热门搜索：

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***

AI智能总结

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

点击免费查看完整报告

你可能感兴趣

阿富汗流离失所问题的地理空间分析（英）

你可能感兴趣

柬埔寨：用于人类发展和物流供应的弹性道路可达性的地理空间分析（英）2024

监测解决境内流离失所问题的进展情况：面向发展的指标框架（英）

从数十亿次地理空间天气观测估计气候冲击的宏观财政影响（英）

流离失所地理、难民营和社会冲突

联合国解决国内流离失所问题特别顾问的遗产