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A Time Series Approach for Soil Moisture Estimation

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2 Author(s)
Yunjin Kim ; Jet Propulsion Lab. California Inst. of Technol., Pasadena, CA ; Van Zyl, J.

Soil moisture is a key parameter in understanding the global water cycle and in predicting natural hazards. Polarimetric radar measurements have been used for estimating soil moisture of bare surfaces. In order to estimate soil moisture accurately, the surface roughness effect must be compensated properly. In addition, these algorithms will not produce accurate results for vegetated surfaces. It is difficult to retrieve soil moisture of a vegetated surface since the radar backscattering cross section is sensitive to the vegetation structure and environmental conditions such as the ground slope. Therefore, it is necessary to develop a method to estimate the effect of the surface roughness and vegetation reliably. One way to remove the roughness effect and the vegetation contamination is to take advantage of the temporal variation of soil moisture. In order to understand the global hydrologic cycle, it is desirable to measure soil moisture with one- to two-days revisit. Using these frequent measurements, a time series approach can be implemented to improve the soil moisture retrieval accuracy.

Published in:

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Date of Conference:

July 31 2006-Aug. 4 2006