Stanford researchers use dark of night and machine learning to shed light on global poverty

Stanford Report, February 24, 2016 Stanford researchers use dark of night and machine learning to shed light on global poverty An interdisciplinary team of Stanford scientists is identifying global poverty zones by comparing daytime and nighttime satellite images in a novel way. By Glen Martin Marshall Burke Stanford researchers use machine learning to compare the nighttime lights in Africa – indicative of electricity and economic activity – with daytime satellite images of roads, urban areas, bodies of water and farmland. One of the biggest challenges in fighting poverty is the lack of reliable information. In order to aid the poor, agencies need to map the dimensions of distressed areas and identify the absence or presence of infrastructure and services. But in many of the poorest areas of the world such…


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