Researchers use satellite data and machine learning to build poverty map

PALO ALTO, Calif., Aug. 18 (UPI) — Aid groups strategizing about where to deploy resources need accurate information about impoverished populations, but locating those most in need isn’t always easy. Researchers at Stanford University have combined satellite data with machine learning to build a precise map of poverty in Africa. “We have a limited number of surveys conducted in scattered villages across the African continent, but otherwise we have very little local-level information on poverty,” Marshall Burke, an assistant professor of Earth system science at Stanford, said in a news release. “At the same time, we collect all sorts of other data in these areas — like satellite imagery — constantly.” Burke is a fellow at the Center on Food Security and the Environment and a co-author of a new…


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