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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 MoreScience 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 MoreNews
President Proposes $983 Million FY20 Budget for USGS
Budget Focuses on Priorities Supporting American Energy Enterprise, National Security, and Natural Hazard Response Efforts
New Species Habitat Distribution Maps Now Support Conservation Planning at a National Scale
A new dataset of habitat distribution for terrestrial vertebrate species in the conterminous United States is now available from the USGS.
USGS 3DEP Lidar Point Cloud Now Available as Amazon Public Dataset
The USGS 3D Elevation Program (3DEP) is excited to announce the availability of a new way to access and process lidar point cloud data from the 3DEP repository.
Publications
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.