NASADEM Global Elevation Model of Earth: Methods for the Refinement and Merger of SRTM and ASTER GDEM
Abstract
NASADEM is a near-global elevation model that is being produced primarily by completely reprocessing the Shuttle Radar Topography Mission (SRTM) radar data and then merging it with refined ASTER GDEM elevations. The new and improved SRTM elevations in NASADEM result from better vertical control of each SRTM data swath via reference to ICESat elevations and from SRTM void reductions using advanced interferometric unwrapping algorithms. Errors in SRTM (due to incorrect interferometric unwrapping) are rare but can be found and removed via a detector that relies upon pattern analysis within synergistic comparisons of SRTM and GDEM. Remnant voids in SRTM are filled primarily by GDEM3, but with removal of GDEM glitches that are mostly related to clouds. GDEM glitch removal uses a measure of curvature and then spatial filtering to detect, isolate, and delete anomalous spikes and pits that are uncharacteristic of natural topography. Water masking uses the original SRTM Water Body Dataset (SWBD), but with errors corrected via a new ASTER Water Body Database. The improved SRTM, GDEM, and water body databases will be made available individually in addition to our merged product, which is particularly important for the SRTM dataset, which stands as a February 2000 baseline for many topographic change studies. New and forthcoming freely available elevation data (at reduced resolutions) from the ALOS PRISM World 3D and TanDEM-X projects will contribute to the critical but not yet reached goal of a complete, high-quality elevation model of Earth, and they are expected to provide additional validation for NASADEM. Indeed, cross validation among all of these datasets is a vital part of reaching that goal. The value of elevation data is difficult to overstate. These data are used in nearly all types of geophysical study conducted at or near Earth's surface.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMIN43B1692C
- Keywords:
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