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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #330158

Title: Challenges in Interpreting and Validating Satellite Soil Moisture Information

Author
item Jackson, Thomas

Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 6/16/2016
Publication Date: 11/1/2016
Citation: Jackson, T.J. 2016. Challenges in Interpreting and Validating Satellite Soil Moisture Information. Soil Science Society of America Annual Meeting. SSSA-ASA-CSSA Annual Meeting 2016.

Interpretive Summary: Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based estimates. One approach is to use data assimilation techniques. It is important in this process to understand not only what the satellite sensor responds to but also how the very complex system is simplified for global implementation. Issues include the radiative transfer model, ancillary data, and dielectric mixing models. An equally important objective is the validation of these satellite products. This always involve the comparison with in situ measurements. The primary limitation has been the number of sites available. In addition, the disparity in spatial scales of the in situ points and the coarse satellite products requires substantial up-scaling efforts. Complicating this is the plethora of instruments and installation designs employed. This presentation will review the approach that has been used by SMAP, the progress to date, and the areas that would benefit from additional research.

Technical Abstract: Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based estimates. One approach is to use data assimilation techniques. It is important in this process to understand not only what the satellite sensor responds to but also how the very complex system is simplified for global implementation. Issues include the radiative transfer model, ancillary data, and dielectric mixing models. An equally important objective is the validation of these satellite products. This always involve the comparison with in situ measurements. The primary limitation has been the number of sites available. In addition, the disparity in spatial scales of the in situ points and the coarse satellite products requires substantial up-scaling efforts. Complicating this is the plethora of instruments and installation designs employed. This presentation will review the approach that has been used by SMAP, the progress to date, and the areas that would benefit from additional research.