Granularity at Scale: Estimating Neighborhood Socioeconomic Indicators from High-Resolution Orthographic Imagery and Hybrid Learning

arXiv:2309.16808v3 Announce Type: replace-cross
Abstract: Many areas of the world are without basic information on the socioeconomic well-being of the residing population due to limitations in existing data collection methods. Overhead images obtained remotely, such as from satellite or aircraft, can help serve as windows into the state of life on the ground and help "fill in the gaps" where community information is sparse, with estimates at smaller geographic scales requiring higher resolution sensors. Concurrent with improved sensor resolutions, recent …

abstract aircraft arxiv basic collection cs.cv cs.cy cs.lg data data collection hybrid images information limitations population satellite scale serve type windows world