seamless EDNA database provides 30 meters resolution raster and vector data layers including aspect, contours, filled digital elevation models (DEM), flow accumulation, flow direction, reach catchment seedpoints, reach catchments, shaded relief, sinks, slope, and synthetic streamlines.

Hydrologically conditioned elevation data, systematically and consistently processed to create hydrologic derivatives, can be useful in many topologically based visualization and investigative applications. Drainage areas upstream or downstream from any location can be traced accurately facilitating flood analysis investigations, pollution studies, and hydroelectric power generation projects. For further information including publications, conference proceedings and downloadable posters, see http://edna.usgs.gov.

CEGIS-Funded USGS-wide Research

CEGIS supports interdisciplinary teams of scientists to address GIScience research issues. The CEGIS Research Prospectus supports cross-bureau research on issues that are a high priority for the USGS. The objectives are to support the use of diverse scientific data from multiple sources and to provide new insights to address complex issues; to apply established science tools and techniques to unique and challenging questions; and to foster opportunities to conduct and report collaborative research that can increase the impact of the science CEGIS does. The projects funded in FY 2007 are the following:

  • Scaling, Extrapolation, and Uncertainty of Vegetation, Topographic, and Ecologic Properties in the Mojave Desert

    Principal Investigator (PI)—David R. Bedford; Co-PIs – Leila Gass, Sue Phillips, Jayne Belnap; Collaborator—David M. Miller (Southwest Surficial Processes and Mapping) ($73,000)

  • A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

    PI—Peter Claggett; Co-PIs—Janet S. Tilley, E. Terrence Slonecker (EPA); Collaborator—Bill Jenkins (EPA) ($132,000)

  • Assessing Local Uncertainty in Non-stationary Scale-Variant Geospatial Data

    PI—Susan Colarullo ($117,000)

  • Methods to Quantify Error Propagation and Prediction Uncertainty for USGS Raster Processing

    PI—John Gurdak; Co-PI—Sharon Qi ($134,000)

  • The Geoscience of Harmful Invasive Species: Integrating LANDFIRE and Invasive Species Data for Dynamic and Seamless



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