One of the biggest challenges in providing relief to people living in poverty is locating them. The availability of accurate and reliable information on the location of impoverished zones is surprisingly lacking for much of the world. Stanford researchers have found a way to use satellite technology to accurately identify poverty in areas previously void of valuable survey information. The solution involves a sophisticated combination of “nightlight” data—areas that are brighter at night are usually more developed—and daytime data like visible roads, urban areas and farmland. The researchers found that this method did a surprisingly good job predicting the distribution of poverty, outperforming existing approaches.