Combining satellite imagery and machine learning to predict poverty

Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolut...

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Bibliographic Details
Published in:Science (American Association for the Advancement of Science) Vol. 353; no. 6301; p. 790
Main Authors: Jean, Neal, Burke, Marshall, Xie, Michael, Alampay Davis, W Matthew, Lobell, David B, Ermon, Stefano
Format: Journal Article
Language:English
Published: United States 19.08.2016
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ISSN:1095-9203, 1095-9203
Online Access:Get more information
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