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GETECH, University of Leeds, U.K.
GETECH, Stafford, Texas, United States
Corresponding author: jdf@getech.leeds.ac.uk
Editor's note: This article updates TLE's 1998 article "Satellite-derived gravity: Where are we and what's next."
| The first 20% of the full text of this article appears below. |
Converting sea-surface height variations, derived from satellite altimetry, to free air gravity is not new. In the early 1980s William Haxby (Lamont Doherty Geological Observatory) produced the first global marine gravity map from SeaSat satellite altimeter data using interorbital track spacing of about 180 km. Haxby's map had a significant impact on plate tectonic theory because marine free-air gravity data were able for the first time to uniformly image the tectonic fabric of the earth's oceanic crust. Since that time, much effort has been applied to improving satellite-derived gravity resolution. A major advance occurred in 1995, when the altimeter data from Geodetic Missions (GM) of GeoSat and ERS-1 satellites were released. Table 1 gives details of these satellites.
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3 km was achieved at the equator with increasing track density toward the poles. This resulted in a spectacular global marine gravity model developed by David Sandwell and Walter Smith based on the sea-surface height data provided by NASA (GeoSat) and Eurimage (ERS-1). Despite the spatial coverage of orbital tracks being
3 km, it was surprising that the overall resolution of this new data set was no better than
25 km. Could better resolution be achieved?
In 1996, GETECH working with the International Gravity Bureau (Toulouse, France) showed that even after improving and refining processing procedures, only marginal improvements on the
25 km resolution were possible if prepicked sea-surface height data were used. Visual inspection of ERS-1 repeat track data indicated a significant noise envelope. GETECH decided the only way to significantly improve resolution was to repick the sea-surface heights from the "raw" waveform data. This had not previously been done for GM data, due in part to the large data volumes (e.g., ERS-1 GM waveform data
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