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Scientists map poverty with satellite images and AI
Stanford researchers unveil a computer model that matches and in some cases surpasses surveys in predicting poverty using daytime Google Maps imagery and nighttime satellite brightness. Tested in Nigeria, Tanzania, Uganda, Malawi, and Rwanda, the method relates roof material, distance to urban areas, and other features to income data, offering scalable, cost-effective insight for policy.
MENTIONED IN THIS ARTICLE
China
South Korea
North Korea
Stanford
Science
Nigeria
Tanzania
Uganda
Malawi
Rwanda
U.S. Air Force Defense
Neal Jean
School of Engineering
Jean
Joshua Blumenstock
UC Berkeley
Data Science and Analytics Lab