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| Earth Resources Observation and Science (EROS) |
Work your way through the poster using the imagemap, or use the links below.
Abstract |
Introduction |
Processing |
Special Issues |
Evaluation |
Applications
The result is a raster data product. A graphic representation of the data (figure 6 (50K) is based on shading elevations by color, and blending a shaded relief view. There are 120 of the 30-arc second data points per degree of latitude and longitude. The cell size on the ground is variable, but is roughly 1 kilometer on a side near the equator, and smaller at high latitudes.
The DTED were generalized from a 3 arc second resolution to a 30 arc second resolution by systematic sampling. These data were used directly in the final data set. All of the other data types were processed using Australian National University's Digital Elevation Model (ANUDEM) software. This software iteratively applies a spline interpolation algorithm to the data, resulting in a gridded surface. The algorithm is able to incorporate a stream network data set (without elevation values) and use it to maintain hydrologic consistency in the resulting elevation grid.
Examples of the input data are shown for DTED (figure 2 [17K]), DCW contours, point elevations, and drainage network (figure 3 [33K]), and other sources (figure 4 [33K]).
These other sources include IMW contours and points, AMS contours digitized by Geomatics, Inc., and a river network derived from both DCW and IMW. A 40-percent sample of DTED was used to constrain the interpolation of adjacent areas. Where there were conflicts between data types, we excluded what appeared to be unreliable data (figure 5 [33K]). The data from figures 2 through 4 were combined by ANUDEM to create a DEM of the area (figure 6 [50K]). The results were reviewed in a series of small areas, and then several runs of large areas were made to cover the continent.
The gridding algorithm in ANUDEM can create spurious hills or valleys, especially in areas of little data with very strong relief nearby. In some cases, such as right next to the Andes mountains in Bolivia, the contour data for the mountains were removed, ANUDEM was run, and a portion of the output grid without the spurious hills was then used as input to another ANUDEM run with all of the data included.
Ideally, the accuracy of the interpolation should approach one-half the contour interval of the source data. However, various artifacts are introduced by the processing. For example, if point data occur in an area with little other control, a mound is created around the elevation point. If these points were coded at peaks (as they often are) then the result may be realistic. However, if the points were in a relatively level area, then the mounds provide a misleading representation of the topography, and the elevation of the surrounding area is underestimated.
There is a stair-step effect at contour lines in areas with gradual elevation change. There is a trade-off between horizontal accuracy in matching the contours and vertical realism in expected topographic profiles. The maintenance of horizontal accuracy at the expense of vertical realism was chosen for this project. Users may want to apply post-processing to create more realistic profiles from these data.
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For further assistance, please contact: Customer Services U.S. Geological Survey Center for Earth Resources Observation and Science (EROS) 47914 252nd Street Sioux Falls, SD 57198-0001 Tel: 800-252-4547 Tel: 605-594-6151 Fax: 605-594-6589 Email: custserv@usgs.gov Business Hours: Monday thru Friday, 8:00 a.m. to 4:00 p.m., central time |
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