Project and Position Details AI models are increasingly used to map floods, land cover, and urban change from satellite imagery and other geospatial data. But these models can be confidently wrong, and their errors are often concentrated in particular places, such as rural or data-scarce regions, where decisions may matter most. This project develops methods to measure, explain, and correct where and why geospatial AI fails, so that its outputs can be used responsibly.