Satellite images of lights at night can track how China's provinces grow, but the link between light and income shifts over time and weakens during downturns. Newer satellite data measure economic activity more accurately than older data, especially for industry and services.
Do regional gaps within a country first widen and then narrow as the country gets richer? We find that this inverted-U pattern holds, and that natural resource wealth, farmland, and ethnic inequality are also among the most reliable predictors of regional inequality.
This study constructs a novel subnational GDP dataset for Vietnam by integrating nighttime lights, agricultural land, and climate data through machine learning methods
This paper introduces a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images.
This study explores the potential of higher-quality nighttime light (NTL) data to predict economic activity across various sectors within regions.