Analysis of bitemporelles images to follow-up the flooding phenomenon in the western high plains of Algeria

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Optik139(2017)61–71

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Optik

j o u r n a l h o m e p a g e :w w w . e l s e v i e r . d e / i j l e o

Original

research

article

Analysis

of

bitemporelles

images

to

follow-up

the

ﬂooding

phenomenon

in

the

western

high

plains

of

Algeria

Abdelhalim

Guerroudj

a,b,∗

_,

_Mohamed

_Hadeid

a,d

_,

_Akram

_Seddiki

c a_Geography_Department,_Oran2_University,_Oran,_Algeria

b_Amar_Telidji_University,_Laghouat,_Algeria

c_Geomatics_Laboratory,_Space_Technics_Center,_Arzew,_Algeria d_Research_Laboratory_EGEAT,_Oran₂_University,_Oran,_Algeria

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received31December2016 Accepted13March2017 Keywords: Highplains Floods Spatiotemporal

GeographicInformationSystem"GIS" AnalyticHierarchyProcess"AHP" Estimatedmodel

Urbanspace

a

b

s

t

r

a

c

t

Intheselastdecades,theHighPlainsSteppeofAlgeriahavebeenmarkedbyanintense

degradationaffectingtheland,duetoseveralfactorssuchastheﬂoods.Theproposed

solutionsthatallowtocombatthesephenomenaandretainthenatureoftheseareasremain

inadequateduetotheabsenceofidentiﬁcationmodel,trackingandﬂoodforecasting.

Thisarticleshowstheresultsofthespatiotemporalstudyofparametersthatdeﬁnethe

naturalphenomenageography,inotherwords,itistheﬁrsttimewhere,thefollow-up

spatiotemporalaggravatingfactorstheﬂood,thenseetheireffectsonthemapoftherisk

hazard.

Thealgorithmicdiagramofourstudyfocusesonthedevelopmentandtheapplicationof

techniquesforthepurposeofthecharacterizationandmonitoringofthespatio-temporal

dynamicsofenvironmentalsystemsatthewatershedscale“wadielbiodh”,inorderto

inte-gratethespatialdataandmapsinGeographicInformationSystem(GIS)thatwillallow

toestablishorimplementaforecastingmodelwhichhelpsintheprotectionoftheurban

spaceandtoanticipatetheinterventionoflocalauthorities.

1. Introduction

Themulti-timesatelliteimageryusedtodevelopdynamicﬂoodriskmapsandtrackgeographicallyrisks,thatcontribute indamagesattenuationaccordingtothesedisasters.

Theavailabilityofsatellitedata,therepetitivenessoftheiracquisition,andtheanalysisoftheimagesmulti-temporal havehelpedtoexpandtheapplicationsofremotesensingtoincludethesurfaceearthchangedetectionandthefollow-up ofthedynamicphenomena[4].

Detectionofchangeinremotesensingisaprocessthatidentiﬁesdifferencesstatesofanobjectorphenomenonby carryingoutobservationswithseveraldates.Itessentiallyinvolvestheabilitytoquantifythetemporaleffectsbyusing multi-datedata[2].

Theaimofthisstudyistodevelopaprocessapplicationofcharacterizationtechniquesandmonitoringofthe spatio-temporaldynamicsofenvironmentalsystemsatthewatershed scaleof“wadielbiodh”,thecombinationofGeographic

∗ Correspondingauthorat:GeographyDepartment,Oran2University,Oran,Algeria.

E-mailaddresses:[email protected],[email protected](A.Guerroudj),[email protected](M.Hadeid),[email protected](A.Seddiki).

http://dx.doi.org/10.1016/j.ijleo.2017.03.047

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Table1

Typologyandsourcesofcollecteddata.

Organization/Direction Datatype Properties

TheNationalAgencyforHydraulicResources(ANRH) GeologicalMap e=1/200000 TheNationalInstituteofCartographyandRemoteSensing(INCT) TopographicMap e=1/50000

DirectionofMétéorology DataRaifall Seriesoftenstations(10yearsinterval) EarthScienceDataInterface(ESDI) SatelliteImage(LANDSAT) Spatialrésolution:30(m)

Acquisitiondate:2001,2014(spring)

Fig.1.Analysisandprocessingphases.

InformationSystemGISandtheMulti-criteriaanalysis(MCA),allowsthedecision-makingbydelimitationanddeﬁnition risk’sareaintheorderoftheweightingofthefactorsstudied.

RegardlessoftheuseofGISandtheMCA,thespaceimagesclassificationisessential,techniquesofanalysis,position classificationofimagesresultingthematicallowtoseethechangeineachparameterdefiningtherisk.

Finally,inordertohaveacorrectandaccuratedecision,thedynamicmapsweredevelopedbycombiningamultisource data,allowtomakeacomparativestudytakingintoaccountallobtainedresults.

2. Methodology

Inordertoachieveourobjectives,athree-phaseapproachwasdeﬁned.Duringtheﬁrstone,wehavecollectedthe necessarydatafromdifferentinstitutionsandservices“Table1”.Foreachtypeofdata,weappliedapreliminarytreatment asrequiredGIS/MCAintegrationformats(SpaceTechnicsCenter,ANRH,INCT,MeteorologyDepartment).

Theextractionoftheinformationaboutthechangeofthefactorsstudiedbythetimeisthesubjectofthesecondphase bytheapplicationofthemethodsofdetectionofchangesqualitative/quantitativeandtheinterpretationoftheresultsofa temporalspaceof13years.

TheﬁnalphaseusethespatialanalysistechniquesandMCAtodevelopthegeographymapsofthehazardﬂoodrisk duringthetwodates2001and2014,theinterpretationandreadingofthemapsmustbedonebyacomparisonwiththe previousphaseresults(Fig.1).

2.1. Choiceofstudyarea

Inoursituation,thechoiceofthestudyareaisstipulatedbytheavailabilityofnecessarydataforthepracticalrealization oftheprojectontheonehand,ontheotherhandtheareathatwehaveselectedisanareaaffectedbytheﬂoodinOctober 2011andin1953accordingtothehistory.

ElBayadhisamunicipalityinthewilayaofElBayadh,whichitisthechief-town,located370kmsouth-eastofOran, 520kmsouth-westofAlgiersand500kmnorth-eastofBechar.Itcoversanareaof463.50km2_._The_population_is_estimated at120,948inhabitantsaccordingtotheGeneralCensusofPopulationandHabitat2015(Fig.2).

2.2. Pretreatmentsandcombinationofimagedata

TheyareclassiﬁedintheTable1,thesetofdatacollectedbasedoftheirtypologyandtheprovideragency. 2.2.1. Realizationofthelandusemap

ForLandsatTMimages,radiometrycorrectionhasbeenappliedtoimprovethecontrastthatisnecessaryforthechoice oftrainingsitesinthesupervisedclassiﬁcation.Thetypeofradiometriccorrectionislinearstretch.

Theimagewasre-projectedfromWGS84systemtotheNorthSahara1959UTMsystem.

Afterthegeometricandradiometriccorrection,theimagewasclassiﬁed,byapplyingthemaximumlikelihoodalgorithm toidentifyfourmainclasses:soil,vegetation,urban,career(Fig.3).

2.2.2. Analysisofvegetationcover

TheNormalizedDifferenceVegetationindicatoris“NDVI”anindicatorthatidentiﬁesthevegetationobject,basedonthe redandnearinfraredchannelimageTM.Intheprocessofrealizationofﬂoodriskmaps,itisusedasaninformationlayer onplantsandnon-plantareas(Fig.4).

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A.Guerroudjetal./Optik139(2017)61–71 63

Fig.2. LocationoftheStudyarea.

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Fig.4.ObjectvegetationmasksbycalculationofNDVI2001andNDVI2014indices.

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Fig.6.GeologicalmapofEl-Bayadhmunicipality.

2.2.3. Studyofthetopography

Theslopesofthemapisanessentiallayerinnaturalhazardsstudies,thefactthatitdeﬁnedtheﬁeldtopographyinthe formofclasses.InourcasethemapwascreatedbasedonaDTMafterimprovement.

ThenumericalmodeloflandacquiredistheGtopo90notcharacterizedbyits30msamplingandprecisionvariable altitudemeasurements.Forthis,wefollowedaprocessofimprovingitsinformationqualitythroughtheintegrationof contourlinesandspotthetopographicmap.Similarly,improvedproducthasbeenre-projectedfromWGS84systemtothe NorthSahara1959systemtogeneratetheslopemap(Fig.5).

2.2.4. Extractionofgeologicalinformation

WeextractedthegeologicalmapwhichcorrespondstotheextentofthemunicipalityofEl-Bayadh,thisextractionhas allowedustoidentifyrocksgeologicalunitscomponents.

Afterextraction,wehavetakeninformationfromgeologistsscientistsaboutthepropertiesorthesensitivityofthese rockstotheﬂood.

theseinformationwasusedascriteriatoclassifythegeologicalmapaccordingtothesubjectstudy(Fig.6). 2.2.5. Realizationrainfallmap

Afteranalyzingtheseriesofmeteorologicalobservations,wemadestatisticalcalculationstoapplylateraninterpolation algorithmofrainfallmeasurementsfromtenstations:El-Bayadh,Naama,AinSefra,Laghouat,HassiR’Mel,Ghardaia,Saida, Tiaret,BecharandAdrar(Fig.7).

2.3. Changedetectionbysatelliteimagery

AfteranalyzingdataontheOued-El-Bayadhpool,wechosetoworkﬁrstonthelandcoverchange,evolutionordegradation andhowwillinﬂuencetheriskmapping?

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Fig.7.Generationofrainfallmap.

Table2

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Fig.8. MergingofNDVI2001andNDVI2014indices.

Thisphase isnota comparativestudyinthesenseofalgorithmicstudybut ratheranapplication ofqualitativeor quantitativedetectionalgorithmstoensuretheinformation.

Thereareseveralchangesofdetectionmethodsintheliterature[1–3],forourcase,weusedtwomethods:Methodmelt indices,andComparisonmethodpost-classiﬁcation.

2.3.1. Fusingindexmethod

Thevegetationindexusesthevegetationspectralsignature(veryhighinfraredreﬂectanceandverylowcloseinred), thisindexisarelativelyreliableindicatorofchlorophyllactivityofvegetation[5].

Weappliedtreatmentonvegetationindicescalculatedfromourbi-temporalimages.

Theinterpretationoftheresultsobtained“Fig.8”hasallowedustoidentifyvegetation(newandold)inacomprehensive manner.

Thismethodoffusionhastheadvantageofquantifyingchange,althoughtheaccuracyisnotbetterbecausethe quantiﬁ-cationisdoneonthebasisofamanualthresholdingofthetwoindices.

Theappliedsolutionhaslimitationsasregardsthechangedetectionforobjectsofsmalldimensions. 2.3.2. Post-classiﬁcationanalysesmethod

Post-classiﬁcationcomparisonmethodsprovideinformationaboutthenatureofthechanges,andhavetheadvantageof comparingobjectclassesinpairs,whichmakesiteasiertoextractchangesaccurately[3].

Thestatisticalanalysisoftheresultsoftheclassiﬁcationsofthebothdatesmakesitpossibletoestimaterelatively (classiﬁcationaccuracy–thematicconfusion)therateofchangebetweenthetwodates.

Forthepaircomparison,theresultobtained“Fig.9”forclassiﬁcationsoffourclasses:soil,vegetation,quarry,andurban, comprises16combinationsofclasses.

Thecomparisonapproachofclassiﬁcationsrequires havinggoodresultsofﬁeld trips.Theproblemofomissionand shadowmaydistorttheinterpretationofcertainobjects(Fig.10).

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Fig.9.Resultsofcomparedpostclassiﬁcation.

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Thechangedetectionmethodsappliedinthisphaseshowasigniﬁcantchangeespeciallyontheturfofthemunicipality ofElBayadhinanintervalof13years,ourgoalisnottoinvestigatethecausesofthischange,butviewisthatthischange affectstheﬂoodhazardmapandhowtointerpretthischange?

2.4. Mappingﬂoodhazard:approachandanalysisresults

Theknowledgeofthefactorsaggravatingtheﬂoodinghazardandtheperiodicmonitoringoftheirvariations,increase ourunderstandingofthephenomenon,alsoallowsustoidentifyareaslikelytobehitbyﬂoodinganddeterminetheirdegree ofrisk.

2.4.1. Mapselabortation

WehaveselectedtheMCAalgorithmAHP(AnalyticalHierarchyProcess)tomergedatawithadvancedweightingforthe developmentofﬂoodriskmap.TwotypesofpretreatmentsareappliedbeforeintegratethemintotheGISprocessontwo levels:

• Firstlevelontheanalysisofdataacquiredaccordingtotheirgeometricalproperties,scales,resolutions. • Thesecondlevelisanadvancedlevel,istocreatethematicmapsandmappingofﬂoodrisks.

Theﬂoodriskmapobtainedbyfusionisarepresentationbyclassesthatshowthedegreeofrisk,butalsoarepresentation ofheterogeneousmergedpixelswhichmakesinterpretationdifﬁcultfornon-experts.Tosolvethisproblem,wehavechosen spatialunitsofgeographicalintegrationwhicharethewatershedboundaries.

“Fig.11”showstheresultofthespatialmulti-criteriacombinationbyintegratingofriskinformationbywatershed. bythelectureoftheMapsoftwodatesshow5classeslandsthatdifferintermsofrisk,inotherwords,itrepresentsa decision-makingmapatthemunicipallevelwherethelandsareclassiﬁedandidentiﬁed.

2.4.2. Comparativestudyandanalysisofresults

Thechangesaredetectedandriskmapsareestablished,wenowlookingfortherelationshipbetweenthechangeinthe riskmapbetweenthetwodatesandthechangeofthelandmapandtheNDVI.

twosampleswereselectedtoﬁndthelinksandchecktheinﬂuenceoftherecordedchanges,thecomparativeanalysis ofthetwosamplesisshowninTable2.

Intheﬁrstsampleandfromtheindexmeltingresult,degradationofvegetationisverynoticeable,whichisthesame resultobtainedbyanalysisposteclassiﬁcation,changeofthevegetationinground.

Thischangehasincreasedtheriskofﬂoodingbypassingfromhighclasstoveryhighriskclass.

Ontheotherhandinthesecondsample,fromtheresultoftheindexmelting,degradationofvegetation,thisresult isconﬁrmedbytheanalysispostclassiﬁcationchangedetectionmethod,thathasbeenappliedinwhereachangeofthe vegetationingroundhasbeendetected.

Theeffectofthischangerepresentedintheﬂoodriskmapbyconvertingthemeanclasstothehighclass.

3. Conclusion

Themainobjectiveofthisresearchwasinfirsttimetoanalyzetheriskgeographically(istosay)i.e,identifytheparameters thatincreasestheriskoffloodinginasteppezoneElbayadh(NorthWestAlgeria)whichisanareaaffectedbytheflooding inOctober2011.

Theuseofmulti-criteriaanalysisandGIS,combinestheseparameterstoachievetheﬂoodhazardmapswithouttaking intoconsiderationthereturnperiod,theimplementationofsuchamap,despiteitsdifﬁculty,doesnotmakearealproblem, butitistostudytheparametersthatcanchangeoverthetime.

Inordertochangedetection,weusedthegivenmultidates-TM(2001and2014)whosepurposewasmonitoringthe evolutionofthefactorsincreasingorattenuatingthephenomenonstudied.

Thestudyofchangealsoallowedustoidentifyareaslikelytobeaffectedbyﬂoodinganddeterminetheirdegreeofrisk. Acomparisonofthehazardmapswasmadesubsequentlytothelink:riskfactor&decisionmaking.

Weestimatethattheresultsofthisworkcouldformasupportofaiddecisionintermsofprevention,forecasting,and protectionofareasagainstthethreatofﬂooding.

Theresultsofthismapping(ofﬂoodhazardmap)arerepresentedschematicallybyasimplewayandallowtodifferent actors(users)intheﬂoodriskmanagementframe,usingthemtoknowhowtomanagetheterritorybeforeandafterthe crisis.

Appliedchangedetectionmethodsshowasigniﬁcantchangeespeciallyinthesward.Thischangecorrespondinthe hazardmaptoaconversionofriskclasses.Achangethatmustbetakenintoaccountbydecisionmakersinthedevelopment projectsandurbanplanningtocreateofnewurbanareas.

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