Raster Vision is an open source library and framework for building computer vision models on satellite, aerial, and drone imagery. It provides a full suite of utilities for geospatial deep learning workflows including reading geo-referenced data, training models, making predictions, and writing predictions in geo-referenced formats. As a low-code framework, it enables users to quickly configure experiments for chip classification, object detection, and semantic segmentation with built-in cloud execution support.