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A time series approach for soil moisture estimation

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dc.contributor.author Kim, Yunjin
dc.contributor.author van Zyl, Jakob
dc.date.accessioned 2006-08-16T17:58:51Z
dc.date.available 2006-08-16T17:58:51Z
dc.date.issued 2006-07-31
dc.identifier.citation IGARSS, Denver, Colorado, July 31, 2006. en
dc.identifier.clearanceno 06-1120
dc.identifier.uri http://hdl.handle.net/2014/39671
dc.description.abstract 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. en
dc.description.sponsorship NASA/JPL en
dc.format.extent 140727 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US en
dc.publisher Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2006. en
dc.subject soil moisture en
dc.subject polarimetric radar en
dc.title A time series approach for soil moisture estimation en
dc.type Preprint en


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