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David T. Sandwell

Researcher at University of California, San Diego

Publications -  254
Citations -  22699

David T. Sandwell is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Bathymetry & Altimeter. The author has an hindex of 65, co-authored 245 publications receiving 20058 citations. Previous affiliations of David T. Sandwell include University of California, Los Angeles & Royal Dutch Shell.

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Global Sea Floor Topography from Satellite Altimetry and Ship Depth Soundings

TL;DR: In this paper, a digital bathymetric map of the oceans with a horizontal resolution of 1 to 12 kilometers was derived by combining available depth soundings with high-resolution marine gravity information from the Geosat and ERS-1 spacecraft.
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Marine gravity anomaly from Geosat and ERS 1 satellite altimetry

TL;DR: In this article, a combination of high-density data from the dense mapping phases of Geosat and ERS 1 along with lower-density but higher-accuracy profiles from their repeat orbit phases is used to construct gravity anomalies from the two vertical deflection grids.
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Global Bathymetry and Elevation Data at 30 Arc Seconds Resolution: SRTM30_PLUS

TL;DR: A 30-arc second resolution global topography/bathymetry grid (SRTM30_PLUS) has been developed from a wide variety of data sources as discussed by the authors, which is based on a new satellite-gravity model where the gravity-to-topography ratio is calibrated using 298 million edited soundings.
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New global marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic structure

TL;DR: An extinct spreading ridge in the Gulf of Mexico, a major propagating rift in the South Atlantic Ocean, abyssal hill fabric on slow-spreading ridges, and thousands of previously uncharted seamounts are found.
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Biharmonic spline interpolation of geos-3 and seasat altimeter data

TL;DR: In this paper, the amplitudes of the Green functions are found by solving a linear system of equations and the interpolating curve is a linear combination of Green functions centered at each data point.