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HomeCEGIS Projects ← Multiscale Databases and Resolution

Multiscale Databases and Resolution



Multi-Resolution Raster Data for The National Map

Additional information and project materials

Objective: Research and develop a Web implementation for fast and accurate reprojection and resampling of raster data for The National Map.

History: Originally funded as a 3 year project; the project is now in a second 3 year phase.

Accomplishments: We have implemented the USGS mapIMG software package on a variety of platforms, including Windows, linux, and Solaris. This software package is designed specifically for global projections of raster data, and solves many of the problems inherent in commercial offerings including areal and categorical distortion of raster cells and wrap-around effects. The software includes new categorical resampling methods that allow significantly better preservation of categories when downsampling, and includes a resampler for data of counts, such as population numbers. We have developed an object-oriented version of the General Cartographic Transformation Package (GCTP).

Results and Outputs: We previously have presented and published several papers in refereed journals concerning this effort, which is a continuation of work on projections that began under Prospectus funding several years ago. We have open source software with test datasets available for mapIMG ( https://cegis.usgs.gov/projection/index.html ) and will soon have the object-oriented version of GCTP available to the public from this site.

Planned Future Work: We are proceeding with this project by adapting the mapIMG software and resampling algorithms to datasets for The National Map, developing the capability to apply the software in a Web environment through a Web browser, and incorporating the ability to manipulate regional geospatial data (as is required by a state partner using a specific Universal Transverse Mercator (UTM) zone). We are now examining Open Geospatial Consortium (OGC) compliant software for rapid projection across the Web using grid computing technology.

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Last modified: Wednesday, 22-Feb-2017 16:30:11 EST