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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: Improvement of Bare Surface Soil Moisture Estimation with L-Band Dual-Polarization Radar

Authors
item Sun, R -
item Shi, J -
item Jackson, Thomas
item Chen, K -
item Oh, Y -

Submitted to: IEEE Transactions on Geoscience and Remote Sensing
Publication Type: Proceedings
Publication Acceptance Date: April 1, 2010
Publication Date: April 1, 2010
Citation: Sun, R., Shi, J., Jackson, T.J., Chen, K., Oh, Y. 2010. Improvement of bare surface soil moisture estimation with L-Band dual-polarization radar. In: Proceedings of the International Geoscience and Remote Sensing Symposium, July 25-30, 2010, Honolulu, Hawaii. VI:971-974.

Technical Abstract: This study demonstrates a new algorithm development for estimating bare surface soil moisture using dual-polarization L-band backscattering measurements. Through our analyses on the numerically simulated surface backscattering database by Advanced Integral Equation Model (AIEM) with a wide range of soil moisture and surface roughness conditions, we found that the relative difference of the overall surface roughness parameters at the different co-polarizations can be well estimated through a roughness index. This new finding leads to an algorithm on estimation of bare surface soil moisture. We will demonstrate the theory and techniques of this algorithm through the AIEM simulated database and validate it with two field ground scatterometer experimental data. The results indicate that bare surface soil moisture can be estimated quite well with only co-polarized backscattering signals. It provides a solid support for Soil Moisture Active and Passive mission (SMAP).

Last Modified: 8/21/2014
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