SpaceNet has hosted three prize challenges, each focusing on a different aspect of applying machine learning to solve difficult mapping challenges, such as building footprint and road network extraction from imagery. Such solutions have the potential to be honed to power new commercial, academic, and government use cases.” “This enables the entire research and development community to focus on developing solutions to challenging geospatial problems instead of spending time on data acquisition. “SpaceNet is designed to lower the barrier to entry for developers, researchers, and startups to access high-quality geospatial data,” said David Lindenbaum, Principal Engineer at CosmiQ Works. Today, SpaceNet hosts datasets developed by its own team, along with datasets from projects like IARPA’s Functional Map of the World (fMoW).
Prior to SpaceNet there was minimal availability of free, precision-labeled, high-resolution satellite imagery available for computer vision research. SpaceNet, launched in August 2016 as a collaboration between CosmiQ Works, Radiant Solutions, and NVIDIA, is an open innovation project offering a repository of freely available imagery with co-registered map features. Presented at the GEOINT 2018 Symposium, the award recognizes one team that has made an outstanding achievement using geospatial intelligence services, solutions, and technologies. TAMPA, Fla.-(BUSINESS WIRE)-The SpaceNet™ collaborators announced today that they are the recipients of the United States Geospatial Intelligence Foundation's (USGIF) prestigious Industry Achievement Award.
Advancing geospatial deep learning applications with open source high resolution satellite imagery and training data