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A Research Agenda for Geographic Information Science at the United States Geological Survey D Details of CEGIS-Funded Activities in Fiscal Year 2007 The Center of Excellence in Geospatial Information Science (CEGIS) funds two sets of research activities. The first set includes activities that are considered “in-house” within CEGIS. The second set includes activities that are funded through CEGIS but led by U.S. Geological Survey (USGS) researchers outside CEGIS, in some cases in collaboration with non-USGS colleagues. In-house Activities The information for this section was provided by Steve Guptill, USGS. Automated Data Integration Data integration is a significant problem for The National Map. This project will examine data integration from a layer-based approach, developing a conceptual framework based on resolution, geometric accuracy, and topological consistency, and apply it to five of The National Map data layers—digital ortho-images, elevations, land cover, hydrography, and transportation. From the experience with the layered approach and the data developed, the project will examine a feature approach to integration based on a model previously developed and implemented as a feature library. The team anticipates significant results leading to an automated approach based on the conceptual framework, the empirical results, and the use of these in metadata to drive an automated process. Study Sites
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A Research Agenda for Geographic Information Science at the United States Geological Survey Atlanta, Georgia St. Louis, Missouri Publications and Reports Implementation of The National Map Road Database—from the American Congress on Surveying & Mapping (ACSM) Annual Conference, Nashville, Tennessee, April 2004 Integration of The National Map: Data Layers and Features—from the American Society for Photogrammetry and Remote Sensing (ASPRS) Annual Conference, Denver, Colorado, May 2004 Integration of The National Map—from the XXth Congress of the International Society of Photogrammetry and Remote Sensing, Istanbul, Turkey, July 2004 Integrating Data Layers to Support The National Map of the United States—from the International Cartographic Conference, Coruña, Spain, July 2005 Generalization for The National Map To meet the goals of The National Map the USGS must accept high-resolution data from local, state, and other sources and merge these data into a consistent framework at an appropriate resolution. To the extent possible, this process should be automated, transparent to users, and occur in real time as part of The National Map viewer or the data delivery system. Part of this process will require spatial data generalization. Publications and Reports Generalization for The National Map with emphasis on the NHD—Abstract from the 25th Environmental Systems Research Institute (ESRI) International User Conference, July 25-29, 2005 Estimation of Accumulated Upstream Drainage Values in Braided Streams Using Augmented Directed Graphs—Paper from the Auto-Carto 2006, A Cartography and Geographic Information Society Research Symposium, Vancouver, Washington. June 25-28, 2006 Multiresolution Raster Data for The National Map As science moves toward regional and global analyses with models of climate and human-induced change, methods are needed to project raster data accurately. The approach for this research theme is to use the theoretical and empirical base of knowledge to (1) design a new projection method accounting for raster cell size and latitude effects on accuracy, (2) systematically analyze the error effects and develop error correction procedures, and (3) develop raster
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A Research Agenda for Geographic Information Science at the United States Geological Survey resampling algorithms that use the error analysis and correct for inaccuracies. The project will also leverage results from previous USGS and academic research on projecting raster data to establish the necessary knowledge base for the decision support system and the error correction procedures. Publications and Reports Open-File Report 01-181—Methods To Achieve Accurate Projection of Regional and Global Raster Databases Open-File Report 01-383—–Methods To Achieve Accurate Projection of Regional and Global Raster Databases Projecting Global Raster Databases—Abstract from the Geoinformatics for Global Change Studies and Sustainable Development Conference, Nanjing, China, June 2002 Projecting Global Raster Databases—Paper from the International Symposium on Geospatial Theory, Processing, and Applications Conference, Ottawa, Canada, July 2002 A Comparison of Equal-Area Map Projections for Regional and Global Raster Data Projecting Global Datasets to Achieve Equal Areas—Peer-Reviewed Paper from the Cartography and Geographic Information Science Journal, Vol. 30, Issue 1, Jan 2003 User's Guide to the Decision Support System for Map Projections Accurate Projection of Small-Scale Raster Datasets—Paper from the 21st International Cartographic Conference, 10 . 16 Aug 2003, Durban, South Africa Open-File Report 03-433—Users Guide for the MapImage Reprojection Software Package Open-File Report 2004-1394 User's Guide for the MapImage Reprojection Software Package, Version 1.01 Scientific Investigations Report (SIR) 2004-5297—A Decision Support System for Map Projections of Small Scale Data Re-projecting Raster Data of Global Extent—Abstract from Auto-Carto 2005: A Research Symposium, March 21-23, 2005, Las Vegas, Nevada Building an Ontology for The National Map The current evolving standards for the various themes of The National Map and the historic developments of Digital Line Graph-Enhanced (DLG-E), Digital Line Graph-Feature-Based (DLG-F), and National Hydrography Dataset (NHD) formal specifications provide a cohesive basis for a new ontology that can support The National Map. The existing standards must be cast into the new environment of multiscale representation, near-real-time and web access, and on-demand
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A Research Agenda for Geographic Information Science at the United States Geological Survey product generation. This can only be accomplished with a complete ontology of all features at all possible representation scales as the basis for feature and information retrieval from the multiple databases that comprise The National Map. This project (which starts in 2007) will be the initial step in building such a comprehensive ontology and will use current geographic information science (GIScience) methodologies developed in the ontology of geographic information that have evolved over the last five years. Fractal and Variogram Analysis of Scale and Resolution Effects in Geospatial Data Fractals and variograms are established methods to determine effects of scale and resolution in geospatial phenomena and processes. This project (which starts in 2007) will use these methods to examine the impacts of scale and resolution on data integration and generalization for The National Map and the National Spatial Data Infrastructure (NSDI). Elevation Technology Assessment The evolving private sector capabilities in the elevation technology area, primarily LIDAR (light detection and ranging), are growing at a rapid rate. Multiple states are now in the process of acquiring state-wide coverage and planning for a broad range of statewide applications including floodplain mapping, hydrologic mapping, watershed characterization, vegetation characterization, and structure analysis. In order to incorporate new technological capabilities into the elevation theme’s National Elevation Dataset and non-bare earth elevation features, time must be spent evaluating new developments in the areas of bathemetric LIDAR, full-waveform LIDAR, bare earth processing algorithms, software packages, ground-based LIDAR as an approach to accuracy assessment, and requirements studies. References on this work are listed at http://lidar.cr.usgs.gov. National-Scale Elevation Feature Extraction This project will conduct the research necessary to build a strategy for the nationwide extraction of important elevation derivatives. As the National Elevation Dataset moves more and more to a LIDAR base, and support mounts for a nationwide collection, there is intense interest in the potential high-quality, high-resolution elevation parameters that can improve the flood, fire, landslide and debris flow, storm surge, and water quality and quantity modeling processes. A national approach will unite federal agencies and other partners in the systematic development of this information. Much of this work will be based on existing work with elevation derivatives embodied in the Elevation Derivatives for National Applications (EDNA) database. EDNA is a multilayered database derived from a version of the National Elevation Dataset (NED, documented at http://ned.usgs.gov) has been hydrologically conditioned for improved hydrologic flow representation. The
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A Research Agenda for Geographic Information Science at the United States Geological Survey 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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A Research Agenda for Geographic Information Science at the United States Geological Survey Integration of Raster and Vector Data to Meet Management Needs at Multiple Scales PI—Thomas J. Stohlgren; Co-PIs—Zhi-Liang Zhu, Catherine Jarnevich; Collaborators—Tracy R. Davern, Robert K. Peet (University of North Carolina), James F. Quinn (University of California-Davis), James J. Graham (Colorado State University), Gregory J. Newman (Colorado State University), Kathryn Thomas ($150,000) Mapping Inundation at USGS Stream Gage Sites: A Proof of Concept Investigation PI—James P. Verdin; Co-PIs—Kwabena O. Asante (Science Applications International Corporation [SAIC]), Jerad Bales; Collaborators—Jodie Smith (SAIC), Kristine Verdin (SAIC), Silvia Terziotti ($150,000) GEOLEM: Improving the Integration of Geographic Information in Environmental Modeling through Semantic Interoperability PI—Roland Viger; Barbara Buttenfield (University of Colorado); Co-PIs—Olaf David (Colorado State University/U.S. Department of Agriculture), Charles O’Hara (Mississippi State University); Collaborators––Frank Geter (Natural Resources Conservation Service), Jeff Hamerlinck (University of Wyoming ($150,000).
Representative terms from entire chapter: