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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.

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National Geospatial Program

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.

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Science Analytics and Synthesis (SAS)

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.

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News

Date published: October 31, 2018

Favorite Headstones and Mapping

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.

Date published: October 30, 2018

USGS Topo Base Map Refreshed and Other Updates

The “USGS Topo Base Map” service named “USGS Topo” has been refreshed with new data and design changes. In addition, several of the “Data Availability”, or “Data Index” services have new cloud hosted URLs.

Date published: October 19, 2018

Celebrating Geologic Map Day 2018

In celebration of Earth Science Week and Geologic Map Day, the USGS National Cooperative Geologic Mapping Program is highlighting several exciting ongoing and upcoming geoscience-related activities:

Publications

Year Published: 2018

Similarity assessment of linear hydrographic features using high performance computing

This work discusses a current open source implementation of a line similarity assessment workflow to compare elevation-derived drainage lines with the high-resolution National Hydrography Dataset (NHD) surface-water flow network. The process identifies matching and mismatching lines in each dataset to help focus subsequent validation procedures to...

Stanislawski, Larry V.; Wendel, Jeffrey; Shavers, Ethan J.; Li, Ting
Stanislawski, L.V., Li, T., Wendel, J., and Shavers, E., 2018. Similarity assessment of linear hydrographic features using high performance computing. FOSS4G North America. May 14-16, 2018. St. Louis, Missouri.

Year Published: 2018

Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks

Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by...

Stanislawski, Larry V.; Finn, Michael P.; Buttenfield, Barbara P.
Lawrence V. Stanislawski, Michael P. Finn & Barbara P. Buttenfield (2018): Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks, International Journal of Cartography, DOI: 10.1080/23729333.2018.1443759

Year Published: 2018

A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset High Resolution Flowlines

Bathymetric and topobathymetric light detection and ranging (lidar) digital elevation models created for the Delaware River were provided to the National Geospatial Program and used to evaluate synthetic flowpath extraction from bathymetric/topobathymetric lidar survey data as a data source for improving the density, distribution, and connectivity...

Miller-Corbett, Cynthia
Miller-Corbett, C., 2018, A comparison of synthetic flowpaths derived from light detection and ranging topobathymetric data and National Hydrography Dataset high resolution flowlines: U.S. Geological Survey Open-File Report 2018–1058, 29 p., https://doi.org/10.3133/ofr20181058.