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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Smos Soil Moisture Validation with U.S. in Situ Newworks

Authors
item Jackson, Thomas
item Bindlish, Rajat -
item Cosh, Michael
item Zhao, Tanjie -

Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: April 15, 2011
Publication Date: N/A

Technical Abstract: Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor using a new technology and for the first time operating at L-band, validation must be conducted to insure quality and support the widespread utilization of the data. In this paper, we contribute to the validation of SMOS using a set of in situ soil moisture networks located in the U.S. These include dense observing networks located within several watersheds and a sparse network distributed across the U.S. Although preliminary, the results of our validation indicate that the SMOS soil moisture estimates are approaching the level of performance anticipated, based on comparisons with in situ data. The overall RMSE of the soil moisture estimates is ~0.06 m3/m3 for the watershed networks. There are bias issues that need to be addressed as well as some outlier responses. Soil moisture results from the ascending and descending orbits are consistent with the in situ observations. The watershed sites are highly reliable and address scaling with replicate sampling. The SMOS algorithms are still being modified and are in calibration/validation phase. It is expected, refinements to the SMOS algorithm will further enhance the soil moisture retrievals. Also, with an increased period of record we expect the analysis to provide more reliable and conclusive results. This analysis will be expanded to include a full annual cycle of observations.

Last Modified: 12/27/2014
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