Publication:
Guiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipe

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dc.contributor.authorFisker, Peter
dc.contributor.authorGallego-Ayala, Jordi
dc.contributor.authorMalmgren Hansen, David
dc.contributor.authorSohnesen, Thomas Pave
dc.contributor.authorMurrugarra, Edmundo
dc.date.accessioned2022-10-31T15:08:08Z
dc.date.available2022-10-31T15:08:08Z
dc.date.issued2022-10
dc.description.abstractSocial safety net programs focus on a subset of the population, usually the poorest and most vulnerable. However, in most developing countries there is no administrative data on relative wealth of the population to support the selection process of the potential beneficiaries of the social safety net programs. Hence, selection into programs is often multi-methodological approached and starts with geographical targeting for the selection of program implementation areas. To facilitate this stage of the targeting process in São Tomé and Príncipe, this working paper develops High Resolution Satellite Imagery (HRSI) poverty maps, providing both estimates of poverty incidence and program eligibility at a highly detailed resolution (110 m x 110 m). Furthermore, the analysis combines poverty incidence and population density to enable the geographical targeting process. This working paper shows that HRSI poverty maps can be used as key operational tools to facilitate the decision-making process of the geographical targeting and efficiently identify entry points for rapidly expanding social safety net programs. Unlike HRSI poverty maps based on census data, poverty maps based on satellite data and machine learning can be updated frequently at low cost supporting more adaptive social protection programs.en
dc.identifierhttp://documents.worldbank.org/curated/en/099135010252263269/P176471047cadc0240ba5d08ef8a2bc86b3
dc.identifier.doi10.1596/38222
dc.identifier.urihttps://hdl.handle.net/10986/38222
dc.languageEnglish
dc.language.isoen
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesSocial Protection & Jobs Discussion Paper;No. 2212
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectSOCIAL PROTECTION
dc.subjectTARGETING
dc.subjectMACHINE LEARNING
dc.subjectSATELLITE IMAGES
dc.subjectSOCIAL SAFETY NET PROGRAMS
dc.subjectTARGETING POOR BENEFICIARIES
dc.subjectGEOGRAPHICAL TARGETING
dc.subjectPOVERTY MAPPING
dc.subjectHIGH RESOLUTION SATELLITE IMAGERY (HRSI)
dc.subjectADAPTIVE SOCIAL PROTECTION PROGRAMS
dc.titleGuiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipeen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleGuiding Social Protection Targeting Through Satellite Data in São Tomé and Príncipe
okr.date.disclosure2022-10-26
okr.date.doiregistration2025-05-05T12:09:36.750706Z
okr.date.lastmodified2022-10-26T00:00:00Zen
okr.doctypeWorking Paper (Numbered Series)
okr.doctypeWorking Papers::Social Protection and Labor Discussion Papers
okr.docurlhttp://documents.worldbank.org/curated/en/099135010252263269/P176471047cadc0240ba5d08ef8a2bc86b3
okr.guid099135010252263269
okr.identifier.externaldocumentumP176471-47cadca9-c06b-4d24-ba5d-8ef8a2bc86b3
okr.identifier.internaldocumentum33926091
okr.identifier.report177340
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/099135010252263269/pdf/P176471047cadc0240ba5d08ef8a2bc86b3.pdfen
okr.region.countrySao Tome and Principe
okr.topicPoverty Reduction::Conditional Cash Transfers
okr.topicPoverty Reduction::Services & Transfers to Poor
okr.topicInternational Economics and Trade::Economic Geography
okr.topicScience and Technology Development::Earth Sciences & GIS
okr.topicScience and Technology Development::Technology Innovation
okr.unitSocial Protection AFR E2 (HAES2)
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