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Evaluation of the Oceansat‐1 Multi‐frequency Scanning Microwave Radiometer and its potential for soil moisture retrieval

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The Multi‐frequency Scanning Microwave Radiometer (MSMR) aboard the Indian Space Research Organization—Oceansat‐1 platform measured land surface brightness temperature at a C‐band frequency and provided an opportunity for exploring large‐scale soil moisture retrieval during its two‐year period of operation. These data may provide a valuable extension to the Scanning Multichannel Microwave Radiometer (SMMR) and the Advanced Microwave Scanning Radiometer (AMSR) since they covered a portion of the time period between the two missions. This investigation was one of the first to utilize the MSMR data for a land application and, as a result, several data quality issues had to be addressed. These included geolocation accuracy, calibration (particularly over land), erroneous data, and the significance of anthropogenic radio‐frequency interference (RFI). Calibration of the low frequency channels was evaluated using inter‐comparisons between the Tropical Rainfall Measuring Mission/Microwave Imager (TRMM/TMI) and the MSMR brightness temperatures. Biases (TMI T B >MSMR T B ) of 3.4 and 3.6 K were observed over land for the MSMR 10.65 GHz horizontal and vertical polarization channels, respectively. These results suggested that additional calibration of the MSMR data was required. Comparisons between the MSMR measured brightness temperature and ground measured volumetric soil moisture collected during the South Great Plain experiment (SGP99) indicated that the lower frequency and horizontal polarization observations had higher sensitivity to soil moisture. Using a previously developed soil emission model, multi‐temporal regional soil moisture distributions were retrieved for the continental United States. Comparisons between the MSMR based soil moisture and ground measured volumetric soil moisture indicated a standard error of estimate of 0.052 m 3 /m 3 .
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Document Type: Research Article

Affiliations: 1: Center for Earth Surface Processes in the Cold and Regions, Chinese Academy of Sciences, Lanzhou, China 2: USDA, ARS Hydrology and Remote Sensing Laboratory, Beltsville, Maryland 20705, USA 3: International Institute for Geo‐Information Science and Earth Observation, Enschede, The Netherlands

Publication date: September 20, 2006

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