DocumentCode :
1224599
Title :
A Time-Series Approach to Estimate Soil Moisture Using Polarimetric Radar Data
Author :
Kim, Yunjin ; Van Zyl, Jakob J.
Author_Institution :
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Volume :
47
Issue :
8
fYear :
2009
Firstpage :
2519
Lastpage :
2527
Abstract :
Electromagnetic scattering from a rough surface is a function of both surface roughness and dielectric constant of the scattering surface. Therefore, in order to estimate soil moisture of a bare surface accurately from radar measurements, the effects of surface roughness must be compensated for properly. Several algorithms have been developed to estimate soil moisture from a polarimetric radar image, all with limited ranges of applicability. No theoretical algorithm has been reported to retrieve volumetric soil moisture of a vegetated surface. In this paper, we examine a different approach to estimate soil moisture that exploits the fact that the backscattering cross section from a natural object changes over short timescales mainly due to variations in soil moisture. We develop a model function that expresses copolarized backscattering cross sections (sigmahh and sigmavv) in terms of volumetric soil moisture using L-band experimental data for both bare and vegetated surfaces. In order to estimate soil moisture, two unknowns in the model function must be determined. We propose a viable approach to determine these two unknowns using combined radiometer and radar data. This time-series approach also provides a framework to utilize a priori knowledge on soil moisture to improve the retrieval accuracy of volumetric soil moisture. We demonstrate that this time-series algorithm is a simple and robust way to estimate soil moisture for both bare and vegetated surfaces.
Keywords :
backscatter; hydrological techniques; moisture; polarimetry; radar cross-sections; remote sensing by radar; rough surfaces; soil; surface roughness; synthetic aperture radar; time series; vegetation; SAR; backscattering cross section; electromagnetic scattering; natural object change; polarimetric radar data; rough surface; soil moisture estimation; surface roughness; surface scattering dielectric constant; synthetic aperture radar; time-series approach; vegetated surface; Moisture; polarimetric radar; soil; synthetic aperture radar (SAR); time series;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2009.2014944
Filename :
4810143
Link To Document :
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