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

Ryan Engstrom, Jonathan Hersh and David Newhouse

The World Bank Economic Review, 2022, vol. 36, issue 2, 382-412

Abstract: Can 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.

Keywords: poverty estimation; satellite imagery; machine learning; big data; inequality (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://hdl.handle.net/10.1093/wber/lhab015 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Poverty from space: using high-resolution satellite imagery for estimating economic well-being (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:wbecrv:v:36:y:2022:i:2:p:382-412.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

The World Bank Economic Review is currently edited by Eric Edmonds and Nina Pavcnik

More articles in The World Bank Economic Review from World Bank Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().