Publication:
Poverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being

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creativeworkseries.issn1564-698X
dc.contributor.authorEngstrom, Ryan
dc.contributor.authorHersh, Jonathan
dc.contributor.authorNewhouse, David
dc.date.accessioned2024-01-17T18:48:34Z
dc.date.available2024-01-17T18:48:34Z
dc.date.issued2021-07-31
dc.description.abstractCan features extracted from high spatial resolution satellite imagery accurately estimate poverty and economic well-being The present study investigates this question by extracting both object and texture features from satellite images of Sri Lanka. These features are used to estimate poverty rates and average expected log consumption taken from small-area estimates derived from census data, for 1,291 administrative units. Features extracted include the number and density of buildings, the prevalence of building shadows (proxying building height), the number of cars, length of roads, type of agriculture, roof material, and several texture and spectral features. A linear regression model explains between 49 and 61 percent of the variation in average expected log consumption, and between 37 and 62 percent for poverty rates. Estimates remain accurate throughout the consumption distribution, and when extrapolating predictions into adjacent areas, although performance falls when using fewer households to calculate estimates of poverty and welfare.en
dc.identifierhttp://documents.worldbank.org/curated/en/099017012082314500/IDU095334dfb00b65041500950f04a9651ccad3a
dc.identifier.citationThe World Bank Economic Review
dc.identifier.doi10.1596/40907
dc.identifier.issn0258-6770 (print)
dc.identifier.issn1564-698X (online)
dc.identifier.urihttps://openknowledge.worldbank.org/handle/10986/40907
dc.languageEnglish
dc.language.isoen_US
dc.publisherPublished by Oxford University Press on behalf of the World Bank
dc.relation.ispartofseriesWorld Bank Economic Review
dc.rightsCC BY-NC-ND 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/igo/
dc.subjectPOVERTY ESTIMATION
dc.subjectSATELLITE IMAGERY
dc.subjectMACHINE LEARNING
dc.subjectBIG DATA
dc.subjectINEQUALITY
dc.titlePoverty from Spaceen
dc.title.subtitleUsing High Resolution Satellite Imagery for Estimating Economic Well-beingen
dc.typeJournal Article
dspace.entity.typePublication
okr.associatedcontenthttps://academic.oup.com/wber/article/36/2/382/6333255 Journal website (version of record)
okr.crossref.titlePoverty from Space: Using High Resolution Satellite Imagery for Estimating Economic Well-being
okr.date.disclosure2024-01-17
okr.date.lastmodified2023-12-11T00:00:00Zen
okr.doctypeJournal Article
okr.doctypePublications & Research
okr.docurlhttp://documents.worldbank.org/curated/en/099017012082314500/IDU095334dfb00b65041500950f04a9651ccad3a
okr.guid099017012082314500
okr.identifier.docmidIDU-95334dfb-0b65-4150-950f-4a9651ccad3a
okr.identifier.doi10.1093/wber/lhab015
okr.identifier.doihttp://dx.doi.org/10.1596/40907
okr.identifier.externaldocumentum34211070
okr.identifier.internaldocumentum34211070
okr.identifier.report186307
okr.import.id2910
okr.importedtrueen
okr.language.supporteden
okr.pagenumber382-412
okr.pdfurlhttp://documents.worldbank.org/curated/en/099017012082314500/pdf/IDU095334dfb00b65041500950f04a9651ccad3a.pdfen
okr.peerreviewAcademic Peer Review
okr.region.geographicalWorld
okr.topicPoverty Reduction::Poverty Diagnostics
okr.topicPoverty Reduction::Poverty Monitoring & Analysis
okr.topicInformation and Communication Technologies::Information Technology
okr.unitOff of Sr VP Dev Econ/Chief Econ (DECVP)
okr.volume36 (2)
relation.isJournalIssueOfPublicationb26f5893-9754-4052-9099-8a165ad8e09c
relation.isJournalIssueOfPublication.latestForDiscoveryb26f5893-9754-4052-9099-8a165ad8e09c
relation.isJournalOfPublicationc41eae2f-cf94-449d-86b7-f062aebe893f
relation.isJournalVolumeOfPublicationdd213de9-52ab-40e9-bb44-86bf0edc81b4
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