Monitoring desertification Risk through Climate Change and Human Interference Using Remote Sensing and GIS Techniques

Abstract

The threat of global climate change has radically increased the attention directed towards
understanding the effect on environment and its natural and human induced changes.
Climatic conditions along with certain human activities such as improper agricultural
practices, violent use of fertilizers, overgrazing and other unsustainable practices have
accelerated the conversion of fertile lands into arid lands and this eventually leads to land
degradation and desertification. The term “desertification” indicates land degradation in
arid, semiarid
and dry subhumid
areas resulting from climate variations and human
activity. Stable degradation of vegetation cover is one of the basic characteristics of
desertification process. Changes in vegetation cover of the Churu district of Western
Rajasthan are very clearly detected from long term satellite data and it has been used for
monitoring desertification process. In this paper, long term NOAAAVHRR
(19832003)
data has been used to monitor desertification processes through NDVI timetrend.
The
study is based on the analysis of regional long term changes of vegetation conditions that
indicates the ongoing desertification processes. Vegetation growth is entirely depended
upon rainfall. Here, long term NDVI trend has been analysed corresponding with the long
term annual rainfall (19832003).
It identifies the areas affected by desertification process
as a circumstance of climate change. The results confirmed that some parts of Churu
district is under climatically induced desertification processes.

Full text

INTERNATIONALJOURNALOF GEOMATICSANDGEOSCIENCES
Volume2,No 1,2011
©Copyright2010AllrightsreservedIntegratedPublishingservices
Researcharticle ISSN0976 –4380
SubmittedonJuly2011publishedonSeptember201121
Monitoringdesertificationrisk throughclimatechangeandhuman
interferenceusingRemotesensingandGIStechniques
ArnabKundu
1
,DipanwitaDutta
2
1CentrefortheStudyofRegionalDevelopment,SchoolofSocialSciences,Jawaharlal
NehruUniversity,NewDelhi110067,India.
2IndianInstituteofRemoteSensing,DepartmentofSpace,IndianSpaceResearch
Organisation,Dehradun248001,Uttarakhand,India.
arnknd@live.in
ABSTRACT
Thethreatofglobalclimatechangehasradicallyincreasedtheattentiondirectedtowards
understanding the effect on environment and its natural and human induced changes.
Climatic conditions along with certain human activities such as improper agricultural
practices, violent use of fertilizers, overgrazing and other unsustainable practices have
acceleratedtheconversionoffertilelandsintoaridlandsandthiseventuallyleadstoland
degradation and desertification. Theterm “desertification” indicates land degradation in
arid, semiarid and dry subhumid areas resulting from climate variations and human
activity. Stable degradation of vegetation cover is one of the basic characteristics of
desertification process. Changes in vegetation cover of the Churu district of Western
Rajasthanareveryclearlydetectedfromlongtermsatellitedataandithasbeenusedfor
monitoringdesertificationprocess.Inthispaper,longtermNOAAAVHRR(19832003)
data has been used to monitor desertification processes through NDVI timetrend. The
studyisbasedontheanalysisofregionallongtermchangesofvegetationconditionsthat
indicates the ongoing desertification processes. Vegetation growth is entirely depended
uponrainfall.Here,longtermNDVItrendhasbeenanalysedcorrespondingwiththelong
termannualrainfall(19832003).Itidentifiestheareasaffectedbydesertificationprocess
as a circumstance of climate change. The results confirmed that some parts of Churu
districtisunderclimaticallyinduceddesertificationprocesses.
Keywords: Climate change, Land Degradation, Desertification, Vegetation cover,
NOAAAVHRRNDVI,Rainfall.
1.Introduction
According to Adger et al., (2000) over 250 million people are directly affected by
desertificationandsomeonebillionpeopleinover100countriesareatrisk.India,being
oneofthe leadingdevelopingcountriesof theworld is notexemptedfromtheproblem
related to various natural hazards. Among them,desertification hase merged as a major
economic,socialandenvironmentalprobleminwestern partofIndia.The"GreatIndian
Desert" or Thar, located in Western India, is surrounded by Indus plains in the west,
Aravalli Range in the southeast, Rann of Kutch in the south, and Punjab plains in the
north and northeast. About 91% of the desert, i.e. 2.08 million square km falls in

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
22
Rajasthanwhichcoverabout61%ofthegeographicalareaoftheRajasthan(Sinhaetal.,
2000). Encroachment of the Thar Desert towards its Eastern boarder has become a
seriousproblemtothe adjoiningdistrictsofthedesert. Itisslowlycapturingthe arable
lands by reducing their productivity. A large number of population and animals of this
region are at risk due to shifting of sand dunes, dust storms and as a consequence
decreasing agricultural productivity. To handle the desertification problem, various
programmes were undertaken by Govt. of India. As for example, Desert Development
Program (DDP) started in197778 with the objectives to control desertification, restore
the ecological balance of desert and semidesert areas and create conditions for raising
thelevelofproduction,incomeandemploymentofthepopulationoftheseareas.Inspite
ofseveralattemptstakenbyour Government,thereislackofwellplannedmanagement
and actual information on climate and human induced desertification. It is true that
climateinduceddesertificationisinevitableanddifficulttoprevent.But,itispossibleto
identify the areas exposed to desertification processes and that would be useful for
makingastrategytopreventtheexpansionofthedesert.Differentmethodsofevaluating
desertification include the use of direct observation and measurement, mathematical
models and parametric equation, estimates, remote sensing and indicators (Rubio and
Bochet, 1998). Nowa days, Remote Sensing is the most successful approach for
detecting the long term desertification process and vegetation changes. It is crucial to
identify suitable indicators for monitoring desertification at local, regional and global
scale.TheimportanceofindicatorsinmonitoringdesertificationwasrecognizedbyFAO
and UNEP in the year of 1980 and they proposed 22 indicators in the Provisional
Methodologyfor Assessment andMappingofDesertification.LipingDi,(2003) madea
detailedstudyonrecentprogressofremotesensingonmonitoringofdesertificationand
mentioned that remote sensing is the only tool of choice for desertification studies at
regionalandglobalscale.Remotesensinghasbeensuccessfullyappliedtotheprocessof
monitoring desert expansion and to the assessment of factors that cause desertification
(Hananetal.,1991).Thereisadistincteffectofdesertificationonvegetationcover.The
decreasing trend in vegetation cover indicates the ongoing desertification process in an
area. The Normalized Difference Vegetation Index derived from the long term NOAA
AVHRRdataisanestablishedtechniquefor monitoringlongtermchangesinvegetation
cover.TheNDVIanditsrelationtogreenbiomasswasfirstsuggestedanddemonstrated
byRouseet al., (1973)andTucker(1979).It is one ofthemost widelyused vegetation
indexanditsutilityinsatelliteassessmentandmonitoringofglobalvegetationcoverhas
been well exploited over the past two decades (Huete and Liu, 1994; Leprieur et al.,
2000).Inhisstudy,Zhang(1999)founda strongcorrelation(R
2
=0.73)betweenNOAA
AVHRRNDVIandVegetationcover.Thepresentstudyattemptstoinvestigatetheareas
experiencinglongtermdegradationofvegetationcoverresponsetoclimatechangeinthe
district, Churu. Here, two indicators of desertification have been selected to identify
climateinduceddesertification,oneislongtermrainfallandtheotherisremotesensing
basedindicatorNDVI.
2.Studyarea
The district Churu, situated in the eastern part of the Thar Desert occupies 13,740.95
square kilometres area which is about 12.40 percent of Indian Arid lands exposed to
different forms of desertification processes. It consists of six tehsils namely Sujangarh,

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
23
Ratangarh, Sardarshahar, Churu, Rajgarh and Taranagar. The district is geographically
located in between 27
◦
24’ North to 29
◦ North latitude and 73
◦
51’49” East to 75
◦
40’
20”East longitude (Figure 1). It is enclosed by Mahendragarh and Hissar districts of
Haryana towards east; Hanumangarh district towards north; Nagaur, Sikar and Nagaur,
Sikar and Jhunjhunu districts towards south and south east; and Bikaner in the west.
According to Census of India (2001), the district has 7 towns, 908 villages and a total
populationof19,22,908personswithadensityof123peoplepersquarekm.Thedistrict
encompasses large shifting sand dunes andhas a varying altitude of213 to 400 meters
aboveMeanSeaLevel.
Figure1:StudyArea
Note:DungargarhtehsilisnowadjoinedwithBikanerdistrictofRajasthan
The surface is generally sloping from south towards North and is characterised by
isolated hills which are typical monadnocks on the former peneplain (Sidddiqui, A.R.,
2009).Climaticallytheregionbelongstohyperaridtypeofclimatewithhighdiurnaland
annual range of temperature, scanty rainfall, dry scorching winds and low relative
humidityresultinghigherrateofevaporation.Thiskindofclimatefuelsingeneratingand
transportingofloosesandordustparticles.Theregionrecordstemperaturerangingfrom
below freezing point in the winters to over 50 degrees in the summer afternoons. The

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
24
pattern of rainfall varies spatially; it increases from West to East. The district is
characterizedbysandyto sandyloamcalcareous typeofsoilwhichiscoarse intexture,
lessstructuredwithnegligibleamountoforganicmatter.Asaresultofit,thesubsurface
percolation rate of soil has become higher and the water holding capacity of the soil
profiles have become low (Sidddiqui, A.R., 2009). The spatial pattern of vegetation
shows a great influence of spatial pattern of precipitation over here. Though there is a
poorvegetationcover,theareatowardseastisgreenerthanwest.Largeareasarecovered
with thorny scrubs, grasses with isolated trees. The scarcity of vegetation covers is
strengtheningtheAeolianprocessesandmakingthesanddunesmobile.Theeconomyof
Churuismainlybasedonagricultureandanimalhusbandry.Themajorcropsareoilseeds,
Wheat,Jowar(Sorghum),kharifpulsesandbajra(pearlmillet).
3. MaterialsandMethod
3.1NDVIData
TheNDVIisagoodindicatorofgreenbiomass,leafareaindexandpatternofproduction
(Thinkableetal.2004).Thefundamentalbehindthisindexisthattheinternalmesophyll
structureofhealthygreenleavesstronglyreflectsNIRradiationandleafchlorophylland
otherpigmentsabsorba largeproportionoftheredVISradiation.Thisbecomesreverse
incase ofunhealthyor waterstressed vegetation.NDVI iscalculated bythedifference
betweenreflectanceinnearinfrared(NIR)andvisiblered(VIS)bandofelectromagnetic
spectrum.
NDVI=(NIR−VIS)/(NIR+VIS)
The NDVI value variesbetwee n1.0 to +1.0. Itranges from 0.1 in deserts upto 0.8 in
densetropicalrainforest.TheValuesbetween0and0.1denotesrocksandbaresoiland
less than 1 indicate iceclouds, waterclouds, and snow. The NDVI has been used for
descriptionofcontinentallandcover, vegetationclassificationandvegetationphenology
(Tucker et al. 1985, Tarpley et al. 1984). NDVI derived from Advance Very High
Resolution Radiometer (AVHRR) onboard NOAA is much used for monitoring
vegetation growth and health and assessing desertification (Prince and Justice, 1991;
Tuckeretal.,1991;Nicholsonetal.,1998;Princeetal.,1998;DioufandLambin,2001;
Anyamba and Tucker, 2005; Olsson et al., 2005). NDVI is calculated from channel
1(visible) andc hannel 2(infrared) of AVHRR. In thisst udy, fortnightly GIMMS NDVI
fromNOAA(AVHRR)hasbeenusedforatimeperiodof21years(1983– 2003).This
datawascollectedfromtheNationalOceanicand AtmosphericAdministration(NOAA)
satellitewhichholdsthe AdvancedVeryHighResolutionRadiometer (AVHRR)sensor
andprimarilyoperatedbyUSA.Thesesensorscollecttheglobaldataonadailybasisfor
amultiplicityof land,ocean,andatmosphericapplications.Besidesthese,itisalsoused
to monitor forest fire, analysis of vegetation, weather forecasting, climatic condition,
study of drought, measurement of global sea surface temperature and ocean related
research.TheNDVIisconsideredasa‘greenness’indexinstudiesofdrylandvegetation
cover. It has found that in arid and semiarid regions, NDVI is well correlated with
parameterssuchas leafareaindex,Greenleaf,biomass,vegetationcover,etc.(Nicholson
et al., 1998). In his study, Zhang (1999) also found a strong correlation (R
2
=0.73)
betweenNOAAAVHRRNDVIandVegetationcover.

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
25
Table1: CharacteristicsofNOAAAVHRRsensor
Characteristics NOAAAVHRR
InclinationofOrbit 98.922º
Heightabovesurface 851Km
Numberoforbits/day 14.1
Timesofcoverageatequator
01:41Descending
13:41Ascending
OrbitalPeriod 102min
LatitudinalCoverage 90ºN90ºS
CycleDuration 1Day
GroundCoverage 2842Km
FieldofView(FOV) ±55.4º
InstantaneousFieldofView(IFOV 1.391.51mrad
GroundResolution(Nadir) 1.1Km
NumberofChannels
OneVisible(0.50.7um)
OneNearInfrared(0.71.1um)
OneMiddleInfrared
TwoThermalInfrared
The NDVI data was freely downloaded from the University of Maryland Global Land
Cover Facility Data Distribution Centre (http://www.glcf.umiacs.umd.edu/data/gimms/).
The images were processed by theG lobal InventoryModelling andMo nitoring System
(GIMMS)groupatNASA’sGoddard Space FlightCentre.Forthisresearch,fortnightly
NDVI data was gathered from already processed 15day NDVI composites using the
maximum value compositing procedure to minimize effects of cloud contamination,
varyingsolar zenithanglesand surface topography(Holben, 1986).The Preprocessing
of 15 day composite GIMMSNDVI (1983 – 2003) data was carried out through
followingsteps:
1. ConversionfromGEOtiffformatto.imgformat
2. LayerStacking
3. Reprojection
4. Scaling
5. Subset
TheGIMMS NDVI dataisavailableinGEOtiffformatwhichwerefirstconvertedinto
image format. Then this 15 day composite dataset of 21 years (19832003) has been
stacked. Each stacked layer of all years encloses ten layersrepresenting ten fortnights
(JuneOctober) of growing season. These stacked layers were then reprojected into
AlbersEqualArea ProjectionwithWGS84 datum.Thisprojectionwas chosento keep
the similar pixel size. The following projection parameters are given for Albers Equal
Area Projection for India. Theser eprojected images wererescaled to retain theNDVI
valuerangingfrom+1to1usingthescalefactor0.001.

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
26
ParametersusedforAlbersEqualAreaProjection:
1. SpheroidName:WGS84
2. DatumName:WGS84
3. Latitudeof1stStandardParallel:12ºN
4. Latitudeof2ndStandardParallel:28ºN
5. LongitudeofCentralMeridian:78ºE
6. Latitudeoforiginofprojection:20ºN
7. FalseEastingatcentralmeridian:2000000.0mts.
8. FalseNorthingatorigin:2000000.0mts.
3.2RainfallData
Longterm (19832003) monthly Rainfall data from India Meteorological Department
(IMD) were usedin this study. Monthly rainfall data of growing season( JuneOctober)
were collected from different rain gauge stations scattered in and around of the Churu
district. The rainfall of different months of growingseaso n was thena veraged for each
raingaugestationtoobtainthemeanrainfallofgrowingseason.
3.3Methodology
Thestudywascarriedout aimingto agoaltoidentifyareasundergoingclimateinduced
desertificationprocessesthroughremotesensingbasedindicatorNDVIandclimatebased
indicator rainfall. The data was processed to make it ready for further geostatistical
analysis. After preprocessing of the AVHRRNDVI images (19832003), they were
normalized for regression analysis. The normalization of multi temporal NDVI was
executedusingthefollowingformula:
[(NDVIn*100)+100]
Then, all normalized NDVI images were stacked together. The fortnights of growing
season (JuneOctober) have been taken into account in this study. After stacking, the
fortnightsofgrowingseasonwereintegratedthroughthefollowingequation.
[15/2(NDVIt+2*NDVIt2+2*NDVIt3+…2*NDVItn)]
Here,NDVItindicatesNDVIofeachfortnightofgrowingseason.
Ontheotherhand,meanrainfallofgrowingseasonofeachraingauge stationwastaken
into account from the year 1983 to 2003. The latitude, longitude and mean rainfall of
each rain gauge stations were copied to coordinate calculatort hroughE RDAS Imagine
9.2softwareforinterpolationpurpose.Thenthex,ycoordinates(inputandoutput)were
savedas.datfile.Afterthat, itwasimportedasASCIIfileofpointcoverageto makea

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
27
vectormapofcoordinatesystem.Afterthis, ArcGIS 9.3wasusedtointerpolaterainfall
ofallstations.TheInverseDistanceWeighted (IDW)methodwithpower2wasusedto
makeinterpolationmapofallyears.Sincethismethodassumesthatthingsthatareclose
tooneanotherare more alikethanthosethatarefartherapart.Thenalllayersofrainfall
havebeenstackedandthensubsetofthestudyareawasgenerated.
After preparing thedat abase for the analysis, the correlationco efficients were obtained
from the regression analysis between integrated NDVI and mean rainfall. The analysis
wasdonespatiallyorinpixelbasistoshowthathowfarNDVIofeachpixelisdependent
uponrainfallreceivedbythearea representedbyeachpixel.Itwasperformedbasedon
thelogicthattheNDVIandNetPrimaryProductivityofanareaarestronglydetermined
bytheamountofrainfallreceived.TheNPPvaluesalonemaynotserveasanindicatorof
desertification without taking the rainfall into account (Prince et al., 1998). In arid and
semiarid lands seasonal sums of multitemporal NDVI has found strongly correlated
withvegetationproduction(PrinceandTucker,1986;Prince,1991;NicholsonandFarrar,
1994;Nicholsonetal.,1998;Wesselsetal.,2006).Also,multitemporalNDVIhasbeen
usedbymanyresearchers(Anyamba,Tucker,2005,Herrmannetal.,2005)tofindlong
termvegetation changes.Past researchesdenote that longtermvegetationstress canbe
identifiedbylongtermNDVIdataandthusitcanbeusefulformonitoringdesertification
processes.Forthisreason,atimetrendanalysiswasperformedusingthemultitemporal
integratedNDVItoobservethespatiotemporalpatternofvegetationconditionofChuru
district.ThetemporaltrendofNDVIwascomputedforeachpixelareausinglinearleast
squareregressionover theperiod1983 to2003.Thistechnique representsasimple, yet
robust,wayto reveallongtermtrendsin a temporalsequence ofdatathat departsfrom
the short term annual fluctuations (Hellden, U., Tottrup, C., 2008). The regression and
time trend analysis was performed through in built model maker tool of ERDAS
IMAGINE 9.2 and ENVI 4.7 software. Intersection of time trend map of NDVI and
correlationcoefficient ofrainfallNDVI usedto quantify the areas under theprocess of
desertificationresponsetoclimatechange.
4.ResultsandDiscussion
Severalprevious researches haveproduced a strongpositiverelationshipbetweenNDVI
and rainfall in dry regions all over the world. Although, response of vegetation to
precipitationvariesbetweengeographicalregionsandvegetationtypes(Li,B.etal.,2002,
Li,J.etal.,2004,Nicholsonetal.,1994),mostofthestudiesvotedforprecipitationasa
strongindicatorofvegetation.Thespatialpatternofaverage growingseason NDVI and
rainfallover theperiod19832003hasbeenillustratedinfigure2. Theaveragegrowing
seasonrainfallofpasttwentyoneyear’svariesbetween200500mm.Therainfallmainly
occurs during monsoon and extends from July to September. The spatial pattern of
rainfall shows that it is gradually declining from southeast to northwest. Theaverage
growingseasonNDVIofpasttwentyoneyearshowmoreorlesssimilarspatialpattern.
It has also been decreased from southeast to northwest corresponding with pattern of
rainfallintheregion(figure2).

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
28
Figure2:MeanRainfallandNDVI(19832003)
ThecorrelationbetweenintegratedNDVIandrainfallis illustrated infigure3,revealing
high correlation between the two parameters exists in the Northern part of the district
whereas the South Eastern part surprisingly experiences a reverse condition. These two
distinctcasessaythatthevegetationresponsetorainfallhasbecomemorepronouncedin
the Northern part of the district while there is less impact of rainfall on vegetation
condition of South Eastern region of the district. The areas with significant positive
correlationcoefficientdemarktheclimaticinfluenceonvegetationconditionwhereasthe
areas with negative coefficient indicate intrusion of anthropological factors rather than
climatic factors. The map of correlation coefficient clearly distinguishes two type of
vegetation,oneisinfluencedbyclimateandotherisinfluencedbyhuman.

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
29
Figure3:CorrelationCoefficient(r)betweenintegratedNDVIandRainfall(left);NDVI
TimeTrend(right)
Alteration of vegetation cover can be happened both by climate change and
anthropological activities. To identify the areas under desertification process, the time
trend of growing season NDVI (19832003) was calculated for the district Churu,
illustratedinfigure3(right). The mapdisplays two categoriesofNDVItrends:positive
trendswhichareconsideredto representimprovementof vegetationcoverand negative
trendsindicatingadecliningtrendinvegetationcover.StrongnegativetrendsofNDVIin
some parts of the district suggest degradation of vegetation cover during the past two
decades. On contrary, moderate to high positive trend is also notable over some areas
indicating greening of those areas within last 21 years. Over the entire district, about
52.03% of all pixels experienced a moderate to high declining trends of NDVI while
13.28%ofallpixelsundergoneanincreasingtrendofvegetation(figure4).
About34.69%areaoutofthewholedistricthasastablevegetationcondition(figure4).
The long term degradation of vegetation as monitored by NDVI is an indicator of
desertification (Hill, J., et al, 2008). It is noteworthythat the decreasing or increasing
trend of NDVI as an indicator of desertification is a combined result of climate and
anthropological activities. To detect the areas under climate induced desertification
process, both coefficient mapand time trend map were used. The areasof significant
positivecorrelation between multitemporalNDVI andrainfallwith decreasingtrendof
NDVI,indicatesvegetationdegradationresponsetoclimatechange.Beside this,human
induced desertification is being noticed in the areas of significant negative correlation
betweenmultitemporalNDVIandrainfallwithdecreasingtrendofNDVI.

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
30
Figure4:Areawisedistribution(%)ofNDVItimetrend(left);Measurementofarea(%)
affectedbyclimateinducedandhumaninduceddesertification(right)
Itwasfoundthatabout64.54%ofareaunderdesertificationiscausedbyclimateinduced
processes and 35.46% area is undergone a human induced change of vegetation cover.
Thelongtermclimate induceddegradationofvegetationindicates a slowchangeinthe
patternanddistributionofrainfall.Highevapotranspirationexceedingrainfallalongwith
strong winds is loweringthe soil moisture and making themdry while fine sand grains
blowingfromtheTharDesertslowlyalteringthetextureofsoilanddecliningtheprimary
productivity. Besides this, increasing trend of population pressure also accelerating the
problemofovergrazingandoverploughingwhich madetheareavulnerable.Thestudy
shows,thisarea isgraduallydesertifyingasacomplexconsequenceof bothclimateand
anthropogenicfactors.
5.Conclusions
The results obtained from the study reveals that the NOAA AVHRR data can
successfully monitor and identify areas under the several process of desertification
response to climate change. The correlation betweenNDVI and rainfall is prominent in
some areas of Churu which indicates the strong climatic influence on vegetation
conditionofthoseareas.Bothoftheindicatorscanbeusedinremotesensinginformation
based model for evaluating desertification monitoring and estimation. The NDVI time
trend clearly recognizes the areas with long term vegetation degradation indicating the
ongoing desertification process. The study reveals that more than half of the district is
undergone a declining trend of vegetation cover indicating the ongoing process of
desertification. Within this, about 64.54% area is experiencing desertification due to
climatic processes and 35.46% area is undergone human induced desertification
processes.Also,thisremotesensingbasedtechniquehasbecomehelpfultoidentifyareas
undertheprocessofgreening as animpactofanthropogeniceffect. Thedecliningtrend
in vegetation explicitly supports the information on encroachment of the Thar Desert.
Thestudyrevealsthattheglobalavailabilityofcoarsescale,multitemporaldataarchives
ofNOAAAVHRR have greatpotentialto answerthequestions arrivedfromlongterm
vegetationchanges.
Acknowledgement

MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
ArnabKundu,DipanwitaDutta
InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
31
TheauthorsexpresstheirsinceregratitudeandutmostrespecttoDr.N.R.Patel,Scientist,
Agriculture and Soils Division, Indian Institute of Remote Sensing, Dept. of Space,
Indian Space Research Organisation, Dehradun, Uttarakhand, India for his expert
directionandsupport.
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MonitoringdesertificationriskthroughclimatechangeandhumaninterferenceusingRemotesensing
andGIStechniques
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InternationalJournalofGeomaticsandGeosciences
Volume2Issue1,2011
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andGIStechniques
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Volume2Issue1,2011
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