Core Science Systems
CSS leads USGS’s mission as the civilian mapping agency for the Nation. We conduct detailed surveys and develop high quality, highly accurate topographic, geologic, hydrographic, and biogeographic maps and data. Our maps allow precise planning for critical mineral assessments; energy development; infrastructure projects; urban planning; flood prediction; emergency response; and hazard mitigation.
National Geospatial Program
The National Geospatial Program is the Federal civilian mapping agency and provides the digital geospatial foundation for the Nation. It engages partners and communities of use to collaboratively produce consistent and accurate topographic map data.Learn More
Science Analytics and Synthesis (SAS)
The USGS Science Data Catalog, supported by SAS, provides seamless access to USGS research and monitoring data from across the nation. Users have the ability to search, browse, or use a map-based interface to discover data.Learn More
The holidays are always a busy and sometimes stressful time of year: food to cook, houses to clean, trips to plan, gifts to buy, family to coordinate, the list goes on. So we completely understand that editing data for The National Map Corps might not be high on your list of priorities these days. --*Sigh*
The National Map Corps encourages and leverages volunteer citizen scientists to update structure data to The National Map. To reward, recognize and motivate these participants, the program awards “virtual” badges for increasing levels of edits and submission.
Community for Data Integration fiscal year 2017 funded project report
The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 11 projects funded in fiscal year 2017, outlining their goals, activities, and outputs.Hsu, Leslie; Allstadt, Kate E.; Bell, Tara M.; Boydston, Erin E.; Erickson, Richard A.; Everette, A. Lance; Lentz, Erika E.; Peters, Jeff; Reichert, Brian E.; Nagorsen, Sarah; Sherba, Jason T.; Signell, Richard P.; Wiltermuth, Mark T.; Young, John A.
Automated road breaching to enhance extraction of natural drainage networks from elevation models through deep learning
High-resolution (HR) digital elevation models (DEMs), such as those at resolutions of 1 and 3 meters, have increasingly become more widely available, along with lidar point cloud data. In a natural environment, a detailed surface water drainage network can be extracted from a HR DEM using flow-direction and flow-accumulation modeling. However,...Stanislawski, Larry; Brockmeyer, Tyler; Shavers, Ethan J.
Area-preserving simplification of polygon features
Developing simplified representations of a two-dimensional polyline is an important problem in cartographic data analytics where datasets must be integrated across spatial resolutions. This problem is generally referred to as line simplification, and is increasingly driven by preservation of specific analytic properties such as positional accuracy...Kronenfeld, Barry J.; Stanislawski, Larry V.; Brockmeyer, Tyler; Buttenfield, Barbara P.