS AND FEATURE SPACE SEPARATION:

\

'. ln the dry season, ref1ectance from the ground surface

18 generally hlgh, however the absence of grasses and

follage over much of the area results ln a spread of the ~

data points lnto the zone of very 10w 'red and hlgh

94

'green

'f

(

..,.

.. "

0

ri

~II)

$20

~2 1

41 2

/WI

liB

140/2

x )(

~

â

• 0 0

*' 'X

..

\

%RED<~O %GREEN>SO

VEGETATION TYPES ~l O. 520, 6? J

. ~.'

, " VEGETATION TYPES 41 2,64 1,87 S '. -

%I!t:n :.~O ~GREEN<:'20

VEGETATION TYPES 14 0, 142

" ~ Il ..

• " R~D TRANSMISSION

• '. , ,

FIGURE 7.1a

\TRANSKISSION TERNARY DIAGRAM "OF ALL "WITHIN CATEGORylI DENSITOHETRIC DATA FOR THE HARALAL TRANSECT

LANDSAT SCENE 2062-07052 HARCH 25', 1975

4- '~

r. '" - -,' " , "

\tt- "

) ,

" , "' ~. ,.'

" 1.

95 '. ' ')

, ."

Il

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'0

~ransmission values on the ternary dla~ram <'lgUre 7.1a).

For a CIR Image this means that the Infrared (ve~etatlonl

reflectance 15 low, whereas the red (soil) reflectance 18

hlgh. The %blue values whlch represent the reflectance ln

green wavelengths are low throughout the d lagram. The sp,read

of the transmission data i5 a functlon of the differences in

the " spectral reflectance of the se'ven vegetation formation

groups in the transect (Figures 7.1 band c). [n these

plots, the grouping of partlcular subsets of data in

specifie tlfeature spaces" shows that some of the vegetation

types can be easily dlscrimlnated, whereas others aIe

overlapping. Those vegetation types which have a significant

thorny plant component ln their composition are dlfficult to

separate on the basis of thelr spectral reflectance in (\ . the

dry season. For example, the feature space of the vegetation,

type 51.0 shows considerable overlap wlth that of ty~e- 52.0.

.. Types 14.0/ • 2, 67.5 and 51. 0/52.0 are separate from each _

other, but the feature space of type-64.1 vegetation - lies _ 0

wl thin that of typé 51.0 and the type 41.2 feature space

,oyerlaps those of. both types 51.0 and 52.U. Each of thesé

featu~' spaces will be examined ln turn with ref~rençe to'

the, 'type descriptions gfven ,ln Table 3.1 and the relevant·

information presented ln the background chapters. In the

,analys is particular attention will be pafd to those wi thln \..

" _ category çells which exhibit distinct anomalies when

compar·ed wl th the genera,l trends of the type.

".

96

o

.--~

412

64 1

fl7 ~

14 Il: J

o o

" x

..

~~o D

150 0 D

D

149.- à 117,118

1400 1311- 0 \Ill ..

J

..

-,

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o

a __ ,~"'-'f-P. -1

.. ..... • " RED TRANSMISSION (CROUND REYLECÎ'A'NC"! IN IR II

, ,

'F,I GURE 7. '!l t;>

--,-

11

. "\TRANSMISSION T'ERNARY OIAGRAM OF A't.L "WITIÙN CATEGORY" D.vA- - " ,FO~ VEGETATION TYPES 41.'2,' 64.1, 67.5 AND 14.0/.2

FOR LANDSAT SèENE 2062-07052 'HARCH 25; L975

-J , '.

97

. -

,'.

. ,

o

(C,.

The ,tran}5~ls's10n . data for 't}ip,e 14 -.JI' 2 v~getatl0·n 1~.,

concentrated at the hlghe3t \red ape~ ~f~e ternary dlagram

(Fiqùré 7.1b), This vege~ation type consistr of evergreen

montane forest covering mUch of the Mathews Range and the

K~rlsla Hl11s. The hlgh IR reflectance from the broad-Ieaf

canopy ls expressed ln intense magenta _on the !..andsat

transparency (F 19ure 5. l 'and El la te 1), res ul t 1 ng ln h 19h

%.r:ed transmission (82-98%) when analysed with the

dens i tome ter . This vegetation type -e-xhibits minimal

transmission in the green (1-6%) and the blue (1-4\).

A detailed examlnation of the composition of the ,

, veg~tation type 14.0/.2 featur'e space suggests possible,

dlscrepancles in the cla~sificatio~ of sorne of the sampllnq

eells. As seen ln Figure 7.1b, the transmission data from

two of the sampling cells (170 ~nd 252) are located wlthin , ,

, , .. the yegetation type 67.~ feature space, while data from two

other cells (159 and 277) plot between the type 67.5 feature , ,

spac~ and the Mean concentration of t~e type 14.0/.2 -data

which Ile to the left ~f the 95% red transmlsston vàlue.

--.Forest type 14.2 15 located ln the Range

(Figure 3.1). It 15 mor~.o~en in arrangement than type 14.0

~orest and 15 Interspersed wlth open areas of grass (Table

3.1) • The more open nature of the vegetat ion canopy 1 n th'ft) 1

area could provlde the ex~lanatlon for the inctèased \green

transmisslon seen in the data fot cel15 252 and 277 .. '

However, cells 170 and 159- belong to the dens,er type' 14.0'

forest and other 14.2 type cella (255 and ~65) are

comparable to the type 14.0 sampllng cells. It fo11oW8 that

98

.,

·-

factors other than stand arrangement must be responsible for

the lower l'R and hlgher rad, re'flectance of these cells. The

probab'le explanation for the anomalies can Be found in' tQe_

mlsplacement of the vegetatlQ,n boundary on the

Referente to the Afrika Kartenwer~ indicates that cell

map.

170' . ,

lies close to the boundary between vege~atlon·types:14.0 and

67.5 but wi thin the l1mi ts of th'e former -( Figur~ 6.4). The

location of the transmission data deep wlthln t~e ty~e 67.5

feature space suggest~ that sample cell 170 15 not evergreen

fo;est but ecotonal in character, 1.~. the bo~ndary between·

vegetation types 67.S and 14.0 passes somewhere through th1s

ce1l. Sample' cclI 252 lies close to the boundary between

,vegetation types 14.2 and 51.0 and a s1mllar type of

,explanation may aiso apply to thls cell.

Panchromatiè alrphoto coverage was avallable for· the

a:rea covered ln cell 252. An examina.tiqn of th~se' p-hotos

using the rnethod outlined ln Appendix C revealed, that the

area cove'red by the sample cell consists' of about 90\ forest ! y

and 10\' blghly _'_' reflectl ve bare steepland, slopes , "

(Figure 2.3a). Approxlmately 20% of ,the forest caver of th15

cell lies ln the'';deep s~adows of t'he more precipito\,Js

slop'es. The contribution of the shadows and the bare slopes

results in the anomolous lower \red and hlgher ~green and

'blue transmission values recorded for this cell, compared

vith the other sampllng cells for vegetation type 14.0/.2.

Slmllar topographie factors may be responslble fo~ the

anomolies aS80clated wlt~ sam~l~, cells ~77 and 159. Alrphoto

coverage was avallable for both these cells and in the case \

t

'. r

. ) : .

~

". ,

. ~

-'

. '

.-\

..

of cell 159, It \lias found that the .area was ':~ompos~d of

a~~~o~~telY 65\ dense forest and 15% bare so11. The bare -

soi1 component 15 probably respon5ible for the higher ,\green'

tJ:ansmlsslon '-values for 'thls celle In tti'e case of ce11 277, -

a~rphoto anal~s15 'rev~aled a mlxed composition of about 60\

vegetation and 20\ bare 5011 or rock outcrop5. The alrphotos

"{Plate 3) suggest ,that the cell 15 ecotbnal in character .

Th~ vegetation 1~ mixed; the foreet e~ement 15 conflned to

the hlgher elevat ions and thete i3 a gradua! 'trans L tian to a \

bushland 1andscape ln the foothll1s. The mlxed.compositlon

'of"this cell would account for 1ts anomalous Iocatlon ln the

ternary dlàgràm.

The feature 9

space for vegetation l'

type. 67.5

(Figure 7.lb) 15 adjacent to that, of vegetation . . type

14.0/.2. The \r~d transm~sslon values' for type 67.5

vegetatl"on are generall'y lower than those recorded for ,type J

, '

14 ",0;.2, whereas' the \green values are hlg'her. Type 6'1.5

'veg~tatlon ls a montane forest~g~aasland aa8~clat1on whlch

occurs a10ng the northern' margln of the Lorog 1 Plateau and

ln ,the saànta HUIs ,(Figure 3.1) .. In the dry sea50n, the

grasslands would be ln a dormant 'state. Thua, the Land3at

MSS 'Jou l,à be senslng a comblnatlon .. of foreat and Utter

reflectance.· The IR ,reflectance fro~ the forest component

'Would result ln a moderatley hlgh 'red tran3'mlss10n (66-"

87\) , while thè 1itter and any bare ~011 would be

responslble for the hlgher' \green values for th15 type

compa~~d wlth type 14.0/.2 vegetation.

100

f'

"

&1

...... N

•

.-

, J •

,~I

, " PLATE 3 STEPEOGRAM OF SAMPLE CELLS 277 AND 287

. ;

101

....--------- ------------ ----

"

1 -

"

o

The d Ispers 1 on of. the type 67.5 dat'a po 1 nte can be

attrlb~ted ta dlfferences ln the ptOPOtt~ori of rnontane

forest tq grassland withtn the type. Those data .polrits wlth

the hlghest. \red valUes correspond to cells where the

greatest concentration of montane forest occurs. The

location of the furest component of the type 61.5 vegetation

complex 15 weIl displayed at "Ali ln Plate 1. As not.ed 1 n

Section 2.4, the Juniperus and Podocarpus dominant forest 15

confined to the sheltered, wetter valley bottoms of the ,

intermittent rivers which drain the sQuth-faclng slopes of 0' • ,

the Saanta Hl11s. Alrphoto analysi5 showed that ln' the cells

exhibi ting the highest %-red "~aluésl' 'the_ forent compr Ined, 5~'\ or more of t~e area sampled. As- the forest component

decreases and the proportion of grassland ln the ~~mpllng

cell increases, reflectance, from the soil and dry I1tter

layer contr Ibutes more red wavelength energy to the, total

reflectance. These cells exhlpit higher %green transmission

values.

The two cells for vegetation type 67.5 with the hlghest

~green values ~re numbers 139 and 149 (Figure 7.1b). The~e

cella' are located on the Lorogi Plateau whlch ls a surface

of low relief wlth relatlvely few intermittent rivers and a

.deep ground' water table whlch l~ml ts tree growth. The resul t

ls a greater grassland component within the area sampled by

, '

these cells. The, p<?sl tion of these two cells 1n the ternary

dlagram raises the questIon of the accuracy of the boundary ~ -; 1

shown on the Afrika Kartenwerk. ,The transmission data for

cell 149 places It wlthln. 'the feature space of v~getatl'on

102

c

,l

> ."

• type ~4.1, while c,ell 139 lie5 at the edge ,of this space.

This 'suggests lthat there ls a closer affiliation with the .

type 64.1 vegetation and an error in the position of the

67.5/64.1 boundary shown at thls location on the Afrlka 1

Kartenwerk.

There is another possibil1ty. , 'Data points 139 'and 149

may be correctly classifled in which case data point 140 is ,

incorrectly classlfled ln vegetation c~tegory 64.1 and

should actually b& ln c~tegory 67.5 for which it qualifies ,

ln tèrms of the %green transmission r.t

r-eading' (22%). The'

possible error ln the position of ~the type 67.5/64.1

',boundary shqwn on the Afrika Kartenwerk will be examlned

further: - in il later section of this chapter which deals wl th

the ecotonal data.

A

'vegetatio~ types 64.1 and 67.5 are siml1ar however, • • 1 "\ _

typ~ 64.1 con~ist5 of scattered thorn plants and grassland,'

the Acacia-Themeda association descrlbed, in Section 2.4. 1

From Figure 7.lb it cao he appreciated that type 64.1

- vegetation i5 spectrally distinct fr()m type 67.5 in othis 'ili~y

se'ason sltuatlon., When, compared wlth the data for: type 61.S

vegetation, the transmission data' for type, 64.1 exhlbit

lowèr \r,cd (58-68\), and hl<;Jher '\gr,een (25-34\) values. '.t'he

\blue (7-8\) values ar'e s Iml1ar •

The woody Acacia cpmponent. of the type 64.1 association . is ,generally of limited stature and ch~ra~terised by 'ga11èd

,thorny bushes and shrubs. The result 1s a more open

physlo9nomlc arran~ement w~th sca~tered bush~s, shrubs (and

'\

103

",

o

l..

sometimes f'~

trees) standIng above .the perè~nlal grass layer,

as ,shown in Figures 4.1g. IR reflectance ln the dry season

will be less' th~n that for type,67.5 vegetation, vith, the

lncreased red reflectance from the dry grâss 11tter

resulting in,higher %green values (32-34%).

The bushland vegetatlon types (51.0 and 52.0) dlsplay

considerable variabllity in their transmission values. In

comparlson to the grassland and' forest vegetation. types

dlscussed above, the data for types 51.0 and 52t~ vegetation

are much more dispersed (Figures 7.1 c). . - Percent red

~transmisslon values for type 51.0 vegetation cover a vide J

,f range (22-74%). There 15 a more moderate range ,ln the \green

• values (20-57\) and a relatlvely small ra~ge ln the \blue

(6-21\),. Type. 52.0 vegetation oecuples a more aoncentrated'

feature spaee than that of, type. 51.,0, and the data ,cluster

at higher, %green and %blue levels. The range of ,

\transmission values for type 52.0 vegetation are smaller

than those of type 5t.0: 15-56% ln the red, 34-58\ Ir the

\" gré'en and 10-27\ in the blue.

. " overlap of the two data sets can be attributed ta

the F

siml1arlty of the vegetation types. According to the

Afrika Kartenverk descriptions, the vegetation types 51.0

,and 52.0 ~re variations of the same dry' thorny' bushland

which conslsts of variable density stands of thorn plants (t,

(malnly Acac,ia dominated bushes), low shrubs and succulents,

vIth a sparse ground cover of mostly '~nnua1 grasses

(Figure 4.1 a to el. However, type 52.0 vegetatIon occuxs ln

104

:'

' ....... nNI .......

'I}

--,

c

'\

,i' o

1 •

. ' .. . '

......... -

o

,

(') .

','

,-

...... -

•

li.....,.. ftfII \10 .... 1.

B

"

• ri

1 \

• 'Ji RED TR ... NSMISSIOH

FIGURE 7.1c ..

,. ~

r"t"

~ 71>.

'!'~ ';P. ,!!,

0"

, .

.. '

• (CROUHD REFLECTAKCE 114 IR .l)

~

-r. ~ 9-. . ~

-Pt" ~

~ ~ • "=,. ~ ~ ~ \ ~

............ ., "

\TRANSMISSION T~RNARY OIAOR~S OF ALL "WITH1N CATEGQRY DATA ., FOR VEGETATION' TYPES 51.0, 52.0 AND 52.1 .

-..: FOR LANDSAT SCENE 20.62-0705-2 HARCH 25, 19.75

\

- 1

)

~ 1

105

•

\ \

. '

) 1

the drlcst sectors of the transect wlth the result that the

stands are much more open and stunted_ than îthose of type

51.0 vegetation and the ground cover-ls much sparser. In

both types, the wlde ~ange of IR ~eflectivity, as seen ln

the tred data, 18 a functlon'of the va~labll1ty ln the

distribution of actlvely-growing vegetation' which 15

slgnlflcant along-watercourses and mInimal elsewhere. The

range of %blue and tgreen transmission values suggest

variability in both the follage anq 5011 calour. The open

cha~acter -of type 52.0 vegetatlpn results ln rower IR

reflectance levels (%red transmIssion) and hlgher red

reflectance .C 'tgreen transmission) from tlle ba.re Î S911s,

especlally durlng the dry season'when the annual gra~5es are

absent and the perennlals are ln a dorm~nt state. The result

15 the concentration of the 52.0 ~ata at %green and \blue

tran~mlss1on levels whlch are ~lghe~ than those exhlbited by

the 51. 0 data." }

Vegetation types_ 51.0 and 52.0 OCCUI- throughout the

transect~ A detal1ed,' examlnab·lon of the location o' of the

sampllng ce,lls ,ln the 1!'~rnary diagram reveals the existence

of 'distinèt ~eglonal dlfferences ln the spectral reflectance \' ,

,~- these two vegetatl'on types. In general, the transmission

'i _data from type 51.0 and 52.0' vegetation in t~e western half

of the transe ct exhlblt lower \red (22-52%) and higher

\qreen '(35-57%) and %blue (14-21%) values CFeature Spaces \,

"A" and "e" in Figure 7.1c)~ The data f~om sampllng cella ln , '

- the eastern pa~t of the transect show hlgher %red (54-74%) . - '

and lower \green (20-37\) and \blue (6-11\) values (Feature

.~F 106 '-- .

o

"

l

"

,0

-.. -. --- --.--- .------.. ---- --_ .... --.- ----------------------------"""1

spaees "B" and "0" ln Figures 7.1e).

ThIs regional. d1fferentlation 15 attr1buted to three

factors. F1rst, the western region of the transect 1s more

aIld than/the eastern reglan (Figure 2.5), particularly in

the .,Rift Valley. The configuration of the Valley and its

generally _ lower elevation cornpared to the rest of the

transect (Figure 2.3) results in a raln-shadow effeet sueh

that the area does not experience the orographie

precipitation that oCCUrs in the Eastern Highlands. Second,

the parent materials of the western half of the transect are

Tertlary volcanics resulting ln so11s whlch are shallo~,

.. daIk col~ured and clayey in texture (Section 2.2)._ Third, a

number of lava formations occur in the Rift Valley. These

are excessively dralned and are qufte rocky, discouraging

vegetative growth. \ \ These three factors act in concert to limit the grawth

of large woody species and perennlal grasses. The ground

conditions favour ephemeral grass,species, succulents and

some small xerophytic shrubs, such as Acacia refJciens, as

the main torms of plant life wlth much of th~ ground belng ~

bare throughout the y~ar, as noted in Sections 2.4, 4.1 and

4.2. The transmission data reflect the influence of these

factors wlth lower %red and h1~her %green and \blue values '~" 1

for these areas.

The ' .. '

hlgh~r \red and lower \gre~n and \blue values for

the vegetatlo~ types 51.0' and 52.0'areas located ln the

transect's eastern r~glon (Feature Spaces "B ri and nO" ln

'Figure 7.1e) reflect both molsture and ,8011 conditions.

i07

o

compared wlth the Rift valley ~Iea, the Suare and Il ponyekl n

Plains, are dralned by a nuroper of rl~er5, ~ome ~f whlch are " perennlal, e.g. the Barsal'ol' and Seya (Figure 2.2), In

'~

addition, the' 50115 of the ~astern ~eglon ar~'derived frolâ

Ba:sement system rocks and tend to be moderately deep, 'sandy

in texture and well-drained (Figure 2.4)4 Thus, conditions

are'more favou~ablc for the growth of woody specles, shrubs

and perennial grasses. The transm{ssion' data from these ,

sectors of the transect reflect a larger active vegetation

component than ln the west and differences ln 5011 colour

which var1es from dark red to yellowlsh brown.

While thls general' regional dfvlsion explalns the " .

'dlfference between the densitometric data for these. two

-vegetation types, a few anomalIes occur which warrant sorne

discuss1on. For example, the data froID cells 151,. 'lSl, 171,

181, 191, 201 and 211, which are aIl located ln the eastern

half of the transect, plot wlthln Feature Space' C

(Figure 7 .1c), 1. e. the y have more aff Inl ty \-tith the western

subset of data. Converse ly, the data from celle 94! 104,

105, 113, 114, l

121, 122, 123, 132 and 133, which are aIl

located ln the western half of ,the transect, appear to be

better matched wlth data from the transect's eastern regloQ

as they plot wlthln Feature Spaee a (Figure 7.~c). The ',~._y

location of these sample celis ~y explaln thls disérepancy. \

They oc~ur on the Lopet Plateau (1 500m) whlch exper~ence,s ,

orographIe precipitalon ~lth the result that theré 15

\ ' greater vegetative groWth than ~ould b~ possible ln th~ Rl~t

Valley, and higher \red transmis~lon'values than for other .

~08

\, . , ,

. l - \.

\ '-

• ! ~.

"

. '

areas of type 51.0 vegetation. In the case of'cells 151, \

.161, 171, 181, 191, 201 and 211, (vege,tatl-on type 52.0l, ...

~ thelz: location within Feature Space C suggests that the a'rea ~

. cov~red by the-se eeUs experlences vegetative "gx:owth

conditions s,lmlHu to those of the Rift Valley. ' 7 •

The close cor rèspondence of feature spaees 51.0 -:

, ' "-

subset A and 52.0 sugg,ests that the veEJrtatlon tjApe 15

actually the së;lme and that the 51.0/52.0 boundary ln the'

western reglon of the trdnsect inay be an art i fact. In the

monograph that aecompë;ln les the vegetat lon map ( Bader (1979)

adml ts that the boundary between these two vegeta-t i on types 1 •

1s uneertë;i in .,-The problem 0 f ecotones \011 Il be examlned later

ln thls chapter.

The densl tométr le .

data for the type, 41.2 vegetation

plots ln the same feature space as type 51.0 vegetation

(subset B) • Red transmlssi~n values range from 46 to 70%,

'\green vë;llues range frOID 21 to 4Q~., wlth a very BIna 1: l range

ln the %blue data (9-14%) (Figure, 7.1b). The phys1-ognomy of

t;he vegetation in types 41.2, 51.0 and 52.0 lB very slmÜârj

theyare aIl bushland (Table 3.1) ~ T~e spread, of data with.ln

the type 41. 2 feature space 'ls deemed to be the result " of \

differences in the proportion of tholny' p.1ants, shrubs and

grasse5 wlthin the samgling celle The data from those cells

whlch lie close to' .the·41.~/67.5 boundary exhlblt the

hlghest %red tr~nsm,lss ion (I-a' reflectance) for the type.

Alrphoto coverage was aval1able for sample cells 97 and ~ 1 • •

, "-98. - These cells have hlgh 'red transmission values. The

109

,-

, \

•

1 e

1

c

, ,

ah:phot05 Indlcate that there 15 a woody component of 55\ to

60\ ln these area 0 The rest of the c.ell consi::st::s of shrubs

and sorne grassland which woulâ be in a dorman~ state at thls

tlme of the year. The explanat10n for the spread of the type •

41.2 data points (50-70% ~ed transmissIon) probably lles in {y

the fact that cells 79, 80, 88, 89, e90 and' 100 have a -woody

component 0 f less. than 55\ wi th shrub and grass e lements 0 f -

up to 45%, .whereas sample cella 97 and 98 support a, w-pody \

cover of more than 55\ wi th a correspond l ngly lower percent -

of, open ground.

The data sub~et for type 52. i v'egetation rsvery 'small,

.' .conslsting of only two "withln category" sampling cell~

(nos. 42 and 62) (Figure 7.1c')'. Cell 62> exhibits the lo~est·

%red transmission (IR reflectance) and:' hlghest %blue '

transmission (green reflectance) of any area ln the entire

transect (Figure 7.1a). The lava formation on whl'ch celi 62

. c. 15 located 15 clear ly vis Ible in' Plate l, j.ust north of the

. \ Slla11 caldera. The absence of vegetat ton, as Indicated ln

,

t'he type description (Table 3.1), results in ellmited IR

reflectance (17\ red transmission), and the .large area of

bare lava ls responslble ,for the hlgh rcflectance' in the . .

m~ddle wavelengths (50\ blue transmisslçm) o. In contrast, the

densltometric data for ·cell 42 place it ln the v 1

type 52.0 feature- space sugg~stlng- a more

mlddle of 'TI

extensive

. v~getatlon coyer comparable to type 52.0' and

- :mlscla351f1cat ion 0 f th-is area, ln the Afr lka Kartenwerk.

The follbwlng l>rellmlnary .. conclu51~~can be reached

110

'.

O"

.,

shown

on the analY315 1n the precedlng pages. ) ,

that 'three band ordInation of ~e It has ba5ed

dens 1 ty

permits:

1) the identificatIon of specifIe feature 5paces \oi1 thln the ternary d iagràm for each 0 f ' the ~egetat 1 on types.

been

data

11) the demonstration of regi6nal dif,ferences (eqst/west) . wlthln sorne of the bushland vegetation types. '.', "-" ,,~ 1

1 Il) the detect Ion of poss ible inaccuraci es 1 n the ~o5ition of vegetation bounda17ies shown on the Af·r lka Kartenwerk.

wl th, an and 67.5) types .' of 'the Ir dr'y

..

l ,

l.v) ,the demonstra t Ion that vegeta t Ion types ,evergreen tree component· (ty~e5' 14.0/.2 can be easl.ly dlfferentlated fx:om those composed of thorny plants, on the 'bas 1s season re fl8Ctanc,e data.

~ '. #

7.2.2 BAND RATIOS %RED 'GREEN TRANSHISSlàN

Of Interest ln thls, study 13 the ut 111 ty 1

of band

ratioing u::qng the transmission' data generated ln the,

densltometrlc analysls .• As dlscu~sed ln Section , 5.'3,

Band 7/5 ratloing )s a standaid method for an~lY81ng L~ndsat

data. This ratio ,normal1ze5 t-he effects of 5011 background

.! \ and littcr ln the surface reflectance. The data pre5ente~ ln ,

Figures 7. 2, a to d are eS8ent l-ally Band -7/5 rat 108 and 1 t l s-

" of Interest to dlscover. whether the data 'ln thls for.~, .

provides improved 'separabillty in the signatures of . the

. var,lo,us vegetation types and whether red fllter:green fi,lter ..

scattergraphs can provld~ any add i tlonal information .. about'

the vegetation of the st,udy area. , ,

The scattergraph on whlch aIl the vegetatIon type:s

i)ave been plotted (Figure 7. 2a) shows .conslderable overlap

111

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U

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LU t :JLU ;tU >~ O':U ~w dr= l ... .'W oQ:: LUQ:: Q::-

1

~rv 4.0;---------~--~----~------~--------~------~~_+

3.5

i

J.O"

2.5

2.0

1.0

~

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, ,

. >

. , . ~ltion Typee.

'lU * SHl Il Ul .' . .ll 0 ~.l ,0 ~H ,. Il 01 t x

1 , ,

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1\ l:l

A

Ail , . . l:l , .. A A~ Il

.~ ,-Il ••• • A fl

'C" ... ~:lt.~

... ~? .~~ 't [:J o6l.D

, ". trl " X

~~~ .. ". , , .ô .,. $"

\ - ~-\ /4" , u " .. ~. "II X

',' " 11 " .)(: , " ~

·.BuJhland

,""

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X·

.X X ,,'

,-Ev.ru,...n forfit

,X X

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O.O .. ~~~~~~~~~~~~~~~~~~~~~~~~~ Q.O 0.5 1.0 1.5, 2.0 2.5 3.0 3.'5 4. O'

GREEN f t,UER, V HUE s:~ .. Uy , ..

.. ~ .. increo:!~ng -- RED REFLECTANCE - de-creo:!mq

- "

" , ." FI GURt 7. 2d RED; GJ~~EN FI LTER (1 R; RED· REFLEc;TANCE)' SCATTERGRAPH

FOR ALL VEGETATION TYPES IN THE I1A.RALAL TRANSECT LANOSAT SCENE 2062~010S2 !HAkCH 25, 19751

, , <,

112' "

"

r, , !

·' , ,

1

ln the central space. The ve~tice5 of the data point

concentrâtlon are def~ned by the v~lu~3 recorded -for lav~,

-bu~land and, forest. The relative location ,of the feature

spaces of each of the vegetation types match those of the

ternary dlagrams however" the exclusion of the blue fllter

data (gFeen rcflectance) does result in a somewhat clearer 1

segregation. For example the separation of 3ubsets A/B and

CID (Figures 7.2 band c).

The Ipcatlons of the anomalous sample cells 140, 139~

149, 170 and 252 are shown' 1 n \ Figure 7. 2d . l ~ appears that

cell 140 15 more clo5e1y a5soclated wi th tYl?e 67.5 da ta

potnts than with type 64.1. ~ample c~ll 110 appe~rs to have

more ln common \Vith the type 67.5 c1uste'r thao wlth type

14.0./ . 2 .. The considerable separat ion of çe 11 252 from other .

type 14.0/.2 data point~ confirms its tr anai t ional

(ecotonal) character. , ,

The regional 'subdivision in the data sets for

" vegetation types 51.0 and 52.Q that was noted abovc also

appears in the 5cattergraphs. However, the scattergraphe ,

al~o~ a clearer deflnltlon of the p051t~on of the boundary.-

In Figur.e-7.2c it can be. se en that a definite .6cparatlon of

subsets C and D occurs at a red denslty value of 2.1. If

thls value ,15 uaed as the ,eut-off 11m1 t between the ea::stern

and western subsets of data, It i3 apparent tha~ sample

ce11s 1'91 and 211 clearly belong to the type "5 east~in

reglon, which corresponds to, thelr geographlcal position in

the transect. In the casé of the data for type 51.0

'veget~tlon, the' reglonal boundary agaln OCCUl5 at a red

113

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., 0 " t. , ~ .. v \ ~~ " v ... ~ .. .. - • ,r U 2 5 -""'1.' 1 2 ~

..,1 -t, '\ A ~ ~ " ..., . ~ ~ ~tj ."tIf .. :/IU

:) w ",0 :.t':i ~ ..

>~ ,. :-104 • ~-, -' -<

0:1- ;:),ou w~ 2 0 -. -:- .. ...... w 2 0 1~1,211~~ .r..; u :de.: "'-'''

f.~'" ......... ;~ Olt' B :.

l.Jlt' . ..... 0: 0:- cr-

I f. '.' C' ' 1 5 0- 5 '.

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~ li !: , 1.0 1.0 1.

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0,5 0.5 " h", )-

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" 1 ~"'T""""""""'r" l"

0,0 0.5 1.0 1.5 2.0 2 5 J.O J 5 4.0 0.0 0.5 1.0 I.S 2,0

GREEN FlUER V l.LUE GREEN FI LT ER V

\lIcreo"f'lQ - REO RE~'lECTANCE - decreo:l1nQ - Increo,lng - qED RErL~C'A·.' ;- ,

FIOVIIE 7.2b RED:OREEH FILTER ( IR :REO REFLECTANCE) SCATTtRG~APH FIOVRf: 7. 2c RED: GREEN FIl.TER (1 R: RED RI FOR VIGET,A TI ON TlrPE 51. 0 FOR vtGETAT l'ON TYPE S 2.0

-/ ... < '!-).. ..

,

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A, ". ~ .. ... ... .. j

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0'

w \' ( c , " ..

t. :!~ r,.l 0

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~ .:. r t 2.5 ~ ~

~ w a .;1&0 :. ::>w " ocP [] ~ ..

:i.~ " e ~- --' • 0 _ x 170 > ... 0::>- []

- Il 1~1,211~~ w<'> " ..... ~ 2.0 III- l( l(

0 :!de: El 140 • Il''' "- w J -. x177 :. 00:: J • j-,' x25Z ""OC j( 0::- 0 14~ UO J( ,

0' 1,.5 c , il 0

" " u =

, . 1.0 , .. ~ '~ " .. ,

-.

0.5 h!'o

" 'f" 0.0 ·""T' . 5 2.0 2-5 ).0 3 5 ~,(, .1

0.0 0.5 1.0 1.5 2.0 2.5 J.O 3.5 4.0

EEN FI LT ER VA~ LJE GREEN FlL TER VALUE qED RErL~C'A·.CE - decreo~'''''Q - tncreo"nQ - RED REf"lECTANCE - decreo'ln~ -,

ER ( 1 R : RED REFLECTANCE) SCATTERGRAPH FIGURE 7. 2d RID:GREEH FILTER (IR:REO ,R&FLECTANCE) SCATTE;RGRAPH

S 2.0 .

FOR VEGItT ~TlON TYPES 41....f. 64.1, 67. S, 14.01. Z. 52.,1 TYPE

.. "

(

.' .

i... ri'

l,

\ . . .

, .'

"

denslty value of- 2.1. If thls boundary ln the scattergraph

1:5 accepted then the anomalous cells 104 and 122, which

f5hbwed afflnlty wlth the data from the. ty,pe's ea~tern

reglon, clearly belong in subset A, the western reglonal •

From this discussion 1 t may be concluded that, in

genera l, the ternar y dlagram provldes resul ts comparable to

those ac1Ùeved us i ng the IR: red scattergraph approa9h ..

However, the ~cattergraph does seem to offer sorne further

clarification of the reg,Ional anomal les occurlng ln sorne

veget~tlon types.

'r •

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olt IJ

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7.3 SEASONAL CHANOg IN THE VEGETATION COygR

- The seasonal-changes that ~ccur ln the vegetation of a

semi-arid area are of special Interest te the resource ,-analyst, the. plant speclallst and the reg~onal planner.

, Information about the spatial pattern of phenologlcal events

15 of particular stgnl.f,icance to the plant geographer -,

becCluse l t supplements the sornewhat llmi ted deta lIa that are

aval1ablè on small-scale vegetation map~.

As discussed in Sections 4.,2 and 5.2, the vegetation of

the Haraial transec~ undergoes distinct phenological changes-­

in response to the ànnual precipitation reglrne. The pattern

of ralnfall distribution and the t-Irning of the 'on!3ct· and,

cessation of the rains have a direct effect, on yegetatlon

growth and there arc corrcspording- changes ln the surface Q

reflectivity (Figure ~.3).· From the details of anbecedent

rainf-all' conditions (Figure 2.7 and Table 6:'3), lt can be

seen that the Landsàt image of Septcmber 21 (Plate 2)

provld,es êI. good ,repre3enta,tion of the wet seÇlson condition'

for the west and central sèct6rs of the ,transeèt. ,The bright

'magenta areas lndlcate' h 19h reflectance from

photo3ynthetlcally active vegetation. The orange coloration.

apparent in the eastern 3ector can be attrlbuted to the - , ,

I1nqerlng effects of the "long" rains of Aprll and Hay:

The apparent phenological" changes in' each, of the c

yegetatlon typ'es 1,1111 be examlned wl th 'the' ald , ~

of ternaty

d.1aqrams and' 'IR: red scattergrapha constructed from the

Match and Septe~er dath. Since thé vet 8eason conditions

prevall only ln the west -and- central sections of the \

116 l' l

...

II!.

(

. '

"

transect, the dlscu5310n 15 I1mlted to the vegetat ion type~

located ln these areas (sample celis 1 to 180

appx:oximately two-th 1 rds 0 f the, full data set) • The data set

lilustratlng seasonal change ls I1sted ln Appendlx D.

7.3.1 VEGETATION COLOUR SHIFTS ASSOCIATED WITH SEASONAL " .. , CHANGE:

The data for septernb~r 2;1, ,"19:5 d1splay the effects of

"greenlng up" ln the west and centdU sectars of the Haralal

transect. There ls' a slgnlf1cant reductlon ·1n red Cgr~,en

fllter data) and green (blue fllter data) reflectance, while

IR réfiectance (red f lIter data) .remalns almost unchanged' ,

(Figure 7.3). This change ls also apparent ln ihe tern~ry

dlagrams (FIgures 7.4 a to d). The calour splft from March

ta September involves a dlsplacement af the a li g'nme nt of

data points towards hlgher \bIue and lawer %green values,

whlch 1ndlcate an Increasc ln the green waveiength

, ,,,efl~ctance and a reductlon in the red wavelength

reflectance (Flgura'7.4a). The range "of 'red transm1s~lon

1, values ln September ~s gui te wlde (25-98%), but there 1s a

grea~er concehtrat~on at the hlgher values. The range ln the

\green values ls somewhat x:educed (1-49\), whlle that of the "

'blue ls s11ghtly ex~a~ded (1-33\),' ~he grassland and

bU8hland :vegetatlon types exhlblt the greatest change~'

between September and March ln the1I spectral signatures'.'

Bach, of the 'signatures will be examlnèd Individually

followlng the ~equerice us~d above in the discussion of the

"arch \tran8ml~81on data.

117

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. , .aPT."BIR '21, '1975

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>-0 z: 1&1 ::;,

<. 'i ~ ,ra..,

" VISUAL FILTER

..

..- ~creuin. TOTAL REP'LECTANCE decreuÎll. , .....

...... ,increuing REFLECTANCE IR À decreuing , .....

GREEN FlLTER

..- increuin, REFLECTANC~ RED À decnuing .....

BLUE FIL TER

, ,

.- 'j,nue~in. REFLEC:rANCE GREEN" decreuÎD" ..... "'. ,'DIFFUSE 'DENSITY

,HISTOGRAMf' OF DtFFUE DENSITY DATA OBTAINED FROM LANDSAT SCENES OF THE HMALAI.. TRANSECT FOR HARCH 25, 1975 AND SIPTEHBER 21, 1975 ..

118

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-........... • • UA .... '-~' .. \ .. -. '" \

... •

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r..1 l' *' MARCH 25, 1975

--.lU A SPii •• 1I.wn ~! 1 ~' / , ., 1 0 1\. 1 0 .l7 " If ~ \

14 " )(

•

""

.. .. " • Il .. ~ RED 'tRANSMISSION (GROUNDREFLECTANCE.IN II!- A)

, "

FIGURE, T: 4a

\TRANSHl S~ION- .:rERNARY OtAGRAMS' OF ""WI'rHrN CATEGORt" 'DATA FROM S'AMPLE CELLS 1"-180 FOR THE MARALAL TRANSECT,

. FR'ÛM LANDSAT SCENES 2062-07052 (MARCH 25,- 19.75) " AND 2242-0~041 (~EPTEM~ER' 21, 1975)

'. ',<-

1 ''0 , ' ,Y

/

" 119

, , "

, ., ., ") "

. . .

\ ,

, .

! ..

"

In September the feature space for type 14.0 ,vegetation

'has essentially the sarne shape and occupies the same

positiçn in the ternary diagram as its March counterpart

~(Figure 7.4b). Transmission data ire concentrated above the

~ 9.5% red, value. The persistent high IR reflectance from type

"

, . 14.0 15 consistent' \,with its' classificatIon as evergreen,

01) montane forest. Even sample cell 170, previously somewhat

/,

anomalous, now exhibits considerable increased IR

reflectance (15% change). However, the arguments 1 for

considering ~his sample cell either ectonal "or (more likely, a 4 ~,- 1

representative of vegetation type,67.S are ~upported by ~his

" seasonal shift which corresponds ta the cha~ges experienced

by other . type 67.S'cells (increases in %red values of

between 8 and 25%). The change table (Appendix D) indicates

that the ~ncreases in transmission in the'%red categ6ry are

counterbalanced by decreases in the %green (red reflectance)

and the %blue (green reflectance) categories.

The increased IR reflectanc~ of vegetation type 67.5 in

September is, graphicalpy displayed in Figure 7. 4b by th~

shift in the position of the feature space. The increased IR

ref1ectance is attributed ta phenological changés in the

grourtd COyer which is mainly the perennial grass Theméda

tr iancha. The fav6urable conditions , ,

of the wet season

result in a flush of new growth, the effects of which

continue to per~ist into September. High IR reflectance

, characterises both the forest and grassland components. The

C~àssification of sample cells 139 and 149 as belonging >-Î vegetation type 67.5 was previously quest:ion.ed. N~w, i t is

120

.-,

1

1

Il

o

• C

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'.

14n

41l 0 AllO,

AJA - • If ,,/1 X

" 1~9

..

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o

a _

149. 097,91

000

,-

.. " .. '-" RElTTRANS'I>4ISSION

, \

"

, !EPTEIoCIlt:1I n. leu ,>,

• " " RED TRANSMISSION

D

o

D a, Sl:PTEWIlEIl al. If" . '

~~~~~----~------~\-----------­• • /l'

" IIf:P TRAfl5MISSION

,f

121

"

, 1

- -' ,

.. 41

-.

- -"

M'

1(:ROIII'I1) REFLECTAI'ICE IN IR ,\,1

" ..

Io(AIICH %l, leU,

"

, '

" Sm~BI:R U. ""

" " RED TRANSMISSION

FIGURE 7. 4b

\TRANSMISSION TERlfARY DIAGRAKS, /

OF ,DATA FROM S'AHPCE CELLS 1-180' .FOR VÉGETATION rYPES 67.5, 64.1, 41.2 AND 14.Q

"

FOR ,HARCJ{ 25 AND S~PTEHBER 21-1 1975

'.

.. ,

/

-0 .,

seen that these cells experience the same shift as other

_ type 67.5 cells which indicates that they are correctly

, classif ied.

There ls only one cell (no. 140) in the phenological

change data set for the vegetation ,type 64.1.

classification Qf this cell was questioned in the analysts

of thè' dry seas.on· data. ,: As can bé seen ,from Figtue 7/. 4b,

this cell mimiçs tfie reflectan~e changes experienced by type

67.5 cells with an increase of 25 percentage units in' 'its

%red category. It ls very likely that the Acacia-Themeda " caver of vegetation type 64~1 would behave in this way,

showing a reflectan~e increase in the IR wavelengths in the

,wet season when there ~ould be ~ vegetation flush in botq \

components~ Other sample cells of vegetation type 64.1 are

loca'ted in the eastern sector of the transect and so there

is no way of deciding wbether t~e phenological Chilll13CS t'hat .

ar~ exhibited would be more readily explai~ed ,if the sampl~

wa~ treated as vegetation type 67.5 rather than a 64.1, ,as , ,

sug~ested in the sec~ion deallng with dry season condi~ions~ ,

'The ,answer to this guestio.n i5 deferred to a later - section

whère the ecotbnal data is analyse'd. / ,

- 1

• ,The feature space, for vegetation ,type 41.2 shows a

definite shift in the ternary diagram between March and

'September (Figùi"e 7.4b). There are significant increases

(25-36 percen,tage uni ts) ,in the red . transmission values,

with similar decreases in the %green. , ,

The relativè position . , or the- sample cells one ,to another' remain's unchanged betw'een

122

" "

1

- 1

•

, '.

( 4-

, "

o ... ,

, ,

" March and September. Those cells which exhibi ted 'the highèst .. reflèctance in March continue to' do so in September. Thè .

increase in refiectance in September is overal.l IR .

att,ributed. to the yegetative response ta the wet season. \:The J,

dense stands of thorny plants and shrtibs, as wetL -as th~

areas of grass', àre nO\-1 aIl photosynt,hetically, active. "

The positi.on of' the feature spaces' of the ~ bus,hland

v~getation types (51..0 and 52.0) 'are shi fted '. signi f iqant ly . , , ,

in the ,ternàry diagram betweÊm Marcn and Spetember

(,Figu'res 7·: 4c ,and 7. 4d). ,These t~o ve~etàtion' ~ypes registe,r

the great'est increases in tred ,tçansmission and th'e " i'argest

decreases fn tgreen transmission of aIl, the vegetation typ~s , , '

in the area. Increases of up to 42" percentage ur.its in the "

red. -transmission d~ta and decreases of up 't,o 36" percenta<ge ~ ...! l ~ 1

units in the 'green da~a ~ere ~Lecorded'(Appendi~ D)~ ChanQes

in the %blue transmis~:;iàn are 'small, ,varyi'ng between +14 and , , ., . -8 percentage units. However, an examinqtion of the feature

spaces revealed - tha t 'the pnenological ~

response' in both

vegetation types is selectJ ve. Sorne area.s display a much ,

-more signi f.icànt "change than other s""

Of the 63' sample, cell:s which cover veg'etation type .,.

, 51. 0, twe.nty-two. were tagged' 'as displaying _' , an ., .

"iQsignificant" change in tJ1eir transmission data between

'. March ~nd Septe~ber. (For analysis purposes, an increase or ,

decrease of up . ta 15 percent.q.ge·~ uni ts is, considered as

"insignificant" for the bushland vegetation, types) . These q

are located on the step-faul te'(} scarps of the Rift

~ ,,' "Jo 123

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~ RED TRANSMIC;SION 11~1l0IlN\) R~:fLr.(,TA"l'E IN IR II

. -

FIGURE 7. 4c

" , MA,Hf Il J'. IQH

tCP'rWau Il . ...,.

11 "

\TRANSHISS~ON TERNARY DIAGRAHS OF DATA FROM SAHPLE'CELLS 1-180 'FOR VEGETATION TYPE 51.0 FOR HARCH 25 AND SEPTEMBER 21, 1975 . "

( ,1 ,

1"

124

",

'.

rU "

'\

. ,

o

Valley~s western face, along the northern margins of the

transect, or on the Suare Pla~ns just north of the Rarisia \ 1

Bills * (Figures 2.2 and 3.1) . In'March, cells Il ta III \

and cell 173 plot at the highest %green end of the feature

space, whi le 'sampl~ cells 121 to 176 (excluding cell 173) ':J

are found at the highest %red end of the feature space. The

relative feature space locations of these cells remain

basically uochanged between the two image dates. There' are

two phenological scenarios which can be used to explain

these differences.

For the sample cells which registered insign~ficant

change between March and September, t~e data suggest that

the areas covered by the se cells have a very lf.

sparse

,vegetative cover, since they do not exhibit the increased IR

reflectance apparent in other adjacent cells.' Their

signature i5 one of persistent low IR reflectance and high

'. red reflectance. The magenta hues indicative of active Co

vegetàtion gro_wth are not found on ,ei ther of the Landsat

images at these ce~l locations. The pr,esistence 9f high red

- reflectance (%green transmission) in September suggests that f

there is a considerable bare surface component in the area

covered by t~ese cells.

Airphoto coverage is available for sample cells 22 and

173 ând the photos show that much of the area covered by

,cell ~ is bare. From photo analysis the cover of woody

species was estimated at 30% however, th~s 15 scattered in

------------------------~--------~----~---------------------, .. These are cells: Il, -13, 15,18,21,22, 24,101, Ill, 121, 122, 153-155, 163-166, 173-176.

125

\

one 1 half of tbe cell and confined to a watercourse in the

other half. A similar woody component estimate (32%) was-

made for cell 173. ' However, here there,is a .more even , ,

scatter of bushes and' shrubs throughout the area. This may >1 '

account for its slightly higher IR and lower red reflectance

values in both Landsat images as compared with c&11' ~2.,

" Wetter surface ,conditions would account for the slight'

"

t

,decreases in the %green anô the slight increases. in the

\biue valùes seen in the transmission data.

For type 51.0 vegetation located in the north and

northeast sections o'f the transe~t (sample cells 121-17"6>,

a very different scenario ls suggested. In March the

reflectance fror.1 this' area gives r,ise to high~r %red return'S

'than is the case for the other area of vegetation type 51.0. , .

This suggests that there is a signi~icant woody component ,in

bhe 'vegetation cover. Examinatiori of the airphotos avai1-able

for samp1e ce1ls 155 and 165 confirms that.a denser woody

oompon'ent does exist in these areas wi th,approximately 4,5-

50% cover c1osure. It consists of both trees and bushes,. ~

compared with the more limited bush and shrub caver seen. in

,cells of vegetation type 51.0 locat~d in the western sector

of the transect. Assuming that the'vegetation of sample'

cells 155 and 165 i5 representative of that for ~ost of' the

area, one would expect considerable increases in their IR

- ref1eç~ance with the onset of wet season conditions. ' Sinee

this is'not the case in ~975, one is led to the conelusion~

that the rains experienced in the west and central sectors

of the transect did not extend f~rther east than the Lopet

126 ','

,1

" Plateau and th~. Kar is ia Bills. Th'e area of type. 51.0

, . bushland just nor~h of the Karisla Hills appea~s .tp lie

, -,.within the eatern sector,'s rainfp.ll' regime.·· Th-e ~ingering.

effect,s of the "~ong" rai~~; are responsible .for 'the slight

inéreases in IR reflectance exhi~ited oy these cells. \ ;

The· tiansmission data for sample cell~ eE vegetation

type ,51. 0 which exhibit,ed ,IlS igni.t: icant" ,

change ·in ,

reflactance betweèn' March and September also 'exhibit

regional variation. In March the area of typ~ ,51.0 •

vegetation on the western side o~ the Rift Valley exhibits // ,.

very low %red transmission (i.e. yeri limited IR ret,urns). (

is high, \ ),

~owever, the %green transmissiQn (red return)

'~ndicating considerable bare ground. . I~ September the 1

situation i5 reversed. There Is consideiable IR reflecta\ce

, ba re . 9 roupd and a corresponding reduction in the

r~flectancé. This response is consi~tent'w~f~ the premis~

that, most' of the vegetation in the area. was dor'mant in

"March.' but in September the bushes and annual grasses ware

, in active growth as a result of the rains. , ... ~ "-

Thé area of type 5~.O vegetatio~ ~ocated on the eastern

side' of the Rift Valley, on the step-faulted scarps leading

up t6 the Lopet Plateau, also d1.splays increased, IR ~nd

reduced red reflectance in September. ~owever, the shift in

po;3ition of the transmission data from MarGh to September l, ) _, ~

, suggests that, the bushland cover in the area east 'of . . the

Rift Valley 15 9 reater than. that of the t'ype 51.0 - area

Yocated to the west.

Airpho'to coverage was avai1able ror sorne of, the sample

- '127

, ,

"

"

1

(;

cells in this eastern sector. These photos indicate that the

wood.y componentJ which 15 qU'ite dense in parts, contributes

51-70% pf the cover of these cell~. Trees make up a

considerable proportion of this woody c6mponent. The're i9 a

considerable difference between these areas and the type

51 ~ 0 vegetation occur'renèe west of the Rift Valley where the

airphotos suggest that thete is a greater proportion of

annuals and perennials, as sugg~sted above. If this is the

case then one can conclude that an annual component does not

.. ,occur ln those sample cells that display no si.gnificant , '

<

phenological changes in-their reflectance data and have a

woody component of 1ess than 30%. This confirms that

reflectance from an exposed soil s~rface dominates the çata

for cells Il, 13, 15, 18, 21, 22, 24, 101, and Ill.

The seasonal reflectance changes in vegetation type

52.0 are comparab1e to those of type 51. O. There is- a "

distinct shi ft in the feature space between March and

September 1975,{Figure 7.4d). In March the data, cluster at

the' highest- %green transmission values. Thus., this

vegetation type exhibits the lowest IR reflectance-level of

any cover type in the transect (Figure 7.4a). In pontrast,

in September the're· are significant increases in - the IR

reflectance. However, even in Sèptember the IR reflectance

,(\red . transmission) is ge~e,Ially lower than for type 51.0

vegetation. This response is consistent with the more 'open /

bush land nature of th~ type 52.0 cover.

There .are 36 data points in the type 52.0 f~ature,

128 .

('

"

,

, "

,)

" "-

-, , '

,6 .... 6 •• 6,

• 6 , , • 6 • ..

6 ~

.< .. .. .. .. .. ... .. ·6 .. .. -a.

.,

'" w ,.

r

-' t'

"

"

"

, ,

"

"

.. '-,

'.

'.

. "

.. ..

, 1

.... ' • •• • ....

..-.

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.. '

•

A ..

1 •

•

,-. 1 Cflllllr> Il IH'FI F:('TA NCf. IN III II

FIGURE 7.4d

, , MA RCI/ 2$, uns

M'fi .le ......

. !

'1

t,

'TRANSMIssioN TERNARY DIAGRAMS ,OF DATA FROM SAMPLE ÇELLS 1-1·80, FOR VEGETATION TYP-ES' 52'.0 AND 52.). FOR HARCH 25 AND S~PTEHB~B 21, .1975, '.

. , , ,

129

!

a

JI,

0

space. The data are seen to divide inte two groups-

'exhibit1ng significant >15% increase in ~~d transmi~siôn}

or insignificant ( <15~} change in their r~sponge between

March 'and September. The twenty sample cells, ex'hibiting

significant phenological change are Iocated on-the 90uthern

,

and eastern slopes of the Silali caldera *, while those

eXhibiting' inSig'ificant change are' l~cated to the west of

Silall -in the Suguta ~iver valley and also to the north of

the caldera. This lack of response seems.to indicate that

there is a çansiderable bare surface companent in thesé r

areas.

The unchanged reflectance situation exhibited by sample

cells 151,,161 and 171 can be attributed to their location

at 'the northern margins of thè Suare Plal.ns where the r-a.,ins

did not penetrate i~ 1975.

The respanse ,of triose sample cells which exhibited

significant seasonal change in the w~t season ~s comparable

to that of vegetation :type 5l.b on the west side of the Rift

Valley, which suggests- that there is a signif l'cant annual ~

vegetative element on Silali's soutnern and eastern slopes4

From the ana'lysis, ft. seems fc3:irly c~rtain that the

bushfand veg~tation types (51.0 and 52.0) exhibit, a , ,

selective'phenologica'l response in the' wet season because of

(i) variations in the woody tomponent and (ii) the presence, " !

or absence of annual vegetation (Table,7.1). For exampJe,

-~----~-----------------------~--------------~--------------

* These are cells: 30, 37-39, 46-50,' 55-~O, 65-68, 72.

'" , -

j -130 \ "

--.... - d

.... ~\ l ",

" 0 , ,-

"

c . ,

. "TABLE 7.1

" . '- " /

SUHHARY OF DENSITOMETRIC DATA FOR THE-VÀtho.ûs', 'VEGET'ATroN TYPES OF THE MARALAL TRANSECT OBTAINED FROM LANDSÂT SCÉNES

2062-07052 (HARCH 25, 1975) AND 2242-07041 CSEPTEHBER 21, 1975) , -___ . _____ ... _____ ... l_~. _______ .... __ .,.. ___ .. ______ .......... ___ ... __ .. __ ........ ____ .- _____ .. ____ ...... _._ ..... _____ -; ______________ .. __ ,.,ArrOI DISCII PI 101 LOClflOI DR! SIiSOI Rr SWOI

fJPI " YUISIfUnO! TRUSlUSSJOI \l1D \GIIII \eLUI '\'RID 'GlIal \Bf,tJ1

, , _________________________ .. _____________________________ . _____ ~----~--~----~-J .. _~-------_________ ~-____

14.1 Imgteel 'omt Saant. ud ) '2 ( 5 ('5 ), 91 ( 3 ( ) larlsia Ulls -

14,2 I,elqtee. 'orest lIathm lange 91-" ( 1 ' (,4 '10 DAn (lOfe open vin

~Olt 9[.lsl.ld)

61.5 tlollhae lQ.rest hanta Ulls ":"11 9-15 4-1 ' ,H-SI .' ',( 5 ( 4 ild 'onhu "

- Cuulbd ' '

U.l tlollt.le GrasslaDd 1t1~1 Pllteau 12 2% , n ~ 1 vLt~ t~O[1 -heu .

'.alld shâbs Il Ponlet! Plill. 5'-U )}-lt , ' . " r '10 ~1f1

41.2 Duse tbon} step-fnlted fi-l. 21-48 f·u -11-'7 1-15 2-U pliits and s~nbs ScatP5 west of vu. SOte glaSS Lorogl Plateal iDdthorntreu D

51.' , LlguOis tbon >3" woody cover 35-U 51-57 ,11-21 2'-47 ll~4~ 20-27

••• ' pluts ald •• ch balt ground 52.' , .ucnlnh, /,

'. vm ulnly ,31-58' woody cover 26-43 44-57 12·21 44-78 ,1'2-40 1HZ ~ ... Il g[.ues large aRltal cOlpô~eDt

51." 51:1'\ voot} coveI 43-14 20-45 '-1~ 'lO-~6 . 2-23 Ha SOie" allilals ,

- -, lAID' tell 42 RUt valle, 33 5. 11 35 45 lO

un Cd1- ,~ lift Ville7 11 )3 St 20 24, Si. _______ ~_~~ __ ~ _________ ._k ___ • _________ ~_ ..• ~~ _____ . ______ ~ __ ~~_._~~_~.~ ____ ~ _____ ~ ____ ~ ___ ~. ____ ~.~. ___

, . ", , " ,

~. , .)

< ,

, .

131 , , ~ .. .. l'';

, "f 1 ; ... '. " / l' <I-te

" " -

.' .

, '.

"

, ,

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l'

,"

areas wi th a very sparse vegetative cover and much bare

ground' exhibit low %red trans~ission (~R reflectance) and

hig~ %green transmission (red rèflectance) in March and

. continue to do so in September, displaying insignificant . '-

change ~n their reflecta'nce data. Such areas were estimated

to have a woody· cover· of 30% or less and a very ,1 lmi ted

'cover of annuals. Areas of bushland type 51.0 which

"iesponded in th~s way are located along the step-faulted

- scarps on the western face 'of the R~ft Valley or along the' .

, northern margins ~f the transect, whi le those of \ bushlaJ'ld )

52.0 are found té the north of the Silal i caldera and

in the Sugu ta Ri ver valleY,\J

Those areas of bushland which exhibited considerable' '.1

change in their' reflectance between the wet and dry' season:;3

were found to have a denser vegetative cover. Areas which

extii'bited signi"ficant IR and relatively low red reflectance

in the dry season and higher IR with much reduced' red

reflectance in the w~t season wer~ estimated io hive a woody

, component of 51 to 70%. Areas" wi th this response are found

.'

on t:;he step-faul ted sc-arps on the eastern' face of the' Ri f,t

Valley leading up to the Lopet Plateau. Bushlahd areas whièh 1

19w IR and high ~ed ~eflectance in March with exhibited 1

increas,ed IR and, red~ced J red r~fl.ec~a'nce in September were

estimatèd ta have a woody cover of between 30' and 50% w~ th a

relatively large componènt of, . annu,als. Tqese ar'eas are ,

looated ,west of the Rift Valley above the step-fau,lte'd

scarps and on Silali 's southèrn and eastern slopes.

"

. )

132

, , '

.'

o '

-'

o

"

Sample cells 62 and 42 (vegetation type 5~.1) show

little chàn~e between March and Septernber (Figure 7.4d).

Sample celi 62 15 essentially unvegetated with a" surface' ,of . , , -

recent ,basaIt lava.' In the case of sample celi . 42, ,which

exhibits one of the highest %g:reen transmisé.ion values' (réd

r'etlectance) wi th no change f,r~m March to Sep'tember 1975, i t

,', . can be ded~ced tha t this i9, also ,an area of bare ground, , ,

-.. ' proi?ab~y sand. If this i5' the case then' sample cells, 35., 43,

,53 and 54, which have similar reflectance characteristics,

may aisp be unvegetated and sand-covered. This would account

for their' continued greenish appearance on the September

image. . "

, , " ln t'his section it has been"sho~n that the 'density data

in "transmission format' 'permi ts a bet ter understandlng of

the phenologica'l changes ,in the semi-ar id vegetation of the ;--0,

l '

Maralal tr~nsect. Further, when the da ta are interpreted

.. ' wi th referenc~ to 'the a~ rphoto coverage of the area,

,..

'"

" specifie factors can be identified whiéh eXp'lain the

\!ar iations "in the, spectr'aJ: signatures of 'the ,bu$hland'

vegetfltion types.

. ' '7)

'-

, . , .1 •

• 1 -. , ' .. J , ,

.. '. k

, . . " '. , '

~ ....... " , ' , .

. ,

" ,

.... l' ...

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',133'

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1 ". 1 \ -

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7.3.2 , .

In

A COHPARISON -OF %RED : iGREEN TRANSMISSION DATA FOR HARCH, 25 "AND SEPTEHBE,R, 2). r ' 197_5:

Section 7.2.2, . the IR~ red ~, transmlss Ion . , , .

-ratIos

provlded sorne addl tlonal information about the dry ~eason

~pectral " ,

signa'tures of sevel;a 1 of the vegetat 1 on types , " 1 n " . . . '".. , ,

\ t;hé' transect;·, and' 3.0 _ 1 t , .... was decideq to use, same , .

" procedure '. ln an a ttemp-t. to obtaln suppl..ementa ry deta 11 -',

" ' , '

relatlng to phenological cha~ge .. Toe ratio plot~" whlch

d,ispla'y qnly the densi tometr lc data for' sample ce.Us l ' to < /.

1&9, are prf!sent,ed 1 n FI gures 7.5 a to d. . ,..

The plot ,for.. aIl vege~à,tian types (F'igure 7. S.a) shows "

qui t~' cieatly the reduGt 1 o'n ln' red r.e f lectance ,ln septembe-r. ", r , wltl1' the 'entl.re data set shiftlng ,ço the"'rlght~, 'l'here 13 a

, . . fllter values, sllgnt but less dramatlc change. ln' the red

O',sùggès.ting an 'increêlse in -IR re flectance . • 1 • \,

-When the for part i cular vegeta tIan. types , '

are , ,

'. '\"e'Ç~mlned .~eparàte ly (~lgures 7. 5b to d >" the "'5am~ sh 1ft l'n

the red r~flectance clearly apparent, Ind'lcatlng a'n " ,

" ' \

'over,§lll !ncrease ln less- bare

ground exposed t'a, the Landsàt 'sensors. H1gher:' den~i ty' ",

" . ~ ,

readlnqs ln september ln il p~rtlcular. fUt~r category , .

Indlcate 'reduced 'ref:leçtance ln 'that wavelength. 'Thus, hoth , ~

the bushland types. (51.1> and 52.0) exhLbit r,~dueed red

- f ' ,'"

reflect~nce" in aU the sampllng, cells.· However, Clnly seve~ , .-

~ , of the type' 51;0 * and ten of- t'he_type? 52~O sample cells '**

\' ~ • '").- ~ "" \ b

display .any'lncrease ln thelr' IR reflectance (decréarses l,n, , ; . ' ,

-----------------~--------------~---------------------------. ~ • 01 , ( 1 * 51.·O'cells:-4, 5,'S, 1022,123,-133, 167. ~. '. ** 52.0 c~nl:5: 38, ..47,,~8,'49, 55, ~~.8, 59,~'65" 66, &7 •

• <

1 J

. , 134

, .

..

" .

- "

,\

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:

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" 1 , - /-

4.0~------~----------------~--------~~---------.~.--.~.~

8EPTENBER 21. 1175- "

'j

3.5 "-, . "1,, !

~ "

"

3.0

, '

2.0 , ...... "

o • •

1 • S '.'

/"

1 .0

o.'s " . , ,

~\

, (,'. ,

O . -' . ',' ,\. ',' • j. " '. 4", () • .' - • l ' - ~""":""""'TTn""""'''''''''''..........r "~-;"T"t' .... t 1" """ ft 'j"'. fI' t ft fi ~ •••• , .. ,., ,_, 'Ji .1 •• "" •.•• , f' r"'T""'rt ............ i"" 'T1'

0:.0 O.~ ""';-0. 1.5 2.0 ~.S 3.0 3.5 4·0

GREEN FIlTER VALUE "

\ , "

....... \' .-

'. " , ,

. "

,.t) 1 , 1 - "

./

(

"

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~

"

44.

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.li -,

t J\ 0\ c iii 0 CI> 1-U CI>

"U '2?. , lUIt :;::IlW

;il~ >:oc{ .cE ~ ,~~ 4E •• ~,lt '-O~ UuU ~ «-

~ 9' 11 •• 'c 'iii .0

Q) L.

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J ' 11.

0 .. ,',

MARCH 25, 1975-­

SEPTEMBER Il., .~75

. ' ~I

. .~ ,

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~11l

Sl Il

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Hl f>4 ,

61 \'

'.0/1

, "

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A,

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'0 ,. X

, ' .

, , .. "

~ .. @ _ .. ~ ~~Q ~.,~

l' ·~"'fH:,l~~ ~M .. ~

'---'

; . - increasing - RED REFLË~TAN(:E - decreo5Jng -

',. 1

..

~·.V

, ' 1

F J GURE, 7 ~ ~j3 RED: GREEN FI LTER (l R: RED REFLECTANCE) SCATTERGRAPH:, OF, "WITHIN CATEGO~Y" DATA FROM SAHPLE CELLS 1-1130 FOR AlL VEGETAT~ON TYPES IN THE HARALAL TRA~SECT

, FOR HARCH 25 AND SEPTEH'BER 21, 1975

, j

135

, ,

" ,

red fil ter, density values) in September.

'A p~ssible explanj:ltion for ,this appare~t anomaly lies

in the' fact that, the fi,rst flush of, new' gr,owth which oceurs

with the rains has already passed by September 21, 1975. \

Thus , a1though the ~urface is ,!egetated, the leaf anç} grass

cover has passed its peak growth stage, and 'IR refl-ectance ïs

only, moderate.

-In ,the, "f filaI plot for vegetation types' 52. 1, 41.2,

67 ~ 5, 64.1 and 14.0 ( F.Ï,gure 7. 5d) 1 only the montane

grasslanas (vegeta't ion types' 67.5 and 64.1 ) show both ,a , ' deet:ease in' red re~lectance ànd an incre~se in IR

r,eflectanc~': in:Ucatinq that~.~ 'area.' aètive gr~wth' i.. " still in prog~ess. J

"

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0-; ,

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1 , ~ \ '

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136 \ ',>'

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a.. , 0 &.,1 0:

\\

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<4.0 ~.

SEPTEMBER 21, 1975

('

3.5 \l,

Ç:~ -\

3.0

Q

2.5 ,

\

, .. 2.0

, j " \ .. 1 j 5

1.0

" . , " 0.5

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----~-~--~

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'-1

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'. ' •• • ',' ~ .. .. ' •• + • • • ... " .. . , , ,. • ••• ..... -• .. •• • " .. * • * • • • • .. * • .. • ..

* • ..

'1

'1

. ,

1.

0.' O~ -, - . , . 1 ~ 1._'"' , ....... , ... , ........ .;,., .... , ........ , .... ,."' ............. , ......... ." ..... , ................. ,.,. .......... , .. , ..... , .... r-9 ..... r-9.~ ........ , .......... , , • ..,.. '1 .. ~ ,.... • , • i t , • , • • •• , •• , • 1 ~....n;;""""",

'\

0.0 6.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0'

. ,

, '

, .

GREEN F J L lER V AL UE

,.

l'

,1

---------~----------------------- --- ---------

-,

(.

"

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.• ;O~--------------------------------~--------_+

3.S-

·

t 3.0-,

. en · E. VI

'0 Q) L- · ,u Q)

u

~~ ~~-

2.5-

· ~

,~~ ~lL.

· 2.0--..W 00::, · · WO:: · cr::-:-

-, 01 1.5-c Vi 0 Cl> "-'0 c

, , 1.0-

· · 1 l

" O.S-· · · · ·

0,0": '"

0.0

MARCH 25,1975

SEPTDIBIIl 21. lI75

. \

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, • '1.0

*

, .

-. t. ~

• • ,.. . '''t ' .. • • • .. .' .' -*** ... ,_ L_, _ .~.~ ..

·'·w' \ ~*,i<, "'l ..... ,"'" • ••• . ~. ' .- ...., . ,... .. \ .' .... * '" \ •• " • ...... • 'i " • * *' •• ~~: ' • ... _.- . . .

... ......... ..' *' ...... .... . ...

• '.

" , '

• , ..

• 1

3 .. 0

GREEN -FIt fER Y,ALUE . , -, increosmg - RED REFLECTANCE - decreq!?Jng _

4.0

FIGURE '7.5b RE,D:GREEN FILTER (IR:RED -REFLECTANCE) SCATTERGRAPHS OF 'DATA FRQM SAHPLE CELLf- l ~ 180 FOR VEGETATION

,TYPE 51.0 FOR HARCH 2; AND' SEPTEMBER 21, 1975

137

.'

. ,

.' - LU :::>

~ (k:

~ d ..... Cl lAJ Cl:

"

; ,

,.

4.0

3.5

3.0

2.5

2. ,0

, /

1 .5

1 .0

0.5

. /

,

SEPTEMBER 21, 1975 . , ,

"

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,,'

A,A

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A ' M A À' A,A 4 A A, At

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-0-.0 " !.. i ~"'r"'''''''''T''1'M'11;'''' 1 " .. " r.,.......""··· l'" '''~r'' .. T""9"""r .... '" "1·' .... r:" ..... "1·" ......... .,." ... ,

f

0.0 0.5 1.0 l .5, 2.0 2.5 3.0 3.5 4.0

GREEN flLTER VALUE " , \

, , .. . , ,\

'.

(

,~

,r

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- "

c

4,.0 .... ----------------....,..---------+ , ' MARCH 25, 1975

~ ... ~ '1 ~

SEPTEMBER 21, 1915

, ,~

t , J.O-

0> C VI, 0-Il) L

'0 Il} ,

"0 2.5-lIMII t ::;)W

~~ .

«1-.

~~ 2.0 ... ..... ...J -~ 1&. W ,oœ Wœ ,'" \,1

0:-. , CI' 1..5-~

.q'J

, 0 t> L . , 0 C'

~ " , l .0-"

• \,

0·5-

.

. ~I.! 0.0-

1 , 1 1 J ' t 1 1

0.0 0.5 1.0 1 .5 2.0 2.5 3.0 , ,3.5 4.0

GREEN fllTER VA~U~ - lncreoslng - RED REf"LECTANC( - deàeasrng _

, .

1~ FIGURE 7.5c RED:GREEN FILTER (IR :RED REFL'ECTANCE) SCATTERGRAPHS

OF DATA FROM' SAMPLE CELLS 1 - 160 FOR VEGETATION' , , TYPE 52.0 FOR MARCH 25 AND SEPTEl1BER 21,' 191'5

13ti

"

,-

1 4.0~j~---------------~----------------~--------

. '

SEPTEMBER 21, 1915

... 3.5

.' .. 3.0

' r

~ . " J'

J "-.' .

, . '1 •

2.5 . 0 , 0

w' . ::>

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, " , 1 . ,

.:1 , ,. '" ( c. t·-..~- ' J, .. \ .... (1 •

• 1 ... 1: ., • t' .. 1 • " 1: , , , , .. , , 1 't 't .. , , ~ ., .,. 't 11""T""t ., , ... t , " 1 ., ... " .; ,'t '"1'" ...... ,. ., , .. , " r · 'f , " ,.,. ....,. T y ... If " • ~ "~ " t

0.0 D. S' 1 .0 1.5 2.û 2.5 3.0 j.

',GREEN ·FILTER VALUE '.

, ,

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•

'. ~ o-I--=:::;::::======!=::=====:::;====::::::::======::&:=~

t

MARCH 2'5, 1975- ,

SEPTEMBER'21.1975 "

, .

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, 2.0

1.5

• 1

.F. ~ GURE .7 '. 5d If'

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0 odJ 0 X -$ 0 0 #' X

0 C • 0 # :#

:$# i-D

#. 1**. ~ ##<>.

## •• ,i .: -

, <> .•

• , ... i

":!

1~5 2.0 2. S " 4,(J '

GREEN f Il TER VALUE '. - increasin9~- RED REFLECTANCE - decre'osmg _

RED:GREEN FILTER' (IR':RED REFLECTANCE) <;>F DArA FROH SAHPLE CEJ.,LS l - 180 FOR TYPES 67. 5, 64. l, '52.1, Al. 2 AND 14. 0 FOR MAR CH 25 AND SEPTEHBER 21, 1975 .

139

..

SCATTERGRAPHS' . VEGETATION

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7.4 'TRANSITION ZONES - ECOTONES

There are 94 sampllng cells out of the transect total

of 300 whlch have been Identlfled as ~cotonal because the

sample area lies astrlde a vegetation boundary shown ln tbe r~).'

Af:rika Kartenwerk. However, the number" of sample 'cells

avallàble for study 13 sllghtly reduced for Match because of

èlpud cover (Table 6.4),.

In this section the dénsl tometr lc data from the sarnple

celis that occupy ecotonal p03.itlons wH1 be examlné-d ln.

. order te determln~ whether t,~eIr ecotonal statua holda, true ,

or whether there are /~ubstantlal dlscre~ancles.' Such ,/

d lscrepancies would Ind lcate poss i ble errOIS 1 ln the

placement of the mapped boundary ln the Afr lka Ka~tenwerk"

In Ta'ble 7.2, the sample celis are Usted accordin,g to

the ecotone, on whlch they o.ccur. In addlt1.on, ' there 13 an

indication of the relative area occupled by each vegetation .

type.' For ~xample, sample cell 19 13 filled almost totally

hy ,

vegetation type 51. 0 with only a sIMII 1 nc l us l'on ~of

vèqetatlon type '52.0 and 50 it 13 deslgnated as belng malniy

a type 51.0 (Figure 6.4). n

(Y

In contras t, sample' ce 11 26 . 13 ' , '

more or less blsected by the vegetation bo~ndar.y 'ànd th.1l!5: 1 t

15 descz::lbed as half typ~ 51.0 an\ half type 5,~.O.

Slnce the - forest areas are the most" dls'tipotlv~ ln

terllU5 of thelr appearance on the Landsat lmàge l' the ecoton~l .

sI tuatlon along these boundary I1nes wIll be, 'lnve:st19<;lte~ "

flrst. Twenty-four cells have been Ide'ntifled' as occur'lng "

along'the 14.01 or 14.2/51.0 eCQtone. However, the Harch 25, . , , , ' <,

1915 data set contains only 17 cells. The ,mlsslng s,even

140

..

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, , , TUU 7.2 . "

CLlIlIrICltlOI or fil Iq)fOflL SUPLllG mu, \ ' . - , • • • 1 r,' 4 ---------_ .... ------._-----_.------..... -.--_.. ...... ....... ----_ ...... -.. -... -.. ~ ..... --_ .. _~ ._------._---.. ~ . . '1COfOII , CIU, 10. ~ VlGldUOI --_ . .:_---_-:.~----_. _ ... _--'--- ------- .. -------

,ICOfOII, 1 CJLL,'O. 1 UGJfltIOi '" ~_ ..... _ ...... ~---_.!_-~= ... "-.,.-_ ... :.. .... _ .. _ ... _ ... _ .. _--~-_:. '" 51.'-14.' , .

U5 lU nt

sn c,H:O 15\ ~ 51.. '

51.. 51.8 51.'

. 61.5-14.0

5z.o-41. 2 J _,,' .'

51.8-U.,l

, " 1 ; 51 .... .,· .. S.

"

171 m' Ut

2U 242 243·

'2H: ' 245

, 146 251 251 2U 261 2U 2n , n' 215 21' 271 -lU ne 2n

51.' ~,

51.. ",f!: 51.-' l's, : 51.' 75"~ 51.1 ; 51\":', 14-. ~

SU'

'" : 14.1 . 15\ ': 5l'.8 , SI\ ~ 14,:2 '" :' 51,.0 7S\ =:14.1 50\ : if. 2

51.' 1S\ ~ ~l.O,

51\ :: 14,2 15' :: 1 t.2 .

5U , 51,.,

'" ,. -H,t

H.t ',75\ ": '51,1

24l '" ' :; SjA '251 ' 51.' 259' , H.l·· ..

1" , . '.n.s ,;.';. ~ '115 , 15' =: si.,

,124 ·15', ::'--51.' • 13f ,. ..61.S:

. lU 1S\ = 5l.1· :', 15'~ 1 ", .. ; ,51.1 J ..

151 ' '''''=}1.f ~ , "1 1

~~ ~ , ~ . 57.5-'ti

.1 111 ) 5" = 'f;1 12. 6tl ll1 . U.1 1S. ' '6tl,

..' ~./, \ 1.

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ne m m

S1.I-S2._ U

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• /' 25 26 11 33 14 75

" 77 II n

,lU Hl m

o 'm . ' ',L11,

l' ln ui', ' lt1 m

'.lU iu

'l 2'''' 2U n4

,215 m

'211 221 lU 234 us m m m

15\ : ~2.' .,,, : U.l

'" : 52.0

15\ = 52.'­

'" = 52.' ,s.\'= '4.1 52.0

51.' S1.'

50\ :: sr.. 0 •

15\ = 52." 56,' = S2 ... H' : 52.0 ,,\ = 5t.' m :: 52.0 15' : 51.8

52.0 ", : 51.. sn : S1.0 50\ = 51.' 15\ = S2.0

51. • S1.6

15\ = 52.' S,1.' 52.0

15\ :: 51._ H\ = ~l.ê

• 15\=SI • .8 51..

51\ :: ~1.1 -'" = 52.t

U .• 52.' '

15' " ~2.e 52.' 52.-8 51.'

15' : 51.. 15' = 51.. 15' : 51.' 15' = 52.'

" Ue.. .sl\ r: itl J l~:,t,.:_ .... _____ ... ____ ... ___ .... ':'; ___ ;'_" ___ ';" __ ."",. _____ ,:,. _______________ .. _ .... __ .. ___ ~ .. ____ : ______ _

, of (1 '" 1 4 ~ • ~ -,

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" r. r - ,' ... ~_._---_ .. _~_._ .... _.~ .. __ . __ ._-_.~ .. ~.-

)- \ . , \ lC~on' 1 ~LL 10. l 'Be_fltl " '" '"

\ . "

/' --''': .. )' .-----._--------_ ... _._---~----_.)----_ .. 'I,

~

.~ \

< ' " 51.1~52.1 32 51.0 \

\ . )

ut sn 51.. l" m 50\ = 51.0 "

" .. .51 .'-52.1 41 51\ 52.. ' '. "

s,f 52.0 52 52.1 .' 51 '52.0 't' ~

il 52.' ~ ,.

71 52.0 .---, ,

1--·-.---·~--.---_··-.-----~---·-------~-· "\ \ '.

", .... l-" 50\, "\. 75\ = appu~l~te ma of' Ii~plt

1 , c~ll coyere4 br t~e ID4fcatea ngetitioD tlpt;" , bi1uce oC

'\ celt'are. cnered " tu "- ' . o't.el ngehUoD tfP~ ,blc~

1

lltea tp Ue etotole ! ;.

f 1 " 1

:j " 1. '.. , .,

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',,"'. \ , ..... ~ ~ ~ .. '\

\ /' " , '

, ~ , , , ,- , . , '. " . <II • ~ otl

<{ , .. -:: / \, .. , ,

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e? , . " ,

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. , . -,

' .. ~

;(" : . " \

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.. -, ~ .' .

J' ~ ... ..

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sample cells"9ccur al~ng the Mathews Range and since ,thjs '" \ , ,

,eastern 'secfor is experïencing dry cond~ tlons .ln September';

,thè .ecotopal'da~~ tor'~a~ch i~" 1975'were s~bstituted for

tnese missin9 cells. Tbe data are plott~d in a ternary ", • ,. ' 'C.

, l 'diagram in Figure 7.6. The ecotonal feature space occupies à - , ,

" :, ~ôsi tion between vegetation types 51. 0 'and' 14.0/.2' "within ' . . .

ca'tegoryJI fe~ture' , spaçes, sUÇ>wn .in Figure 7.1a wi th $light, < ,... 1 " ;

" ,'overlaps ah the extremes: ,The reflectance. charact,eristics of:

"

'.

. '

.1 , ~.

the 14.0,14.2/SJ.,.0 ~cofone are 's.imil~r 'to the "dry season

spectral l

signatùre ,for ,

type ,67':5 vège'ta t .i.on (61-86%

't;ransIPissÎ,on, ~n the % red Ca tégory, . 10-31%' in' the green and

'.4-9% i,n the blue): .

" 'r~ th~ dry ,tlea-son, 'r,eflectance ln the,IR wavelengths

.ould. r~main relatively bigh for the e~e~green forest but .

qUite low for the' bushiand'types. Therefore, it should be

~asy ta dete,rmine whether the composition of. -a par'ticluar . , " 'ecotonal ' c~ll- (ia 'mai~ly forest or mainly \ bù.shland. Soth

. - forest types, ,(14.0 and 14.2) extübit~d iired transmission

,J

-values ~reater than 91% 'with less than 5% trans~iBslon in , t.

the 'gF~en and b,l'ue ca tegor ~es in. the dry season. For 'the , ' l •

dense bush+and ('type 5~ .'0), the valu_es· range'd from 43-74%

red, 20-,4S% green and 7-,16% blue. C'Ornpar ison of the ecotonal

values with these within category figures indicates that the

, majority of the 17 cells' are, indeed ecotonal in .character.

The spreatl of the 14.0,14.2/51.0 e~tonal feature space

i~ a functio~ of the proportio~ Qf for~st ~d bus~land within

Ehe area covered by the sampling celle In the dry season,

sample cells which are composed pr imar ily of type' 51.0

J,

. 142 , 1

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"" _,,-r , ,..Y

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> S,l ~

,~ ,~""

~'<! "-

, 4.t ~ • lTQ (.

177 e. i7o,180 ~ ln •

1110 • 1711 •• 25r

:lC-4 .' 'l17 2.2 .. e.e 276 HI, 27~ •• 2411

"

135.

2'3,·· 144

.' fe3, 170

"t Hf.1l TRANSMISSION

FIGURE 7,.6 '.

'TRANSMISSION TERNARY DIAGRAH TYPE" 14. 0, '14,2/ Sl. 0 ECOTONAL

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FO~ AL~ TitE SI TUA1\I ONS

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vegetation can be expected to plot,at'the hlghet 'green'

vè!l~l\ie8 , and. dlsplay reflectance cha:r;acterlstlcs slmllar ta '1 ,

,the bu-lk ~f th~ type ,51.0 "wi~hln category". cells." Those

Bample cells whlch ha,ver a 'f-0rest èo~pone~~ g~eater than 70%

or 80~ shoul? plot, ~t the hlghest :tred." values for the

ecotonal fea~ur~ space, and sample cells of more or less

equal'- grassland and forest comP9sltion should plot ,between' , '- '\ these two extremes. , ,

• This premise holds tr~e for sQme of the ecoto~al sample

l ,

cells. For example" on the basls of thelr map position,

sa~ple cel'ls 245 and 269 are deemed to be composed, of -

approximately 50% forest· (Figure 6.4). In the ecotonal . . •• c

'tèature spa~e,these two cells plot just abovi the 90\ red

transmission value, a location considered to be consistent

with_ their ecotonal situation as the buit of the "wlthin

category" forest cells are located above the 95% red value. " '

Alrphoto coverage was avallabl~ for ce11·245. The alrphotos

conf lrmed the cell" 5 ecot9nal status showlng a woody cover

over '82\ of the area of the cell and dense forest' ln

approximately 50\ of the cell (Plate 4). In Sect,ion 7/2.1 it , .

vas suggested that cell 277 was ecotonal rather than wlthln-

type. sample _ cell 245 'has a very s Imllar ' dens i tometr le

signature to cell 277 thereby glvlng stron~ support to thls

Interpretation.

At the other end of the' ecotonal feature space, flve

':sa'mple cells (177,' 257, 27-0,279 and 280) cluster together

between the 61:'\ and the 65% red transmission 1evels. ,These

cel.13 were aIl classifled as belng primarlly type 51.0

144 , '

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1 PLATE 4 STEREOGRAM' OF SAMPLE CELL 245

o 1,45

r ~

(

vege~ation, ~.e. only a very small part of the ce~l contains'

type' 14.0 or 14.2 vegetatio.ll. The tra1nsmission data for

these five cells ls similar to that obtained -for "w~l:hin , "

category" cells of vegetation type 51.0 (Feature Space B,

Figure 7. lb,),. This confirms their status and indicates 'that

th~ ~oundary in the Afrika Kartenwetk is probably correctly

'pl~ced.' / . Having established that the 14.0,14.2/51.

" ,

feàtu-re, space i5 anèhored at one end by, sample celI which

are primai' ily bushland and at the ,other ~nd by sample ell

wHich ~ave 4;domi~~nt forest component, sorne Inferences can '

be,made regarding the caver" composition of ttiose cells 1ying

between the two end clusters. Those cells 1ying closer \ to

samp1e cell 257 ~n ,the ternary diagram. _can be expected ,to '

contain mor~ bus,hland than forest, while those lying 'èloser

to sample cell 269'should have a larger forest dompone~t: , . \ ~

'. . An examination of the boundarJ position in the Afr i'ka

Ka r; te nwe,[' k' .and the t ransmi-ssion characteristics of " the'se'

lntermedia te sample cells showed that ' whi1e this : ~

int'erpreta tion ho1ds for of ' ,

true most the cells, sorne , ,

ar:tomalies exist which indicate - possible e,rro'rs iil the

p,ositiqn of the map,bou:pdaries. For example, ory the b'as'is of , 1

i~~-ma~ position, tw~-thirds'of the area covered by cell 251

is asSessed as forest. Thus, this èell should have plotted " '

around the 90% red 'trans~is~ion value in a simllar ~anner to

qelIs 245 and 269. Ln~tead , the densit;ometric

characte'ristics of sample cèll 251· place it within the dense,

bushland (vegetation type ,51.0 '), 'leadin'g to the conclusion

, .

. , '.

"

"

. , ,

-,

, ,

)

,0

that the area of forest at the northern end of the Mathews , ,

Range is probably much more restr lcte.d than is indicated on

the map. The situation o~ samplè cells' 264, 276 and 287 was "

found .to be ~im~lar. ~he map bounda~y locatlons indicated a , '

.sub·stant~al fO'rest cornponent wi thin the sample celi but the J , \ 1, .1

'~~n~itome~r~c sig~~ture and'pqsition in the te~n~ry diagra~ , ,'--.,..-

,( • .. 1

indib~te~ dense bushland insteaH. ~irphoto c6ver~ge for 1

sa.mple cefl 287 confirmed 'tha't much of the area covered by

the ciell'~as bushland not· foie~t (Plat~ 3) .

. In the case of sample cell~. 168, 179 and 267 the

situ~tionl is reversed • The position of the veqétation

. boundary. in, thes-e cells according to "the Af r ika Kartenwerk '.

~ndi~ates that they should plot close to the bu~hland end'of , , \

,thé 'ec~tonal feature space in the ternary diagram. Instead,

their,' actual locations indicate that the area of, forest

within these cells is g~eater than i'ndicated~ From ~is one

'ma y , concluc;1e that the f".>r'éSt-buslÙand boundary is hrobapif;

Incorrectly placed at these ,map loçations.

In a similar fashion, aIl the other sample cells of

ecotonal chara'cter 'V1ere analysed followi,ng,. the method'

des.cribed above.' In the 'case of ecotonal situations, in the

west and central sectors,of the transect, the wet season

data were also used where they aided '~1-n- the analysis. In

this way an assessn\ent was made of .the accuracy of any

boundary that was co~ered by a sampling celle The assessment'

was fairly straightforward -for most of the ecotonal cells.

~owever, the type 64.1/51 .. 0,52.0 and ,type 64.1/67.5 ecotones

merit further discus~ion.

147 " ,

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,-

In previous sections sorne questions were ra'ised

regarding the abili ty, of this . - typ'e of analysis to

discriminate ,between veg~tation types 64.1 and 67.5. It was .

suggested that the ecotonal da~a might clarify the

situation. In Figure 7.7 aIl those sample cells where

vegetation type 64.1 forms part of the ecotone are plotted

together with the type 64.1 "within category" data. As can

bé seen, there are two dis~inct clusters according ta the

vegeta t iOI) cate-gory wi th which "type 64.1 forms the " ecatone.

In the eastern iector of the transect o~ the Il ponyeki

Plains, sample cells from the_ 51.0,52.0/64.1 ~cotone display

densitometric characteristics very similar to that of the

dense bush1apd (type 51.0) "wi thin category" , ~

vegetation.

Along the type ,67.5/64.1 ecotone (montane forest-grassland) , . .

on the Lorog! Platèau, , '"

the ecotonal c~lls exhibit

densitametric ~haracteristics comparable te those displayed

by sample cells of type 67.5 vegetaticin in bot~ the wet and

dry seasons. ..-

Ai~photo Coverage was not available'f6r any of these

ecotonal cells, nor WqS wet season reflectance data , .

available fo,r the type 64.1 sample cel1s"'locate~, i~ the

eastern sector of the transect. Bowever, on the basis 'of the ,

densitometric data, it can be'cencl~ded (i) that the ar~a of, . ,

type 64.1 vegetation located in the eastern"s~ctor of the , 1

transect is spectral~y distinct from the area of type 64~1

vegetati,on located. in the central highland ar,e,ai, (ii) that

on the;II Ponyeki Plains the densitometric sig~~ture of type

végetaf'ion \

,64.1 15 very similar to that of the bush land ,

Q ( 148 '-. .....

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--------------- --------------------------------------------

< •

. .-

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.. i ..... 1.. .. . .~

41 .220

240 .. 139 no reo.OO. i50

250 O.2IQ· 2(8

l'.:t'OTONE SI 0, 520/a4 1

160 • lM •• 1~~

140 0. 130 f,OTONE ln s/a. 1

.. 120 • !lO

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<) fi.' 'Y 1 < .. f 1",tl~ ..

• D ~J' 'If .·,fl~

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Iln I~(J

, IIO.120~~~ ____ ~------~r_~---~----~-_r--------~--------~------~r_------~-~----_r---~~ It " .. li, , Il

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FIGURE 7.7 l'

.. ,J

%TRÀNSMI SSI 0 FOR ALL THE' TY'P.li - 'SI'. 0,52.0/64.1 ECOTONAL S I·TUA'I'I ONS ., 1

, "

\.:

149

types (51.0 and 52.0) in the dry 3e3so'n; and (Ui) that the -

area of, type 64.1 vegetation located on the Lorogi Plateau

15 spectrally sim11ar to vegetation type 67.5 in the' wet

sea50n, but exhlbits alightly reduced tred transmission (IR

" re flectance) and more %green transmission (red ,ref lectance)

than vegetat'ion type 67.5 ln the dry season.

In t::erms of boundary,accuracy, the transmission data

for sample cells 110 and 120 indicate that these cells have

",ore afflnity with vegetatfon type' 67.5 than type 64.1, ln

~hlch _ case sample celJs 139 and 149, whlch were prevlously

,thought to'be type 67.5 (SectIon 7.3.1), may Instead belong

in vegetation type 64.1. This means that the 'wooody

compone nt 15 more ~lkely to be thorn trees than montane,

, forest and the 6~ .1/67,. 5 boundary occur,s farther north ât:

these locations than 15 Indicated on the Afrlka Kartenwerk. Q

... No assessment can be made for the' 51.0,52.0/6:4.1 ecotone'

wlthout the wet season data for the eastern sector of the

transect.

The accuracy of the vegetatIon type 51.0/52.0 ecotone

ln the eastern half of the tr~n$ect ls âlfflcult ta aS3ess

wlthout wet season transmission data or airphot~- coverage.

However, the ,dry season data suggest that aIl the sample

cells on the ecôtone ln this area have a woody cover of 51%

.to 71%. Thus, there Is more afflnlty with type 51.0 , 1

,vegetation jthan . type 52.0. The dry

slqnatures:for these cells fall wlthln

season transmission

the range 43-62 \red,

30-43 and 8-14 \blue. These values aIl Ile wlthln the 00

150 '-\

,

0' \~ ':', r

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feature space ,of type 51.0 vege t'a.t 1 on as dlscussed above , , '

. (Table \t

7.1). It follows that .' .

the ,area' of type 52.0

vegetation in 1

the Mld7Uaso Nglro Basln ls much smaller than . ,

Indicated on the Afr ika Karteriwerk.-, Wet season data ~nd, . -'l

ai:rphoto coverage are 'need~d to cionflrm this Interpretation. !

An assessment of the type 51.0/52.0 ecotone in the Rift.

Valley can be attempted uslng the same type of analysls. ln

Section 7.2.1 it was suggested that the feature space o~

. vegetation type 52.0 was more or less identical wlth that of

vegetation type -51~a subset A (Figures 7.1e and J.ld). The

implication was that the areas ~overed by the sample cel~s

of vegetation type 51.0 ~5ubset A) and vegetation type 52.0

must consist of essentially the sarne type of bushland. 'The

phenological changes ln the transmlsslo~ characterlstlcs of l ,

the two bushland types (51.Q and 52.0), discussed in Section >II.

7.3.1, tended to support thls suggestion. The analy~ls

indicated that the area of type 52.0 vegetation on t~e

southern 'and eastern slopes of the Si la!'! caldera was\ 1

densltometrically ,slmllar to the area of type 51. 0 "

vegetation located on the western side of the Rift Valley,

and that both these areas had a woody cover component of 31-

50\. In the sarne section It was shawn that the area of t1pe

S~,. 0 vegetation, located in the Suguta Ri ver valley just

,n~th of the caldera was den5itometr~cally slml1~r to the

area of type 5.1.0 vegetation located on the step-faul ted

scarps of the Rlft'Valleyt s western face, and that both

these areas had a woody cover value of approxlmately 30~

wl th much ba~e g~'Ôund throuqhout thè year ,-

151

. ,

According to ,the vegetation type descriptions in the

Afrika Kar~enwerk (Table l.l), the o~ly difference' between

~ypes 51.-0 and 52.0 is stand arrangement. . The distr ibution

of thorn plants' and ~uccule~ts is much more open in

vegetation type 52.0 than in type 51.0. The an'afysis of the

densitometric data indicates that the three divisions ct these two bushland types, ela~orated as a function of %woody

cover and cluster ing of the densi tometr ic data -(Table 1.1);

can be reduced to two divisions if fi) the densitometric

signature~ of type 51.0 vegetation are considered as

représenting a woody cover of between 51 and 70% and

(ii) the 30-50% woody cover values are interpreted as

representing the response of type 52.0 vegeta~ion. If the

respective dry and wet season transmission figures for these

two divisions are used to classify aIl the type 51.0 and , ''\

52.0 sample cells in the western section of the transect, "

then the type 51.0;52.0 boundary shown in' Figure 7.8 is

probably more accurate than the boundary indicated in the

Afrika Kartenwerk.

This 'analysis of the ecotanal situations has shawn ~hat

three band ordination' of the densitmetric data can

contribute in the assessment of the accuracy of boundary

~lacement in maps of semi-arid vegetation types. It has been

shown that beundary accura9Y ls more effective1y analysed

when bath wet and dry seasen' data are available for

comparison, particularly for the bush land vegetation types.

, . 152

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' ..

.. ',\

, ,

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7.5 SUI1I1ARY OF 'lHE' DENSITOHETRIC DATA ANALYSIS

The results of the analysis of the densltometric data ,

can be summarlsed as follows:

1) Toree band ordination of %trans~.5s1on data from Landsat

,'colour composite/transparencies 13 an effective method ~or,

analysing the vegetation characterlstics of areas of semi­

arid vegetation. Supplementary detalls can be dèr'iyed whlch .

provide valuable additional information not generally

ava1.1able on smali-scale vegetation maps. In this, case

study, densltometrlc analysis perml tted ( 1 ) the

dlscrl~lnation of the var10us vegetatlon types existlnq ln

the area;

pne,nol.og i ca l

qu~e,

(i i) the deterrn1nation of' 'the extent' of' (J

change wlthln the vegetation types on bath a

and a quantitative bas~s; and (ll1), the . '

assessment of the accuracy of th~ vegetation boundarles

shown on the standard reference map of the a'rea (t'he 'Aft i'ka

Kartenwerk) . Specif ically, it ",as poss ibl:e . (to , "!

iden'ti ~y .Y

".feature spaces" for each of the ,;,ege-tatlon, types and ,to

detect ppssible Inaccuracies the . veg~tation

classification of ~ertaln areas of the Mar~lal transect ln

the Afrlka iartenwerk. In addition, when the densltornetrl~

data was Interpreted wlth reference to the alrphoto coveragé f

of the a~ea, specifie factors could be ldentlfled whlch

éxplalned why the' phenological re~ponse was selectl\le in ·t'he

bushland vegetation·types. " ,

2') ,This' type of. analys15 permlts the Identlflcatl,on o,f'

reglonal dlffererices withln the vegetation type~ and àllows

an ass~_ssment of the :ac.tual 9~'o9raph'lcal extent of wet

153 "

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, '

..

, , '

(

,. , , "

, . "

,season ra'infall dur ing the per iods 'for which Land~at images "' ~. ~ ~

a~e available.

3) Ba~d :rélt'ios .( IR':.r-ed reflectance scattergraphs) prGv'Î:des

re~llltS ,

comparable to those achieved using the ternary "

dia9~am an~lysis approach and in particular, seems te offer

fw-ther clarification of the regional anomalies which were

apparent, in s'orne of the bushland vegetation types. However,

three band. ordination, by inclu4,.ing %blue transmission

( gr eep 'r e flectance) in t he anal y~ i s, \ seems to i;>e rmit a more

accurate assessment" of phenological changes in the semi-arid ,

situation than is. possible ~,itp ,two-band ratioing.

4) Where tnere are sfgnificant' droug'ht-resistant and '~nnual ~ • ù ~ ,

components in thé: vegetation" o

\

wet and dry season

~ \transmission data are necessary for the\ discrimination of , ((' ,,' ,

. , , ,

" the J vegetation type and im "assessl11,en1= 'of phenolOEJical

changes or boundary accura~y.' .l~qw~ve'r, "where the vegetation t, ...

type~has a substantial evergreen component, that type can be

easily differentiate~/~ro~ ~h~se, ~om~~s~d of thorn~ plants ,

the basls of their ,dry seaso~ ',1 '

reflectance

characteristics. ... I, '

.'. 5) , cAerial photography is a useful to~h: ahd',whez:>. st~d}.ed in l. f 1 ~ , l ,

conjuncti?n with the Land9ilt imag'~s' '. It: . i9 . pbssible 'to , , , ,

the actual comp~sition(oi ~he, various ~ ','

e~timate vegetati'on • , T

types, particula~ly thé bushlan~ types.- This esti~a~~ 'can' ,

'help in identifying , .

factors responsible for sorne 'of ,the 1

anomalies seen in the reflectance data. . -- , ,

, , )

On the hasis oe tbe analysis "of the densitometric datë;l .

154

4)

: '

!'

, ,

o

.'

presented in .this' èhapt,e'r; rèyisions of ,the vegetation . '

,det,ails' sho~~ on the Afr ikët Kar tenwerk arEt proposed in the

rnann~r shown in Fi9ure 7.8.

FIGURE 7~8 :' "1 ~ ~'I

, PROPOSEO REVISIONS'TO ''l'ijE V:EGETATION DETAILS SHOWN ON THE " " 1\FRIKA '1(hRTENWERK 'AS A RESULT OF THE DENSI~OMETR-IC ANALYSIS

''\ "

"

>,

, ,1

• UN\lEGETATÈ:O SAND ;,OR LAVA' SURFACE , ,

• -l

, 1 ,

, . ' , " BOUNOARY' POS IT IONA L ERROR IN' THE ECOTONE '

{arrow, indicates dir~ction in' which the' '" boundary.., line-- Snauld be shiftedl

li! AREA OF SAMPLE CELL APPEARS TO -BE ECOTONAL RATHER THAN "WITH IN CATEGORY"

'"

• ACCURATE '~WITHIN CATEGORyll OR ECOTONAL CLASSIF ICATIQN

'. ". BOUNOARY ACCURACY UNKNOWN WITHOUT WET SEASON DATA

"

"

w: REVISEO AREA OF BUSHLAND TYPE 52.0: 30-50% WOODY C()tPOHENT ~ ~ LARGE ANHUAL COMPONEHT , ,

~,,~ REVISED AREA OF BUSHLAND TYPE 51.0: 51-70% WOODY COMPONE NT ~ SMALl ANHUAL COMPOHENT

155

, 1

C .' \

"

(

, -

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.... .." \,

> , '

,"

SUMMAR y ANI}, CONCLUS t.ONS' '\., ,

~,

\, In thi-s thesis il manual, densltometric-based' technique \

was' applled' to L<!lndsat faise colou~ compos i te ,imagery" to ,

de-termi ne the ab! l! ty of a," l~w-technoiogy" approach to

pr?vide su~plementary deta i Ïs to and' ver Hy thé accuracy of

an eX'lsting sma ll-sca le (1:1 mll1i-on) physlognomlc

vegetation mai;> which had 'been prepared usinq the compilation \

met:hod.

Systemat lc 'denslty measurem-ents were made on two

Landsat images of the stQdy area, both of wh ich were )

acquired within the same year but at different phenological

periods. The acquired densltometrlc da'ta were corrected' for l'

proê~ssing ëJ!nd haze errors and then classlfied 'accordi~g to

the-vegetëition types specifl~q in t~e Afrlka Kartenwerk. The

" d~ta were examined in t'Wo formats, first in terms of the

surface reflectance recorded in each of the three Landsat

bands, and then 1 n terms of the ra.t i 0 of the IR and red "

reflectance wavelengtl:ts. "

For the' thr~e band analysls, red, green and blue

o~ticai density values were converted to percentages of

"total reflectance (~transinisi31on).. The5e val~es 'Were then

treated as subsets and p1.otted on ternary diagrams accord ing

to thel~ 'vegetat,lon classification. T}:le IR:Red ratio data

were considered in the form of a graphie plot of the data

whlch used the actual dens i ty values obtalned in the red and

green fliter categories. ,The use of t~rnary diagrams ls a

156

"

, ,

l '

1

1

1:

,',

-t, .......

'1' jJ

"

",

'.

-',

~ part~cula'rly effective method of. establlshing 3pectra l

signatures (II featurè 'spaces") for the various vegetation

types. It _ presents the refleçtance data in a fQrm whLch Ls

easily interpreted and analysed . . The resul~s of the analysis, summatised Ln Section 7.5,

have demonstrated that the "middle.-ground" appr oach used ln

this stUdy" can permi t the d 15er i mlnat ion 0 f the Afr i ka

Kartenwerk vegetation' types, as we Il as a Il 0 W the ,

determination of the .. extl!n~ of phenological changes wltltln ,

the vegetation types 'and the '-assessment of' thè accuracy of

the vegetation ,b?undarles shown on the map. The s,tud'y has \ 1

presented a relatively simple and effective procedure for

obta i n lng addltlonal, information . for' and verUying the

accuracy' of sma] l-scale vegetation maps through the use of

(1) an avaflable, l~w cest, repet!t1ve data base whlch 13

sui table fo~ broaÇl-scale appl icatlons (Landsat i magery); ~nd

, (11) an Inexpénsive method of data analysls, compatlble wlth

the reliabi 1 ity and accuracy o,f the data base and producing "

vaUd resul ts (dens Itometry) .

A low-technology a~proach 15 of gr.eat bene fit to

developing countrles whe-re computer-based image processlJ'Ig

"

techniques are often not feasible, and where 1 i mi ted 1

personnel, flnancial and technlcal resources need to be

deployed ln a rat i onal manner. Sucl). an approach wl11 perm1 t

these countr les to take advantage of the' f.Ull potentla 1· of a

unique and tlmely information source - Landsat.

, 157

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APPENDIX~ A

DENSITOMETRIC MEASUREMENTS OF, LANDSAT SCENES

, , '~.' J'

'. .'

2062-07052 (MARCH 25, 1975) AND 2242-07041 (SEPTEMBER ,21, 1975) OF THE MARALAL TRANSECT

'*

(Vegetati"on type for .each sampling cell is based on Afrika Karte~werk~ Bader 1979) , ,

~ , ,

- ~ ~;;---

'1 '. , -'

an ecot one situation " ~

" . / densitometric measurement not possible due to

. contàmination by cloud or cloud shadow A

UNCORRECTED: ac~ual density reading

" . ~

CORRECTED: readings corrected in the manner describ,ea in Section 6.4 to minimize the effe'cts of atmospher ie scattiring and to standardize the images-

158

o

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- -----"" ---"_ .. _._-, .. ,.-

c

'l

'\

/ l,'

........ 25 weB 1915 , ,

'.J., --_._--~----------~~-.-.--------------~--._.--------~----_.----------.---_. __ .----.. _-~--~._-----._-, \ SlIIPU 1 VlGIUfIOI 1 ' UICoRRKCno' 1 COUletID, , l , fllISIIIIIIO. , , CILL lOI TIPI 1 YISU!L J 'RBD 1 GiBEl 1 BWg 1 YlSUAL 1 RID ~'Gilii 1 BLUB 1 RlD 1 GUll t BLUE

" ,

.------.---.-.-----------~------------------~--------- ----~-·---------------------r-------------·---

1 51.'0 1.03 ' 1.3' 0.91 0.94 2.61 ' 2,.21 2.43 2.10 SI 3S 'tS " 2 51.0 0.97 1. 58 ,0.11 0.13 2.61 2.U: 2.27 2.n, 30 SI U·

3 51.0 1.03 1.70 11. &6 O~86 2.67 2.61 2.n" 2.12 21 52 21 4 51.0 1.02 1.55 0.-18 0,.91 2." 2.'46 "2.34' 2.71 36 n '. 17 "

5 51.0 1.06 1.55 0.94 0.96 2.10 2.46. 2.40 2.12 l,' 44 17, 6 51.0 1.05 1. 57 0.92, 0.97 2.69 2.41 2.38 2.1l 37 41 16 7 51.0 0.$7 1 1.40 0.73 0.82 2.51 2.31 , 2.19 2,68 . U U 16 8 51.8 1.01 1. 57 ••• 5 0.93 2.H 2.41 2.32 2.19 34 49' 17 9 51.0 .0.9' .1.61 O.to 0.87 2.61 2.58 1.2& 1.13 li 55 U

10 51.8 0.86 1. 37 0.72 0.'0 2.50 ,2.2' ' 2.18 2.66 .31 41 16

11 51.0 0.92 1.45 0.79 0.82 2.56 2.36' 2.25 1.U U 47 17 17 51.0 6.96 1.58 0.13 6.11 2.54 2.49 2.19 ,2.U 27 54 19 13 51.'0 0.92 1.66 0.14 0.18 2.56 2.51 2. 2(} 1.64 24 56 2G .' 14. 51.8 0.96 1.72 0.76 0.80 2.6& 2.U 2.22 2.U 22 57 ' 21 15 51.0 0.77 1.35 0.63 0\73 2.41 2.26 2.09 2.5' 14 50 I~ 16 51.. 0.82 1..0 O.U 0.75 2.46 2.31 2.14 1.61 3l 50 11-11 51.0 0.81 l.41 0.65 0.75 1.45 2.32 2.11 2.n 31 52 16 18 51.8 0.83 1.39 0.'9 0:75 . 2,41 2.30 2.15 2.'1 34 49 11 - 19 t 0~5' 0.91 0.47 0.60 2.20 1.82 1.'3 , 2.'6 SI- H 11 20 51.8 0.67 1.12 0.56 0.73 2.31 2.83 2.82 2.,5' ' 43 45 12 '

21 51.0 0.e5 1.31 0.72. 0.71 LU 2.2& 1.18 1.6) ]7 t1 16 22 51.0 0.83 1.51 O." 0.71 2.47 2.42 2.12 2.51 21 54 19 2l 51.0 0.81 L64 0_.67 0·.71 2.~1 2.55 2.13 2.57 22 57 n 2~ 5U 0.86 1.62 G.n 0.71 2.50' 2. 53 2.13 2.57 22 57 ,21 ' 15 t 0.64 1.21 G.50 0.5' 2.28 .. 2.12 .1. 96 2.45 )4 50 16

,26 t 0.12 1'.20 '.n o.n 2.3' 2.11 2." 2.55 46 45 15 27 t o,n 1.67 0.14 0.83 1.51 2.58 2.20 1.'9 H 57 U 28 . 52.0 1.03 1.69 D.16 0.92 2.61 2.U 2.32 2.71 28 53 19 29 52.0 0.92 1.58 0.77 0.88 2.56 2.41 2.23 2.14 3J 51 li 30 51.0 0.86 1.40 0.73 0.16 2.50 2.31 2.19 2.72 37 49 14

11 51.0 0.89 1. 53 0.13 0.78 2.53 2.44 2.19 2.U n 52 ,19 32 t 0.91 1.59. a.74 0.79 2.55 2.5' 2.20 u~ 27 54 19 n t 0.82 1.68 0.62 0.67 2.46 2.51· 2.88 2.53 21 s. n " 34 . 52.0 0.51 1.03 0.45 0.54 2.21 L9t 1.91 2.41 . 42' 4t 14 15 52.0 LOt LU 0.82 G.al 2.68 2.7S 2.28 l.n 2t SI 12 36 S2.0 1.16 1.82 1..0 1.80 . 2." 2.13 2.U ~:" 21 52 20 11 52.0 O ... 1,')1 0.77 • 8.81 2.52 2.29 2.23 2.13 te U 14 38 52.' ' 'l.U 1. 82 '.H D.U 2.71 2.13 2.14 2.15 27 53 20

r 19 52.0 LU LU 1.08 l.O' 2.82 2.58 2.54 M5 te U 11 40 52.' 0.96 1.49 '.12 0.91 2.61 . 2.41 tU z.a 37 48 15

U t 0.95 1.14 0.15 '.74 2.59 2.65 l.2l 2.60 21 S, 2l 42· St1 0.73 1.31 '.51 US 2.37 . 2.22 2.14 2.51 33 50 11

i'} U 5l.0 O.U 1.11 '.4' t.51 1.15 1.03 1.'5 tU n u 15 ~ ft 52.1 1.11 1.15 '.H 0.91 2.15 2.U 2.U 2.U 23 55 22

45 52.0 1.24 2.11 1.03 .. " 2.81 L09 2.49 ,2.12 15 SI 27

J

15'

, . l' ,

25 IlliCB 1975 ,

C 1 / ' l _______________ .., ..... ___ .... __ ..... __ ~ ______ ~ .... _____________ --___ ... __________ ... ______ • ----/<0 .... -______ ..... _______

'lIPLI !nGn'nroll UlCOIUCTBD 1 CORRICflD 1 , TRAlSKISSIOI Clf,L 101 ftP) "nuAI.' RlD 1 GUll 1 8'.OB.' VIlOAL l'RlD , Gilll, 1 BLIJI rm 1 GRill 1 BLUE

\ '. ( ....... -*' ............... "; _______ ... "' ___ ...... _ .. _ .. _ ............. ""'_ .......... ___ ...... ~ __ ... ___ .. .,. __ • ___ .. - ___ ............ _ -~1'1'''''''''- -- ......... _ .. -~- _ ........

46 52.0 1.15 1..0 1.10 O. ,. 2.79 2.11 2.46 2.84 2. 51 21 ;.

47 52.0 L02 1.72 Ut 0.85 2.66 2.63 2.30 2.11 2S St 21 U 52.0 0.96 , 1:51 0.13 ,0.89 2.60 2.42 2.2' 2.75 ' 35 48' , 17 49 52.0 1.24 U2 1.12 1.10 ' 2.88 2.13 2.S' 2.'6 ' 11 .7 20 50 52.0 0.85 1.41 0.11 0.'3 2.U 2.12 2.17 2.69 35 50 ' 15

"

51 t 0.83 1.31 0.69 0.73 2.41 2.28 2.15 2.59 35 U 17 52 t 1.38 " 1.'2 1.16 l.U 3.02 2.13 2.72 3.04 3S 44 ' 21 53 52.0 0.87 1.31 ,Ut 0.80 2.51 2.24 2.10 t6' U H 15 SC ' 52.0 1.06 1.69 8.19 0.17 2.7' 2.60 2.35 2.B 28 51 21 55 52.0 1.'33 2.22 1.14' 1.06 2.97 3.13 2.60 2.'2 11 56 21

5' 52.8 1.28 1." 1.13 1.19 2,92 2.11 2.5! 2." , 27 51 22 57 52.0 1.21 2.04 1.10 '1.61 l.n us 2.56 2.'3 22 S5 23 58 52.' 1.11 1.91 .,99 o.,. te'! 2.12 2.45 2.14 . 23 55 22 59 52.0 1. 2' 1.95 1.11 1.09 2.90 2.86 2.57 2.H H 52 22

'0 52.' 1.23 Ln 1.15 1.11 2.U 2.51 2.U 3.1f 4t 41 15 ~,'

n t 1.31 1.9. 1.25 1.14 "3.02 2.8, 2.11 l.00 li tG 2t n , 52.1 2.36 3.09 2.25 1.69 4.0' UG 3.11 3.55 17 33 50 53 t 0.54 Ut 0.47 0.57 ' 2.18 1. 75 1.93 tu 5t 3S 11 64 52.' 1.17 1.13 1.13 1.84 2.81 2.64 2.U 2." 3t 48 18 '5 52.0 1.23 2.01 1.04' 1.00' 1.81 2.92 2.50 2.86 .2} 55 24

" 52.' l.l6 2.U 1. 20 1.11 "3.00 ).04 2." 2." 22 52 26 n -52.0 1.i1 1.97 1.12 1.08 U1 2.88 2.58 2.H li 52 22 U 52.0 1.01 1.57 0.16 0.91 1.65 2.41 2.32 2.77 3t H 17

" t 0.92 1.3' '.80, 9.90 2.5' ' 2.30 2.26 2.76 t1 45 14

f 10 t : - t.n 1.20 0.'0 O.,. Ul 2.11 2.26 2.16 51 ' 37 11

"

11 t 1.05 1.58 0.95 1.02 2.i9 2.41 2.41 1." 'n tl 43 14 " 72 52.0 1.18 1.75 LU 1.07 2.12 2.U 2.58 2Jl d4 48 18

13 52.0 " 0.13 1.)3 •• 57 0.65 2.31 2.24 2.83 2.51 32 51 17 74 t o.g6 , 1.63 •. 1' 0.12 UI 1.54 2.24 2.61 21 54 l' 15 t 0.92 1.51 0.17 0.82 2.'56 2.42 2.23 2.61 12 50 11 l' t 0.95 1.37 '.14 o.n 2.5, 2.2' 2.38 2.15 43 42 ' 15 17 t 'f _ 0.85 1.22 0.17 0.12 2.49 2.13 2.23 2.61 fi 31 14 11 t 0.72 1.09 '.63 t.72 2.36 2.81 2 • ., 2.5' U 39 13 a 41.2 . LOS 1.t5 . '.96 1.00 2,69 2.36 2.42 2.86 H te 14 80 t1. 2 f 0.99 1.28 '.'5 o.n 2.U 2.19 2.41 2.15 5S 33 12

Il t 1.07 1.41 O.,. 1.02 2.71 2.39 2.44 2." 45 40 15 n t 1.03 LU '.'3 1.13 2.61 2.37 2.n 2.U 44 42 14 Il 51.0 1.02 1.12 '.14 '.81 U, 2.63 2.30 2.14 25 55 21 \ 14 5.1.' 1.10 1.41 1..3 LU 2.74 2.31 2.U 2." U 37 15 \

15 51.0 ,"'3 LU '.16 '.98 2.57 . - 2.11 2.32 2.16 51 3' 13 \ \

" 51.. 1.01 1.41 1.11 1.15 2.12 2.32 2.41 2.91 51 36 13 ,

\

(:, -n t o.n 1.21 .... "'1 2.S7 2.12 2.3' 2.13 5' 33 11 Il 41.2 1.01 1.35 .. ,. tu us 2.1' 2.te 2.U 5' U U ., , 41.2 0';" 1':01 '.13 .... 2.41 1"2 2.19 2.7. 5t "31 1"

" n.z 1.14 LU 1.12 1.U 2.11 Z.27 2.5' 2." 61, 1 29 \.11

.. ~ lU

\1

? " .' "

\

25 KARc. ms ~~

~ , ,

Ù; ---_ .. ~- .. ---................ _ ... --- ..... _ ..... _- --- ...... -.... \"'- ...... --_ ...... ,,_ .. --_ ................ --- .. ------_ ..... -.......... _ ... -----._ ..... -- ..... -...... .-

SAllPU IVIGIUTIOHI ' UICORRBCYlD 1 ,~ CORUCTU ,1 \ TlU8NISUOI CILL Ibl 'nPB 1 VISUA~' 1 RiD 1 GRBU 1 ILUB 1 fISUAL 1 nD 1 Glln 1 SLUr! UD 1 Gal Il 1 StUI , --.. _----- -- -_ ..... ----------.... -... --------------_ ........... ---.,. ...... ---_ ... -...... -...... _--- -- --_ ......... _---- _ ........... -_ ... _ ... ----.....

n: 51.0 0.9) 1.36 0.83 0.95 2.57 2. 21 2.29 2.11 45 42 11 92 51.0 1.01 ' 1.45 ..,1 0.'9 2.65 2. 36 2.37 2.15 4J 4l 14 Ù' 51.0 1.09 1.50 1.00 1.01 2.73 o 2.41' 2. 46 2.11 4S 40 15 9( 51.0 0.85 1.15 ... 0 0''0 2. ., 2.06 2.26 2." 55 H 11 '5 51.0 0.96 1.29 0.89 0.91 2.60 2.20 2.35 tal 52 3' 11 gp 1.45 1.56 1. 50 LU' J.U 2.41 "2." 3.B 6' 22 10 n 41.2 LU 1.36 1.19 1.22 2.83 2.27 2,65 3." U a 18 ,. , 41.2 1.22 1.38 1.23 1.14 2.16 2.29 2. " 3.11 64 26 10 n 41.2 1.3& 1.38 1.36 1.32 2.94 2. 29 1.82 ).11 11 21 ,

100 41.2 o .9( 1.18 '.H 1.08 2. S' 2.09 2.11 2.U ,9 II 10 ,

lU 51.0 1.02 1.54 US 0.91 2.66 2 •• 5 1.l4 2.71- Ji n 11 102 SU 1.09 1.58, '.97 1.00 2.73 2.n 2.43 2.16 39 45 16 113 51.0 1.01 1.46 Ml 0.98 2.67 1.31

' , U9 2.'4 41 41 15 0

" lOf 51.9 0.98 1.25 ..,S 1.03 2. 62 2.16 2.n -2." 57 32 11 115, , 51.0 0.91 1.11 1.00 1.10 2.61 2.02 2. 46 ?" U 2t ' 1 ',-

10P 1.33 1.31 1.40 1.40 2.91 2. 22 2.15 3.16 76 17 1 111 61.5 l.U' 0.98 l.30 1:31 2.13 1.89 2.16 3.23 .S 11 4 108 67.5 1.09 ' l.08 1.16 1.25 2.13 1.'9 Ut 3.11 " 1& 6 119 67.5 1.21 1.23 1.37 1.39 2.91 2.14 1.13 3.25 11 16 ,

" 110 t " 1.29 .1.21 l.U 1.31 ~ 2.91 2.18 2.17 3.24 77 16 1 "

III . '51:0 l.U 1.65 0.98 1.02 2.15 2.56 1.44 2." 36 47 Il ., 112 51.. _ 1.05 1.51 '.H 1.01 2. 69' 2.42 2.4& 2.11 42 43 15 113 51.0 0.77" 1.03 0.13 0.88 . 2.41 1.94 2.19 2.14 51 13 , 114 51.0 ' 0.81 1.14 ' '.13 O." 2.51 2.05 2.2', 2.12 57 13 10 Ils * O.SI 1.01 '.90, 1.'00 2.52 Ln 1.36 2.U 61 21 ,

, 116 " .5 0.86" o.~s U3 1.04 2. 50- 1.16 2.n 2." n 18 , , " .

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'3· 51.1 LU 1..5 2.09 1.74 3.17 2.55 3.33 ].32 7S 12 1)

'4 51.8 1. 70 1.40 2.18 J.U 2.99 2.10 3.42 J.39 91 4 5 '5 51.. 1. 74 1. 58 2.14 1.U 3.0] 2.20 3. 38 3.39 SI , , " . 1.86 . 1., j6 2.65 2.18 3.15 2.06 3.19 1.U 97 1 2 91 41.2 1.71 lJ5 2.42 1.00 1.06 2.05 1.66 ut ,s 2 l ,. 41. 2 1.65 1.16 2.42 2.03 2.94 1.86 3.66 Ul 91 1 2

" 41.2 1.71 1. 22 2.52 2.09 3.00 1. 92 1.16 3,61 91 1 2 lOI 41.'2 1.73 1.31 2.38 !J6 3.02 2.01 ' J.62 J.54 95 2 3

lU 51:0 US 2.13 1. 58 1.44 2.94 2.83 2.82 1.02 31 38 24 102 51.0 1.77 1.95 1. 83 1.60 3.06 2.65 J.07 3.18 60 23 11 113 51.0 LU 2.01 2. 00 1.61 US 2.71 3.U" 3.25 63 19

!~" 114 SU 1.87 1.11 2.15 1.18 3.16 2.41 3.39 3.36 80 10 , US ~" 51.0 1.15 1.40 2. 28 1.92 3.04 2.10 3. 52 l.se 93 3 . ' m t 1.58 0.99 2. 50 2.11 2.87 1.69 3.14 U9 98 1· 1 117 n.s 1.5' 1.16 2. 01 1.81 2.85 1.86 3.25 3.H 93 4 )

111 n.5 1.73 1.18 2.62 2.18 3.02 1.88 3.86 3.76 9. 1 1 il' 61.5 1.14 1.23 2. 51 2.18 3.03 1.93 3.11 3.16 " 1 2 11I t 1. 75 1.20 . 2.65 2.23 3.04 1.90 3.89 1.1l 98 1 1

111 51.0 1. .. 2.14 1.79 1.60 3.09 2.'4 3.03 3.U 41 31 22 "

112 51.0 1.12 2.02 1.88 1.65 3.11 2.72 3.12 3.B 59 23 11 113 51.0 LU 1.41 1." 1.11 2.91 2.11 3,20 3.a 81 7 , 114 51.0 1.71 1.35 2.28 1.91 3.00 2.0S 3.52 1.49 H l 3 115* LU 1. 22 "2.35 ' 1.98 2.95 1.92 l. 59 3.55 " 2 2 lU " .5 1.65 1.12 2. 53 2.16 l'.H 1.82 3.77 3.74 ' 9. 1 1 117 51:5 1.5' 1.16 2.11 1.91 2.88 1.86 1.35 J.U 9S 3 f lU n.5 1.14 1.21 2.64 1.20 3.03 1.91 3.18 3." 9. 1 1 lU " .5 1.63 1.14 2.41 2.0. 2.92 1.84 U5 l.U 91 2 :' 1 120* 1.61 1.10 2.45 2.09 2. 9O 1.80 3.U 3.61 9. 1 1

121· 51.0 1.45 1. 57 1.53 1.47 2.74 2.21 2.71 US 51 21 11 -122 51.0 LU 1.37 2.06 1.19 2.91 2.01 3.36 3.31 U li 24 123 51.0 1.65 1.19 2. 36 2.02 2.94 1.89 1.'0 U. " 2 Z 12ft 1.54 1.13 2.13 1.89 2.ll 1.é3 J.17 3.47 95 3 2 ~

US 61.5 1.62 1.14 2.31 2.02 2.91 1."4 3.55 U. 9' 2 2 12' ".5

.121 n.s 1.11 1.22 ' 1.52 1.14 3.00 1.92 3.16 3.11 " 1 2 12. n.5 1.99 1.60 2.62 2.15 3.28 2.30 3." 3.13 94 3 l 12', n.5 1.13 1. 30 2.40 2.06 3.02 2.00 3.64 3,64 " 2 ·2 n .. 1.50 0.98 2.28 1.96 2.79 1.68 3.52 3.54 '7 2 1

Ul 51.0 1.6' 1.76 1.16 1.64 2"5 2.46 3..0 1.21 U 11 11 1

132 51.1 1.48 1.30 1.77 1.61 2.77 2.00 3.11 3.25 87 1 5

D ~ III 51.0 1.62 1.17 Z.l1 2." 2.91 1.17 l.5S l.St " 2 2 13P 1.51 1.00 2.S2 2.14 2.17 1.78 3." 3.12 " 1 1 usa Ln l.11 2.5' tu 2." l.11 l.U 3.11 " 1 1

HI

..

Zl IImIIA ., 7 S

~ _._----------------------------------------.. ---------------------._---------------------------------.urLi Im"AflOII UlCOIIICflD 1 COUICfID 1 , RUI.lIlIo.

au. 101 ml 1 muAI. 1 110 1 SIlO 1 nUi l 'UUlt 1 IID 1 Slin 1 l'" 1 lit 1 GUll 1 ILVI -- .--_ .......... -....... -............ _.- ............ -................ -_.- _._ .......... _ ...... -- -_ ..... _ .. ---_ .......... -. _._-- -_ ............. -._ ........... ----.- .....

lU 14.. . lJ7 61.5 1.84 1.f2 2.53 2.12 3.13 2.12 3.77 3:11 95 2 3 131 61.5 1.81 1.35 2.53 2.10 3.10 2.05 3.77 3.U 96 2 2 Ut 61.5 1.54 0:97 2.41 2.05 2.13 1.61 3.'5 U3 U 1 1 ; 141 64.1 1.50 0.ge 2.26 1.96 2.79 1.68 3,50 ur 97 2 1

lUt 1.42 1.61 1. 42 1.46 2.71 2.38 2.66 3.04 57 Je 13 lUt 1.65 1. 74 1.74 1.65 2.94 2.44 2.98 3.23 69 2. 11 lU 51.0 1.55 LlO 1.89 1.79 2,84 2.00 3.13 3.31 ., 7 4 Hf 51.0 1.43 1.19 1. 73 1.69 2.72 1.89 2.97 3.27 89 7 4 us 51.8 1." 1. 55 2.16 l.86 3.08 2.25 1.40 J." 88 , V~

~1Ut 1.62 1.04 2.59 2.22 2.91 1.74 3.83 3.10 98 1 f 141 61.5 1." 1.10 2.59 2.21 2.95 1.'0 1.13 3." 98 1 1 141 61.5 1.51 1.11 2.30 1.99 2.87 1.01 3.54 3.57 96 2 2 lU 61.5 LU 0.90 2. 20 1.93 2.73 1.60 3.44 3.51 97 2 1 mt 1.31 0.89 2.02 1.83 2.66 1.59 3. 26 J.U 97 2 1

151 52.0 1.5, 1.83 1.60 1.59 2.88 2.51 2.84 J.ll 5. 2' 13 mt 1.5J 1.86 1. 50 1.5J 2.82 2.56 2.74 3.11 51 34 15 lSl 51.0 1.32 1.., 1. 36 1.47 2.61 2.19 2.60 3.05 " 25 ,

\.7. 154 51.0 1.12 1.17 1.21 1.37 2.41 1.87 2. 45 US 74 28 , 155 51.0 1.41 1.47 1.50 po 2.70 2.11 2.14 3.8. 12 U , m t 1. 76 1.50 2.17 1.90 3.05 2.20 ).41 3.41 90 5 5 1511 U3 1.0' 2.58 2.22 2.92 1.16 3.02 J." " 1 l,

mt 1.98 1.58 2.55 2.18 3.27 2.28 3.19 3.76 9,C 3 l 159 lU . UP 1.43 0.98 2.01 LI' 2.72 1.68 J.25 3.44 " 2 2

~

~

lU SU 1.34 1.88 1.24 1.32 2.63 2.sa 2.U ue 31 u 17 UP 1.45 1.90 1.38 1.42 2.74 2.60 2.62 J.08 42 U 17 lU 51.0 1.45 1.76 1. 45 1.5J 2.75 2.U 2." 3.11 55 3J 12 lU 51.1 1.18, 1.32 1.23 1.40 2.47 2.02 2.47 2." 68 24 8 us 51.0 1.16 1.34 1.19 1.31 2.45 2.04 2.43 US 65 21 , 1" 51.0 1.11 1.13 1.21 1.34 2.40 1.83 2.45 U2 76 18 , lU 51.0 Ln 1.41 2.2. 2.80 1.08 2.11 J.52 3.51 92 4 4 UP 1.62 1.04 2.60 2.24 2.91 1.74 3.14 3 •• 2 91 1 1 ln 14.0 1.7. 1.21 2.57 2.24 3.07 1.91 3.11 3.82 91 2 1 111 lU 1.78 1.28 2.51 2.20 3.07 1.98 3.'5 3.78 97 1 2

\. " 171 52.8 1.2' 1.14 1.15 1.21 2.55 2.54 2.39 2.n 34 n 19 1721 1.24 1.65 1.17 1.29 2.53 2.35 2. .. 1 2.11 46 fi 14 lU' 51.0 LU 1.17 1. 36 LU 2.71 2.57 2.U 2.U U 40 1~ 174 51.8 1.21 1.37 1.26 1.39 2.50 2.07 2.50 2." 67 25 •

,", 115 51.8 1.11 1.12 1.23 1.3. 2.41 2.02 2.47 2.H U 24 • 176 51.8 1.26 1.45 LlO 1.44 2.55 2.15 2.54 3.82 6S 26 , -

0 1171 1.31 l.U LU Ln 2.59 2.06 Z.U US 13 19 'L--

--~-1J,-t 1.51, 1.45 1.70 1.61 2.18 2.15 2.94 3.25 U 13 , n,. 1." 1.U 2,42 2.11 2.95 1.16 3." 3." 97 2 1

viti 14.' 1.71 1.12 2.75 2.31 1.00 1.12 3.99 3.'5 ,. 1 1

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, - .. •• n IBCI!l!IOII UlcœUCno l 'COIllan l' '11-:11101 ", ..

ClL~ 101 !IPI , YlSUlL , RID 1 Glili 1 BLOI 1 YIIUlL 1 IID 1 GIIiI 1 ILUI 1 lit 1 Ga 1 UI . ---~_._---- --------_ ... -----.... --.---_ .......... --_ .. -- -- -- ..... -.. ------... ------- .... _---_ .. --_ .... _-- ----------- -_ .. -..

. r 111 52.0 1.35 1.11 '1.16 1.31 1.64 2.51 1.S0 2." h n 17 112 52.0 1.08 1.43 1.01 1:11 2.37 2.13 0 2.25 2.15 50 II 11

113 • 1.31 1..0 1.21 1.34 2.60 2.50' 2.45 2. 92 ft 45 15 "

lit • 1.19 1.38 1.21 1.35 2.48 2.08 2.45 2.93 64 27 , US 51.0 LU 1.27 1.26 -LU 2.U 1.97 2.50 2." 72 21 7 • lU 51.0 LU 1.30 1.20 1.38 2.45 2.00 2.44 2.96 U 2S 7 117 51.0 1.04 1.29 1.02 , 1. 30 2.33 1.99 2.26 2." " 12 1 Il. 51.0 LU 1.28 1.16 1.37 2.H 1.98 2.40 2.'5 67 26 7 lU 51.0 1.16 1.31 1.15 1. 36 2.45 2.07 2.39 2.94 62 10 1

. ~ ue· 1.53 1.5'3 1.68 1.66 2.82 2.23 U2 3.24 17 1

7 1 H

b 191 52.0 1.18 1.64 ' 1.07 1.20 2.47 2.34 2.H 2.78 H H 15

192 • 1.21 '1.69 1.11 1.24 2.50 2.39 2.35 2.82 H t4 15 1 U3 • L35 1.17 1-.21 1. 35 2. 64 2~n 2.52 2.9 J 4S 40 15 U4 51.0 1.38 1.53 1.42 1.46 2.67 2.23 2." 3.04 66 ,,24 10

-l, US 51.0 ,1.25 1.36 l.l1 1. 46 2.54 2.06 1.55 3.04 18 21 1 19' 51.0 1.09 1.28 1.11 1. 37 2.38 1.98 2.35 2.95 65 28 7 U7 51.0- 1. 20 1.49 LU 1.40 2.49 2.19 2.f2 2.98 57 34 , 1,. t -.

1.20 1.51 1.16 1.40 2.49 2.21 UO 2.98 55 36 9 -7

1" · LU 1.4' 1.15 1.36 2.41 2.1,. 2,3' 1.94 55 35 10 2 .. t 1.21 1.44 1.21 1.H 2.50 2.14 ~.f5 2.97 61 30 ,

P .cl " " 211 ' 52.0 1.09 1.5' 8.97 1.17 2.38 2.29 2.21 2.15 lt n 14

212 52.' 1.11 1.66 Ln 1.Zt 2.41 2.36 2.33 2. 12 42, f4 14

1.3 • 1.21 l.U 1.14 1.2' 2.50 2.32 2.38 2.11 H 41 13 A 2.4 • 1.19 1.49 1.16 1.34 ua 2.19 2.40 2.92 5' 34 18

215 • 1.33 ~U2 1.32 1.36 2.62 2.32 2.56 2.H 55 12 13 -' 2" t 1.17 1.34 1.20 1.38 2.46 2.04 2.44 2.96 " 26 • 2tJ •

. , 1.21 ,1.;0 1.11 I.lt 2.49 2.20 . 2.41 2.H 55 lt 11 2 .. 52.' 1.25 1.61 1.21 1.35 2.54 2.31 2.45 2.93 51 31 12 219 , 52.0 1.24 1.62 1.19 1.34 2.53 2.32 Lfl 2.U U lJ 1]

21. • 1.26 1.45 1.28 1. 39 2.55 2.15 2.52 2.97 63 21 11

, 211 52.0 1.13 1." 1.01 LU l.t2 U6 U5 2." 31 ta 15 212 52.0 1.14 1.65 . 1.84 1.22 2.43 2.15 2.11 2.10 40 46 ' 14 213 52.8 . 1.11 1.5' 1.10 1. 2S 2.f6 2.26 2.34 2 •• 1 U 39 1)

214 52.0 .- 1.33 1.67 I.H 1.36 2.62 2.37 2.53 2." 51 35 14 . ~ 215 52.0 1. 30 1.'5 1.26 1.3) 2.59 2.35 1.50 2.91 51 n u 216 52.' 1.28 1.54 1.21 1.35 2.57 2.24 2.51 2.93 51 31 12, 211 _52.0 1.31 LU 1.29 1.3. 1.60 2.32 U3 2." 5t 14 12 211 52.8 1.25 1.60 1.21 1.32 ' 2.54 2.30 2.45 2." . 51 3' 13 ZU 5UI 1.17 1. 58 LU 1. 29 2.U 2.20 2.31 2.87 5) 36 11 22. t 1.20 1.47 LU 1.,33 2.49 -2.17 Z.U 2.91 51 32 11

221 1 1. 20 1.78 1.10 1. 26 2.49 - 2. 4,0 2.U 2.14 ft fi U'

0 222 • 1.16 1.61 1..5 1.2. 2.4~ 2.31 2.U 2.71 'lt 46 15 223 52.0 .1. 21, 1.56 1.15 1. 21 2.50 2.2' 2.)9 2.15 SI 31 Il 224 52.' l.li l~S' 1. .. 1.23 2.45 2.2, 2.32 2.U -u U 13 US 52.' 1.1' 1.52 1.1' l.U 1.5' l.12 2.53 1.94 ," 29 11

-, (J .

nt . ,

., ,/

21 SIf1IKBIR 1915

(. ......•...... ,: ..........•...... _-----_._-----------------------------~--~------------------------IAllPLI 1 flmlfIOI 1 . OICORRlCflD 1 CORRlctlD " ,.1I8I1UIIOI CI'L 101 tIPI 1 YI8UA~ 1 RID 1 GIBEl 1 BLUI l 'ISUAL 1 IBO 1 GIIII 1 ., 1 1 IID 1 Gliii 1 BtOI . ______________ • ____ ~ ____ • __________________________________ a ________ ~ ___________________ ~ ___________

\~2' 52.0 1.15 LU 1.11 LU 2.44 . 2.16 2.35 2.'6 ' SC 35 11 27 52.0 1.24 1.62 1.18 1.-2' 2.53 2.32 2.42 2:" 48 li ')4 \'

·'U' 52.0 1.22 1.5. 1.16 1.29 2.51 2.2' 2.40 2.87 n 3t1f.! 13 22' 52.8 1.~5 1.49 1.10, 1.30 2.44 2.19 2.34 2.'" S2 37 11

230 • O. f 1. 38 0.94 1. 21 'i:;;2.28 2.00 2.18 2.86 55, )7' 1 ... "

231 51.,0 1.34 1.69 ,1.30 l'oU -2.63 2.39 2.54 2.99 51 36 13

212 51.0 1.41 1.73 1.3a 1.42 2.70 1.43 2.62 3.00 52 3t 14 233 51.0 1.37 1.61 1.37 1.44 2.~' 2.31 2.61 3~02 59 30 11

/ 234 • 1.41 1.69 1.41" 1.47 2.70 2.39" 2.65 3.0S 51 Ji 12 235,- 1.34 1.53 1.37 1.47 2.63 2.23 2.61 3.05 64 26 10

lU • 1.11 1.3. Ln Ln 2.48 2.08 2.45 2.99 65 21 • 237 _ 1.21 1.'49 1.1' 1.35 2.50 2.19 2.43 2.91 57 33 10

23. • 1.23 1.50 '1.21 1.36 2.52 2.20 2.45 2.94 57 12 ur 239 _ 1.16 LU 1.12 1. 31 2.45 2.18 2.3' 2.89 54 36 10 240 64.1 O." l.H 0.81 1.19 2.15 1.86 2.05 2.77 57 36 7

\ 241 t 1.57 1.60 1.66 1." 2." 2.30 2.'0 3.25 13 19 • 242 t 1.5. 1.61 1.56 1.~7 2.79 2.31 2.80 3.1 S " - 22 11

243 • 1.58 1.67 1.56 '1. 63 2.17 2.37 2.'9 3.11 59 21 10 244 t LU 1.65 1.85 1.76 2.97 2.35 l.eg 3.34 71 14 ~ . 245 ,. {.Ol Ln 2.41 2.12 3.30 2.37 3.71 3.le 92. 4 4

• 246 • 1.62 1.62 1.11 1.70 2.91 2.32 1.01 3.28 li j. 16, 1 • '- 241 51. 0 1. 22 1.43 1.24 1.40 2.51 2.13 2.48 2." 63 0 28 9

241 • 1.36 1.65 1.35 1.44 2.65 2.35 2.59 3.02 S, 32 12 2n H.l 1.13 1.44 LlO 1.31 2.42 2.14 2. J4 2." 56 35 \ 9 ~)~ ... HO 64.1 0.9' 1.11 0.87 1.2. 2.19 1.87 2.11 2.86 " H , 251 t 1.31 1.43 1.15 1. f7 2.U 2.U 2.5' 3.05 61 24 8

:-152 14.2 1.51 1.37 1.84 1.77 2.86 2.07 1.4a 3.35 n • 5 253 14.2 1.86 1.72 2.13 1.'2 3.15 2.42 3.37 3.58 84 9 1 254 14.2 Ln 1.18 l.l2 2.34 2.'9 1.80 U6 3.92 " 1 1 255 14.2 r 1.61 0.97 2.16 2.42 2.90 l.67 4.00 4.00 99 0.5 0.5

25' 14.2 1.84 1.31 2.65 2.27 3.13 2.01 3.89 )..5 n 1 2

251 • 1.15 1. 29 1.19 1.35 2.44 LU 2.U 2.U 61 24 • 2S1 t 1.61 1." 1.63 1.60 2.90 2.56 2.17 3.18 5. 28 14 25' t 1. 36 -1." 1.34 1.41 2.65 2.36 2.51 ~ 3.06 56 33 11 260 64.1 1.06 1.31 1.45 1.32 2.35 2.00 2.29 2.'0 U 11 a

261 51. • 1.11 1.31 1.22 1.35 2.47 , 2.01 2.U 2.93 68 24 a Hl 51.0 Ln 1.5. 1.43 1.52 2,61 2.24 1.57 1.ID " 25 , 20 51.' 0.90 1.11 8.19 1.17 loI' 1.11 2.13 2.15 63 30 7

2U • 1.5. Ln 1.62 1.62 2.79 2.19 2.16 3.20 H 16 • 2'5 14. 2 l.U 1.11 2.22 2.01 2.19 1.11 3.U 3.5' 95 2 2 25' " 14.2 1. '1 LU 2.51 2.20 1.20 2.U 3.82 3.71 " 2 "2

161 • 1.10 1 •• ' 2.13 1.11 2.99 2.19 3.2t 3.U 81 7 5

-0 n. t 1. " 1.71 2.31 2.o, 1.21 2.40 1.61 1.61 ,. S 5

2" • 1.91 1.U 2. )3 2.'5 3.21 2.32 3.57 3.il 91 5 4

n. • 1.13 1.31 1.U 1.31 2.42 2.01 2.38 2.19 ,. 21 , ~,

111

r-

i •

"-"

/' / 11 5",clIllI lUS -------~---... _---------------------_.----.-----_! __ .----------------_._--------~_._-------_._-~----

0 SlIPLI IYlGlTA'IOII UlCOIIICflO 1 COUICUD 1 , fWllIlIlIOI , ClLL lOI flPI l 'IIUAL 1 110 1 GIIII 1 BLUI 1 VllUlL 1 RIO 1 GRill 1 BLUI 1 RIO 1 GRill 1 ILUI

1 ... -------------.. ----------------------------------------------._._----_._----._.----._------_._.-. j .

m 51.0 1.35 1.51 1.40 LU 2.64 2.21 2.H 3," 66 25 , m 51.0 1.30 1.5, 1. 30 1.40 I;- 2.59 2.29 2.54 ua 51 32 11 m 51.0 0.90 1.19 0.16 '1.21 2.i, 1.89 2.10 2.79 - 51 36 7

> m 51.0 1.0' 1.37 1.05 1.29 2.31 2.0J 2.29 2.81 57 34 , 275-' - 1. 70 1.74-' 1. .5 1.72 1.9, 2.44 3.09 3.11 13 17 10 f . m t' 1.50 1.5' 1.61 '1.62 2.79 2.26. Las l.10 13 U • " m 14,2 1.71 1.49 2.15 2.00 3.6, 2.19 /3.19 3.58 90 6 4 ml 1.6, LU 1.94 1.84 2.95 2.16 3.18 3'.42 81 • 5 m- 0.96 1.18 0.95 1.H 2.25 LU 2.19 2.1f 62 31 7 2IO t 1.22 1.50 1. 21 1.36 2.51 2.20 2. 45 1·" ~1 32 11 ,y

m 51.' r 1.11 1.52 1.11 1.34 2.U 2. 22" 2.35, 1.92 52 38 10 lU 5LO 1.03 1.46 0.96 1.29 2.32 2.10 1.20 2.17 51 40 , 28~ : 51.r 0:11 1.13 0.14 1.17 2.li ' 1. 83 2." 2.75 60 33 7 214 51..0 0.81 1,20 0.84 1.23 2.11 1.90 2.08 2.11 5' 31 1 215 51.0 1.16 LU 1.14 1.H 2.45 2.11 2.31 .)..2-'2 5' 32 9 216 51.0 1.04 1.32 1'.02 1.31 2.33 2.02 2. 26 2.89 51 H , 2811 1.49 1.63 1. 55 l.S9 2.71 2.33 2.H 3.11 67 23 iO 118 51.0 1.11 1 •• ' LU 1.31 2.U 2.19 2.38 U5 55 35 18

q lU 51.0 0.90 ,1.09 D.n 1. 22' 2.19 1.79 2.15 UO..r &5 29 , no 51.0 0.93 0' 1.12 0.94 1.24 2.22 1.82 2.18 2.12 H 21 1

.0,

m,t 1.47 2.02 1. 38 1.41 - 2.H 2.12 tU 2." n 45 ' 19 m t 0.91 1.33 0.92 1.21 2.21 2.03 2.16 2." 52 l' ,

.1 -m 51.0 o.,. 1.31 O.H 1.25 2.27 2.01 2.17 2.13 54 38 • "

m 51.0 o ... ·1.14 0.86 1.11 2.17 1.84 2.10 2.75 " )J

2'5 51.0 0.92 1.21 0.'0 1.2f 2.21 l.B 2.14 2.'2 5' 34 1 lm 51.0 1.0. 1.25 1.00 1.31 2.29 1.95 2.24 2.89 U 12 1 m 51.0 1.11 1.43 LU 1.31 2.41 2.13 2.32 U5 5' 36 , HI 51.0 1.12 l.U 1.09 1.34 2.41 2.14 1.33 U2 55 li , 2" 51.1 1.01 1.41 1.13 1.3, 2.36 2.U 2.27 2.U 54 38 • m 51.0 1.01 1.31 " 1.05 1.31 2.31 2.07 2.29 2';5 5. 35 7

,

o 172

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,

1 o

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\ , o

,

;. . \-

• APPÉNDIX B

. . OPTICAL DENSI'TY TO PE'RCENT TRANSMISSION

( CONYERSION TABLE

/

..

. \

173

CONVERSION TABLE ,

Optical. Dcnsity vs. Percent Transmission

-

Q

c: c; c: c: C c: 1: 1: C c: c c Cc g ~ .. ~ 9, - ~ 21 o 0 00 00 o 0 00

::- !:- ë';; .~ f-~ .. -.-

.~ ë .:i.~ ~ .. - .- l:' ..... -.- ~ ë'a'ij oC •• - 1 >- c .... - c: .. - c"''' 1: ....

.... u .. v .. u (J.;: :... 1 Cl'~ Cl CI'- CIl CI'- CI CI':! ~ .;; CI .!.! ~ .;:;;

;; Cl'- :J ;; .... '" .. lit ~.- :\1

c: ~E=I C ~C:=I c ~ E:;: c: ~t::;: . C ~ E:;: c ~E:;: c ~ E;:;: C E; CI (>'ê " 1

III Cl .... U 1 QI CI .. CJ CI CI .. CI III CI ... " <tI " '" " CI o .. CI CI " lit <tI Q 0..51):1 a p" c ~ a p"Ccx a 0.. c 0:: a 0. Co:: Q 0... C oc Cl o.CQ!

Q.oO::: Q o .. o .. o .. o .. 0 .. o ...

~ 01 .. .. ':0 t!:o t!:o ~o ':0 ':0 .... 0

, . 1

,

"n"O 0.50 3 1.6:! 1 00 1O.U:l 1.50 J.li;:! 200 l.~OO 2.50 .U.316:! :1.00 0.1000 3.50 0.0316

0.01 :J1. "';2 0.51 3,) r,o 1 01 :.L -;'; 2 1. ::'1 3.09C 2.01 O. ":72 2 51- 0.3ù~0 301 O.OJ';1 3.51 0.OJ09

~.O 1\5.:J0 0.52 3ü ::0, 1".02 3.5;'0 1.52 3.020 2.0~ 0.9550 2.32 0.30~O J.02 O.O:l5j 3.52 0.0302

0.0 g:; 31 0.53 :9.51 - -r03 9.333 1. 53 2.951 2.0J o .133:1 ::! 53 0.2951 3.03 Q.OUJ3 3.53 0.0295

O.Oi 91 '::J O.5~ 28 Si 1 04 fr. 1::0 . 1.5-1 2.flH-I 2.0~ 0.91 -;0 2 ;'-1 o .jWi)4 J.Of 0.U'31::: 3.54 0.023H

0.05 39.13 0,55 28 13 . 1.05 8.313 1.55 2.818 2.05 0.6913 255 0.:!318 3.05 d.u8'J! 3.55 0.02\39

O.OG 8ï. jQ 0.56 ~7.5i ,LOG 8.710 1.56 2.754 '~6 0.1.710 2.5G 0.2754 3.06 0.OD71 3.56 0.0275

0.07 35 Il 0.5'; :6 !l2 1.07 6 51'1 1.57 0 2.692 2.07 0.ô511 2 51 0.2GJ2 J 07 o O~51 3.57 0.CJ219

O.OS !i3 '13 o 5& ::ô 30 1.03 . tl.318 1 58 2.630 2.08 0.831/3 25& 0,2GJO 3.0C ·0.JG32 3.58 0.0263

O.O~ 31 ~u ~1J.j9 ::!~.jU 1 09 6.126 1 59 ~70 2.0'1 0.8123 2.~9 O.2~iU '3.0J O.\l:'; IJ 3.59 0.0257

o 10 j~J..I3 0.60 2i 12 1.10 7.9-13 1.(;0 2.512 2.10 0.ja4J 2 Gu o 2512 3.10 O.OÎ9~ . 3.GO 0.0251

01lj';7C2 O:C 1 ::' 1 55 1.11 7.7C2 1.61 2.455 :? II U.7762. 2.G 1 0.2~55 J.11 0.Ui76 3.61 0.02-15

012 j',30 (/ G2 :J.~O 1 12 1.50C . l.t2 2.390 2.1~ 0.Î5:;(; :c 62 il 2JCJ) 3.]2 0.0i::.I 3.62 0.0231)

O.IJ i 1 11 O.C3 2J H 1.13 7 -113 1.63 2 H4 2 13 o ';41 J 2 G3 ù.2JH 3.l3 00711 3.53 0.023 ..

0.11 pOt" 1. 064 2291 l.H 7.2H) 1.6-l 2.2~1 2.14 0.7':401 2. fi .. o ::::~I J.14 o 0721 3.6-1 0.0:::') , _ '1"1

0.15 iO. j:) 0.G5 22.39 1.15 7.079 1.65 2.239 2.15 0.7079 :: 65 o.:mo 3.lj O.OiOe 3.65 0.0223 ,'- ,

0.16 CI) 1:; O.Ct> 31 '88 1.16 6:a 18 1.5G 2. 1 III! 2.16 o 6a 18 2 66 0.21G8 3.IG 0.OG<)2 3.66 0.0213

6.17 6i.tFl o 6Î 21.3!i 1 1';' 6761 1.67 2 13S 2.17' 0.(,;'-1 2 ... 7 o 21J~ 3.17 0.0(JJ6 3.67 0.02H

O.IS [, ... Di U.~;; 20.$9 ,1. IG 6607 1.63 2.0t.:.I ~.lG o G&a1 2 û/3 O.:!O8:.1 :i.1:J o ùG',1 3.G8 0.021,;

o l') ,6', 5-;' n (:> ':0 -1:: ,1 19 ô .. 57 1.6C1 2.043 2.10 o fi 157 2.69 0.:'0-12 :J.IJ o aGI6 3.69 O.U~Q"

O.lU b3 :0 a.i l] 1':; 3~ 1 20 ' 6 31 () 1.70 l.995 ~. 2U lI.G3 1 () 2. j'O 0.1:1J5 J..~() ().U 'J.t)JI 3.70 0.01J9

0,21 H. U; ,0.71 19 jO 1.21 6.166 " 1.71 1.950 2.21 O.CICG ·2.71 o J'l50 J.:!I 0.OG17 3.71 0.01'15

o 'i"l 60.20 O.~~ 1!l Oj 1 22 602G 1.72 1.905 2.22 o GO 2(, l. 72 0.1~(}5 3.~~ 0.0&11 3.72 O.OI~'O .-" c

0.23. 5S.[;~ • 0./3 18 G2 1. 23 581:l8 1 i~ 1.b62/; :! 23 0.5U!ib 273 O. WG2 3.n O.OS:;~ 3.13 0.0186

0;:-1 57 5~ O.H Hl 20 i .,. ~.75-f 1 74\ J 1;20 2.::!~ u.:">"j54 2 7-1 O:lR~O 3 24 O.ù~.i j 3.7-1 0.013::! _"i

0.25 ~c 23 0;5 1": 76 1 ::5 5.623 1.75 1.776 2.25 o SU:?3 -275 0.171G 3.:!~ u.05li:!! 3.75 O.UI';'&

0.:!6 5405 O.ïG 173S 1.2G 5 -195 1 7G 1.7-38 2.:!t. 0.5-1% :.! 76 0.1731, 3 26 U.055ù 3.76 0.0174

0.2; 5370 O. j7 16.:Jti 1. 27 53iO 1 71 I.G08 2.2.7 O.537U .! 77 O.lb% 3.:!? u.O;·J1 3.71 0.01G!)

0.2$ 52 .;S o. ;~ 1 (. C') 1. :!n j 2-18 1.';8 1.r.(1) :! 2.'j 0.5:;-!:} ., -. 0.1(.(jlJ 3.:!G U Oj.'J 3.78 0.016G _ Iv

O.:!!> 51 29 U.j~ 1 \., ~.! ' 1. 2~ 5 12J 1.7~ 1.622 2 '}- !l.Sl:!4 ~.iO 0.1622 3.2:> C.OC,IJ 3.79 O.OIG.:! ._J

O.JO SO.I~ o SO Li.ùS 1.30 5.012 1'.6C l.5!l5 2.30 0.501 :! 2 :;0 0.1::'1:5 .>.30 0.0501 3.BO 0.0158

09 48.93 0.81 15.4D 1. 3 J 4 398 1 III l.549 2 :\1 0.~&9S 2.01 0.15.JY J 31 0.0-489 3.81 0.0155

0.32 47 SG 062 15.1-1 1 32 4.786 1.32 1 514 2.:J2 o nSG 2.82 0.1514 3 32 00'';8 3.82 0.015:.!

0.3:1 46 'i7 o L3 1-1.7!l 1.33 4.677 1.83 J.479 2 33 041.377 2.[;3 o 147~ 3:33 0.0';68 3.83 O.OHa

0.3~ ~ 5. 71 O.1\~ l·1.ij 1. 3-1 4.5;1 1.84 1.H5 2.J4 0-1571 2.0; 0.1+15 ;$.34 0.ù.J57 3.84 0.UI .. 5

0.35 -ti.67 o !i5 H.1:; 1. 35 4.41.37 l.ü,:; 1. 413 2.35 U.HG7 2.S5 o 1~13 3.35 D.O·HG 3.85 0.CJ1.J 1

0.36 -13 G:- . tl.36 13.80 1.36 4.3(;5 1.&6 USO 2.3û 0.43G5 2. tl (j o 13~0 3.36 0.#)43G 3.86 0.0138

0.J1 '12 CÜ 0.01 1 J. 4!J 1.37 ~.2GG 157 1.34~ 2 3i iU2LG :.57 0.134:1 3.31 0.0~2IiG ,,3.87 0.0135

0.:.1:; 41.(;) r,.~o 13 III 1. :>8 4 169 1 86 1.318 "'.3(! 0.11(j~ 2 d:;S 0.13W J 33 0.0; 17 3.B8 0.0132

0.39 -tu i-l 0:.;.1 1 2. Sv 1. 39 ~.07~ I.~~ 1. ::'8 233 O • .JO"(-l 2.31 0.12:.;a 3 .l9 0.0-i()7 3.89 0.012(l

().<IO 39.8 J 0.'10 1'::.59 l.-IO J.nl I.~O 1.259 2.N 0.3nl 233 0.125'1 3.40 0.03 )H 3.90 0.0126 <:

0.-11 3G,90 C 91 12.30 J 41 3890 1.91 1.230 :!.41 0.3390 2.91 0.1230 3.41 0.0389 3.!) 1 0.0123

0.42 3û.02 0.~2 1:;:.02 1. -I:! 3.Ga2 1.32 1.202 2.42 0.:.1002 2.92 0.1202 3.n Ô.\J~60 3.92 0.0 !tt)

043' 31:1'> O.Sj Il. .5 1043 3.715 UJ J.115 2.43 0.3715 2.n 0.1175 3.U 0.0371 3.!}3 0.0117

0.-11 3f. JI ù 'l-l 1 I.-lB 1,44 3.631 1.94 1 1-l8 2.44 o ::ô:J 1 2 !}-I 0.1118 3.~.J ù.03v3 3.!H 0.0114

0.45 35.';C 0.9:- 1 J. 22 1.-15 3.5-1<i 1.95 1.122 2.45 0.35-13 2.95 0.1122' 3.~5 0.O3!:15 3.!}~ 0.0 Il~,

O.oJG 34.f.7 0% 1:> l')/j 1.-IG - 0.0109 3.-167 1.96 1 O:JIJ 2.46 0.3-11.37 :!.% 0.1096 3.46 0.0347 3.06

0.,41 33 fS o.or 10.7:? 1.47 3.3GS 1.97 1.072 2.-1; O,:13~~S 2.!>7 0.1072 3.-17 0.0339 3.97 0.0107

OA6 3J.l1 o ~S 10.-17 1.-13 3.31 1 1.98 1.047 2AS 0.3311 298 o.JOn 3.48 0.0331 3.!l3 O;tlIO~

-0 ... 9 3;? .I{. Ü 99 ](1.23 1. -l!l 3.230 1. !)!l 1.02J 2 -19 0.3236 2.9Q 0.1023 3.49 0.03:-1 3.99 0.0102

O.~'O' ~ J.~2 1 00 JO.UU 1.50 3.1 G:! ~.OO 1.000 2. !>:) tl.3'IG2 :1 Où O.IOUO J.f,O 0.031 (j 4.00 0.0100

-174

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APPENDIX C

AIRPHOTO COVERAOE OF AND ·APPLICATION TO THE MARALAL TRANSECT

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175

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Airphoto coverage of the transect was flown ln 1975, at the 1:50 000 scale, over â four week petlod (Table C-l) and f Ive weeks pl lor to one of the Landsat scenes, thereby facliltatlng comparlson.

1 t was not poss lble to pUlchase complete coverage of the area and -50 blocks of photos were to provide a sampllng of aIl the vegetat~on types major transi tion zone5.f\(eeotones) (Figure C-l).

alrphoto selected and the

The alrphotos ~ere partlcularly use fuI ln the as~e8sment of the woody component ln a partlcular sampling

" cell.' In mak,ing the assessment the following method was employed. The position of the sample celi was plotted at scale on a 1:250 000 topographie map of the transect. The flight Ilnes and principal points of the avai)able alrphot03 ~ere also plotted on this map. With the aid of the topographic 'dQtailscshown on the map, the position of the sampl1ng cells were located on the. airphotos. The circumference df the cell (drawn -to scale) ,was outl1ned on the photos where ste;eo coverage was available and only if the whole saruple cell was situated within the area covered by the airphoto.

Since the photos were at the 1: 50 000 scale, direct tree counts wi thin the ce Ils were l)ot poss i bIe, hor was th Is conside~ed necessary given the worklng scale of the analysls (1:1 million), Rather, what was attempted was,an estlmate of f1:he area componênt of the woody elements (trees, bushes and shrubs) exlsting within the samp11ng celle

The estimate was obtalned by prepàr ing a transparent overlay of the sampl1ng celi s~bdlvided Iike a pie-dlagram lnto 16 segments (Figure C-2). This was conslderedt adequate for the type of estimation belng performed. The overlay was positioned under the stereoscope'so that lt covered the sample cel1 under study on one of the photos formlng a stereo-pa ir, A Ze lès mlrror stereoscope wl th four t 1mes magnlfication was used in the analysis, The woody componen,t w1 th!n the partlcular cell was est!mated as a ~ercentage of the total cell area. Each ple-shaped segment of the circie was examined individually and an estlmate was made of the percentage of the segment covered by woody vegetation. When aIl 16 sections had been exam1ned, a total value for the cell was derlved. This value eould then be compared wlth the densltometrlè data 3ince eaeh value i3 an Integration for the whole 5ampl1ng celle The -overlay c'oulÇJ aiso be used 'to estimate indlvidual components wlthin the alrphoto cell since each ple-shaped segment represented 6.25% of- the total area.

. .

176

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FIGURE C-2 lE-SEGMENTS OF THE,AIRPHOTO OVE~LAY

. TABLE Ç-1 AI~~ OTO COVERAGE OF THE MARALAL T~NSECT

Type: Scale: Size: Date: Total Nol.

Panchromatic 1:50 000 23cm x 23cm \ January IFebi~âiy '1975 . of Photos: 100

) .

"

-------------------------------------------~---------------DATE OF ACQUISITION

January' 20

'January 21

Febru-ary 4 1

February 17

FLIGHT LINE·

1602

1606 1'"

1634

1636

1599

PHOTO NO

049 to 054

078 to 081· 124 to 127

Q86 te 087 .060 te 061 155 te 158

130 to:131 137 to 140 149 to 163

023 to 029 --------------------------------~--------------------------

177

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APPENDIX 0

CHANGÉ IN PERCENT TRANSMISSION DATA FOR SAMPLE 'CELLS l - 180 OF THE MARALAL TRANSECT

Landsat Scenes ~962-07052 (March 25, 1975) and 2242-07041 (Se!\tember 21, 1975)

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:.t Denote's' an increase Or decrease in %transmission in thé­filter category as shown

Not possible to çalculate the change because o.f lack of data for one or other scene

179 1

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-31 - 4 137 51.5 • 11

-, - 2 U 51.1 • 3. - 28 - 2 m '67.5 t 1t -. - 2 '4 51.0 • 36 - 30 - 6 1}~ 61.5 • 25 - 20 - 5 U 51.'

• H - 30 -, 140 64.1 i 15 -li - 5

'6 t • 29 -21 • 8

n 41.2 t 31 - 24 - 7 Hl* t 5 -. t l ,. .- 41.2 f 33 - 25 · 8 142· · , - )0 • 1

" 41.2 f 21 - 20 - 1 143 51.0 • 15 - 1l - 2 10. f1.2' + 36 - 29 - 7 144 51.0 + 20 - 11 - 3

145 51.0 + 16 -14 - 2 101 51.0

• 2 - 9

• 7 146 • +11 - 1 - 3 1t2 SU + 21 :'22 t 1 147 67.S • 13

- , - 4 101 51.0 f 20 · 23 t 3 148 n.s • 10 - 16 - . 114 51.0 t 21 - 22 - '1 149 67.5 • 29 - 23 - 6 105 51.0 + 25 -21 - 4 150 t + 28 - 22 - , 1" t + 22 - 16 -, 101 ' 61.5

• 8 · 1 • 1 151 H.O +13 - 13 1

lU 1" 67.S f 22 - 17 - 5 152 1 + 3 - , -- + 3

10' n.s t 19 · 15 - f 153 51.0 + 2 - 4 • 2 Ill' t ,21 - 15 - 6 154 51.8 t , - . - 1

155 5l.G • 10 - 11 • 1 Ul 51.. t 11 -H t 5 156 t +11 - 14 - 3

112 51.0 • 17

· 20 t 3 157 t + 16 - 11 - 5 l ' 113 51.. t 19 -H - 3 158 t t 3 - 2 - 1 '0

114 51.0 t 37 - 30 - 7 159 14.0 liS' • 2. - 22 - 6 HOt + 21 - 23 - 4 11' n.5 • 22 - 17 - 5 ,

117 67.5 t 12 -, - 3 161 . 52.' 0 - 2 + 2 111 n.5 tU -14 - 5 162 t 0 - 3

• 3 lU 67.5 +11, -13 - 4 lU 51.. t 1 - 4 t 3 ni t t 22 -17 - 5 lU 51.0

• 1 - l t 1

US 51.1 0 - 1 t 1

~ 51.. t 7 · 9 t 2 166 51.0 • 11

- , - 2 51:. -, - 5 tH 167 51.1 t 21 - 16 '- 5

. 123 51.0 t 31 • 25 - 6 168 t + 15 - 11 - 4 124 • + 19 - 15 - 4 169 14.1 - 1 ~_, t 1 ~

US n.5 • 13

· 10 - l no tu • 15 - U - 3 lU 67.5

111 //su 127 n.~ t 13 • 11 - 2 t 1 - 3 • 2 U. 67.5 + 7 -, - 1 172 f-- - - 3 • 1 + 2

119 n.5 • 21 · 16 . - 5 173 51.. • 1 - l • 4

" UII • 25 - U - , 114 51.f • l

- 3 + 1 -:-- 175 51.0 t 4 - 5 ' + 1

''PU! 51.' • 11

-11 8 116 51.' + 4 - , • 2 132 51.8 t 30 - 26 - 4 177- t 10 - 10 t

O' ·133 )t..' t le -u - 5 n .. t11 -11 - 1

Ut ~ r - .19 · 15 - 4 119 t • 14

- 10 -. Us t + 12 -, - 3 118 14.1 1 • 1

111 /1

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6

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