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阿富汗流离失所问题的地理空间分析（英）

房地产2023-10-01世界银行欧***

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This Policy Research Working Paper examines the use of geospatial data from remote sensing to monitor displacement flows in Afghanistan. The paper draws on the 2018 drought in northeastern Afghanistan, considered one of the worst in decades, to identify displacement patterns by combining displacement data from the International Organization for Migration's Displacement Tracking Matrix with nighttime lights data. The results suggest that trends in nighttime lights can be used to proxy cumulated displacement movements from 2018 to 2020. This study highlights the potential of remote sensing data in monitoring displacement and could inform the development of robust monitoring systems in conflict and climate change-affected areas.

PublicDisclosureAuthorized PublicDisclosureAuthorized PolicyResearchWorkingPaper10583 GeospatialAnalysisofDisplacementinAfghanistan AnaisDahmani-ScuittiErwinKnippenbergWalkerKosmidou-BradleyJohannaLeeBelanger PovertyandEquityGlobalPracticeOctober2023 PolicyResearchWorkingPaper10583 Abstract Givenincreasinglevelsofdisplacementduetoconflictandclimatechange,itisimportanttoestablishrobustmonitor-ingsystems.Thispaperexploreshowremotesensingdata,particularlygeospatialdata,canbeleveragedtomonitordisplacementflows.ItdrawslessonsfromnortheasternAfghanistan,namelythe2018drought,whichisconsideredoneoftheworstindecades.Theanalysisidentifiesdis-placementpatternsbycombiningdisplacementdatafromtheInternationalOrganizationforMigrationDisplace-mentTrackingMatrixwithnighttimelights.Theresultssuggestthatthecumulateddisplacementmovementsfrom2018to2020canbeproxiedbytrendsinnighttimelightimagery.Settlementswithhighernetinflowsofdisplacedpersonsbetween2018and2020havecomparativelylarger nighttimelightgrowth.Allowingfornonlinearitysuggestsdecreasingmarginalreturnsofdisplacementonnighttimelights,assettlementsshowingthelargestexpansionofnighttimelightsarethosewiththelowestdisplacementinflows.Themodelusesdataonnighttimelightstopredictwhetherasettlementwasanetreceiverofdisplacementflowsduring2018–20andcorrectlyclassifies63.2percentofthesettlementsasnetinflowornetoutflow.Thisstudyprovidesaproofofconcepttotestwhetherpopulationdis-placementscanbeproxiedusinggeospatialdatatrainedonadministrativerecordsinadata-scarceenvironment,wherereal-timeinsightscaninformhumanitarianassistance.ThisworkwasdonebeforethepoliticalcrisisofAugust2021. ThispaperisaproductofthePovertyandEquityGlobalPractice.ItispartofalargereffortbytheWorldBanktoprovideopenaccesstoitsresearchandmakeacontributiontodevelopmentpolicydiscussionsaroundtheworld.PolicyResearchWorkingPapersarealsopostedontheWebathttp://www.worldbank.org/prwp.Theauthorsmaybecontactedatadahmaniscuitti@worldbank.org. ThePolicyResearchWorkingPaperSeriesdisseminatesthefindingsofworkinprogresstoencouragetheexchangeofideasaboutdevelopmentissues.Anobjectiveoftheseriesistogetthefindingsoutquickly,evenifthepresentationsarelessthanfullypolished.Thepaperscarrythenamesoftheauthorsandshouldbecitedaccordingly.Thefindings,interpretations,andconclusionsexpressedinthispaperareentirelythoseoftheauthors.TheydonotnecessarilyrepresenttheviewsoftheInternationalBankforReconstructionandDevelopment/WorldBankanditsaffiliatedorganizations,orthoseoftheExecutiveDirectorsoftheWorldBankorthegovernmentstheyrepresent. ProducedbytheResearchSupportTeam GeospatialAnalysisofDisplacementinAfghanistan AnaisDahmani-Scuitti,ErwinKnippenberg,WalkerKosmidou-Bradley,JohannaLeeBelanger JELClassification:C15,C21,O12,O15,L94,R23 Keywords:migration,displacement,geospatialanalysis,econometricregressions,nighttimelight PolicyStatement Robustmonitoringsystemsarecrucialinhumanitarianinterventions,particularlyinthemostvulnerableareas.Theseareas,pronetonaturaldisastersandrivenbyconflict,areoftenhardtoreach,makingon-the-grounddatacollectionlogisticallydifficult,time-consuming,andexpensive.Thispaperexploreshowremotesensingdata,particularlygeospatialdata,canbeusedtomonitordisplacementflowsinaconflictzoneaffectedbydrought.Usingthe2018droughtinNortheasternAfghanistanasacasestudy,itshowshownighttimelightscollectedbysatellitecanbeusedtoquantifythedisplacementofpopulations.Theseresultscanbeusedtopredictwhetherasettlementwasanetreceiverofdisplacementflowsin2018-2020,providinginsightsthatcaninformhumanitarianassistance. Wedeclarethatwehavenorelevantormaterialfinancialintereststhatrelatetotheresearchdescribedinthispaper.Thefindings,interpretations,andconclusionsexpressedinthisworkdonotnecessarilyreflecttheviewsoftheWorldBankoranyaffiliatedorganizations,itsBoardofExecutiveDirectors,orthegovernmentstheyrepresent.TheWorldBankdoesnotguaranteetheaccuracyofthedataincludedinthiswork.ThisresearchwassupportedthroughtheWorldBankBudget(BB)fortheAfghanistanPovertyandEquityProgramFY21-22aspartofitscoreanalyticalactivities. Correspondingauthor,adahmaniscuitti@worldbank.org Dahmani-Scuitti:WorldBank,Poverty&EquityGlobalPractice,WashingtonDC,USA;Knippenberg:WorldBank,Poverty&EquityGlobalPractice,WashingtonDC,USA;Kosmidou-Bradley:WorldBank,Poverty&EquityGlobalPractice,Dakar,Senegal;LeeBelanger:WorldBank,Poverty&EquityGlobalPractice,WashingtonDC,USA. 1.Introduction Anestimated5.5millionpeoplewereinternallydisplacedinAfghanistaninthesummerof2021,accordingtotheInternationalOrganizationforMigration(IOM,2021).The2020GlobalReportranksAfghanistanamongthetopfivecountrieswithhighlevelsofinternaldisplacementduetoconflictandviolence.ItranksfirstwiththehighestnumberofInternallyDisplacedPersons(IDPs)duetonaturaldisasters(IDMC,2020a,11-12).Importantgeographicdisparitiescanbeobserved,withregionssuchasHerat,Helmand,Badghis,orKandaharhostingmanyIDPs(Figure1).Since2017,350,000–480,000peoplehavebeendisplacedannuallyduetoongoingconflictandviolence(UNOCHA,2020;UNOCHA,2021).Adevelopingdrought

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