Measuring intra-urban poverty using land cover and texture metrics derived from remote sensing data

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dc.citation.journalTitleLANDSCAPE AND URBAN PLANNING
dc.contributor.authorDuque, Juan C.spa
dc.contributor.authorPatino, Jorge E.spa
dc.contributor.authorRuiz, Luis A.spa
dc.contributor.authorPardo-Pascual, Josep E.spa
dc.contributor.departmentUniversidad EAFIT. Departamento de Economía y Finanzasspa
dc.contributor.researchgroupResearch in Spatial Economics (RISE)eng
dc.date.accessioned2021-04-12T14:26:14Z
dc.date.available2021-04-12T14:26:14Z
dc.date.issued2015-03-01
dc.description.abstractThis paper contributes empirical evidence about the usefulness of remote sensing imagery to quantify the degree of poverty at the intra-urban scale. This concept is based on two premises: first, that the physical appearance of an urban settlement is a reflection of the society; and second, that the people who reside in urban areas with similar physical housing conditions have similar social and demographic characteristics. We use a very high spatial resolution (VHR) image from one of the most socioeconomically divergent cities in the world, Medellin (Colombia), to extract information on land cover composition using per-pixel classification and on urban texture and structure using an automated tool for texture and structure feature extraction at object level. We evaluate the potential of these descriptors to explain a measure of poverty known as the Slum Index. We found that these variables explain up to 59% of the variability in the Slum Index. Similar approaches could be used to lower the cost of socioeconomic surveys by developing an econometric model from a sample and applying that model to the rest of the city and to perform intercensal or intersurvey estimates of intra-urban Slum Index maps. (C) 2014 Elsevier B.V. All rights reserved.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1174
dc.identifier.issn01692046
dc.identifier.issn18726062
dc.identifier.otherWOS;000347508700003
dc.identifier.otherSCOPUS;2-s2.0-84919675390
dc.identifier.urihttp://hdl.handle.net/10784/28020
dc.language.isoengeng
dc.publisherELSEVIER SCIENCE BV
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84912051604&doi=10.1016%2fj.landurbplan.2014.11.009&partnerID=40&md5=fd50936c3d05954f5d2105bfd6abd061
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/0169-2046
dc.sourceLANDSCAPE AND URBAN PLANNING
dc.subject.keywordIntra-urban povertyeng
dc.subject.keywordSlum indexeng
dc.subject.keywordRemote sensingeng
dc.subject.keywordRegional scienceeng
dc.titleMeasuring intra-urban poverty using land cover and texture metrics derived from remote sensing dataeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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