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Title: SURFACE SOIL MOISTURE RETRIEVAL USING SSM/I AND ITS COMPARISON WITH ESTAR: A CASE STUDY OVER A GRASSLAND REGION

Author
item Jackson, Thomas
item HSU, A - SSAI
item O'NEILL, P - NASA

Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2002
Publication Date: N/A
Citation: N/A

Interpretive Summary: Surface soil moisture estimated from data collected by a coarse resolution satellite sensor operating at a high microwave frequency (Special Sensor Microwave/Imager - SSM/I) were compared to those retrieved from the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) data using the same retrieval algorithm. These comparisons were made using data sets collected as part of the Southern Great Plains 1997 (SGP97) Hydrology Experiment. The results indicated that an error of estimate of 7.81% could be achieved with SSM/I data as contrasted to 2.82% with ESTAR data over three intensive sampling areas of different vegetation regimes. It confirms the results of previous study that SSM/I data can be used to retrieve surface soil moisture information at a regional scale under certain conditions. These results are of value in the development of future satellite instruments as well as extracting useful information from the current SSM/I for hydrology and agriculture.

Technical Abstract: Although Special Sensor Microwave/Imager (SSM/I) is not optimal for soil moisture retrieval, it can under some conditions provide information. Rigorous analyses over land have been difficult due to the lack of good validation data sets. A scientific objective of the Southern Great Plains 1997 (SGP97) Hydrology Experiment was to investigate whether the retrieval algorithms for surface soil moisture developed at higher spatial resolution using truck- and aircraft-based passive microwave sensors can be extended to the coarser resolutions expected from satellite platform. With the data collected for the SGP97, the objective of this study was to compare the surface soil moisture estimated from the SSM/I data with those retrieved from the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) data, the core sensor for the experiment, using the same retrieval algorithm. The results indicated that an error of estimate of 7.81% could be achieved with SSM/I data as contrasted to 2.82% with ESTAR data over three intensive sampling areas of different vegetation regimes. It confirms the results of the previous study that SSM/I data can be used to retrieve surface soil moisture information at a regional scale under certain conditions.