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

Simple item page
dc.contributor.authorEngstrom, Ryan
dc.contributor.authorHersh, Jonathan
dc.contributor.authorNewhouse, David
dc.date.accessioned2017-12-21T20:28:23Z
dc.date.available2017-12-21T20:28:23Z
dc.date.issued2017-12
dc.description.abstractCan features extracted from high spatial resolution satellite imagery accurately estimate poverty and economic well-being? This paper investigates this question by extracting object and texture features from satellite images of Sri Lanka, which are used to estimate poverty rates and average log consumption for 1,291 administrative units (Grama Niladhari divisions). The features that were extracted include the number and density of buildings, prevalence of shadows, number of cars, density and length of roads, type of agriculture, roof material, and a suite of texture and spectral features calculated using a nonoverlapping box approach. A simple linear regression model, using only these inputs as explanatory variables, explains nearly 60 percent of poverty headcount rates and average log consumption. In comparison, models built using night-time lights explain only 15 percent of the variation in poverty or income. The predictions remain accurate when restricting the sample to poorer Gram Niladhari divisions. Two sample applications, extrapolating predictions into adjacent areas and estimating local area poverty using an artificially reduced census, confirm the out-of-sample predictive capabilities.en
dc.identifierhttp://documents.worldbank.org/curated/en/610771513691888412/Poverty-from-space-using-high-resolution-satellite-imagery-for-estimating-economic-well-being
dc.identifier.doi10.1596/1813-9450-8284
dc.identifier.urihttps://hdl.handle.net/10986/29075
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 8284
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectPOVERTY MEASUREMENT
dc.subjectSATELLITE IMAGERY
dc.subjectMACHINE LEARNING
dc.subjectWELL-BEING
dc.subjectPOVERTY
dc.titlePoverty from Spaceen
dc.title.subtitleUsing High-Resolution Satellite Imagery for Estimating Economic Well-Beingen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titlePoverty from Space: Using High-Resolution Satellite Imagery for Estimating Economic Well-Being
okr.date.disclosure2017-12-19
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/en/610771513691888412/Poverty-from-space-using-high-resolution-satellite-imagery-for-estimating-economic-well-being
okr.guid610771513691888412
okr.identifier.doi10.1596/1813-9450-8284
okr.identifier.externaldocumentum090224b085464805_1_0
okr.identifier.internaldocumentum29284908
okr.identifier.reportWPS8284
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/610771513691888412/pdf/WPS8284.pdfen
okr.region.administrativeSouth Asia
okr.region.countrySri Lanka
okr.statistics.combined9720
okr.statistics.dr610771513691888412
okr.statistics.drstats4851
okr.topicPoverty Reduction::Poverty Assessment
okr.topicPoverty Reduction::Poverty Monitoring & Analysis
okr.topicPoverty Reduction::Small Area Estimation Poverty Mapping
okr.topicScience and Technology Development::Technology Innovation
okr.unitPoverty and Equity Global Practice
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
WPS8284.pdf
Size:
1.96 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description:
Download
Collections
Policy Research Working Papers