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Mapping near-surface soil moisture on regional scale using ERS-2 SAR data
Authors:A Oldak  T J Jackson  P Starks  R Elliott
Affiliation:1. Earth Satellite Corporation , Environmental and GIS Services, 6011 Executive Blvd , Suite 400, Rockville, MD 20852, USA E-mail: aoldak@earthsat.com;2. USDA-ARS Hydrology and Remote Sensing Laboratory , Rm. 104, Bldg. 007, BARC-West, Beltsville, MD, USA;3. USDA-ARS Grazinglands Research Lab , El Reno, OK, USA;4. Oklahoma State University , Stillwater, OK, USA
Abstract:Soil moisture is an important hydrologic variable of great consequence in both natural and agricultural ecosystems. Unfortunately, it is virtually impossible to accurately assess the spatial and temporal variability of surface soil moisture using conventional, point measurement techniques. Remote sensing has the potential to provide areal estimates of soil moisture at a variety of spatial scales. This investigation evaluates the use of European Remote Sensing Satellite (ERS-2) C-band, VV polarization, synthetic aperture radar (SAR) data for regional estimates of surface soil moisture. Radar data were acquired for three contiguous ERS-2 scenes in the Southern Great Plains (SGP) region of central Oklahoma from June 1999 to October 2000. Twelve test sites (each approximately 800?m×800?m) were sampled during the ERS-2 satellite overpasses in order to monitor changes in soil moisture and vegetation on the ground. An average radar backscattering coefficient was calculated for each test site. Landsat-5 and -7 Thematic Mapper (TM) scenes of the experimental sites close in time to the ERS-2 acquisition dates were also analysed. The TM scenes were used to monitor land cover changes and to calculate the Normalized Difference Vegetation Index (NDVI). Land cover and ground data were used to interpret the radar-derived soil moisture data. Linear relationships between soil moisture and the backscattering coefficient were established. Using these equations, soil moisture maps of the Little Washita and the El Reno test areas were produced.
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