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ABSTRACT
Soil moisture plays an important role in various applications such as hydrology, agronomy, climatology and ecology. Over the past few decades, images acquired by PolSAR (Polarimetric Synthetic Aperture Radar) systems have raised much interest in the remote sensing community. However, only a few studies have analysed the potential use of polarimetric parameters for the estimation of soil moisture. Taking Juyanze as the study area, two feature extraction methods, the simple polarimetric intensity and phase processing, and the polarimetric decomposition were used to extract different polarimetric parameters. The response of single, multiple, and combined polarimetric parameters to bare surface soil moisture was investigated based on linear and non-linear regression strategies in using fully polarimetric RADARSAT-2 SAR (Synthetic Aperture Radar) imagery and field measurements. The results indicate that each individual polarimetric parameter at C-band is not very sensitive to surface soil moisture under this investigation. However, with the increasing number of polarimetric parameters, the correlation between soil moisture and polarimetric parameters improves steadily and the root mean square error (RMSE) and mean absolute error (MAE) decreased gradually. Combined polarimetric parameters have little improvement on the correlation between soil moisture and polarimetric parameters. The non-linear regression method can improve the correlation to some extent. However, the preliminary results so far still do not satisfy the accuracy of using the polarimetric parameters to inverse soil moisture. Further investigations are required in the direction of a better characterization and exploitation of polarimetric SAR data for the retrieval of soil moisture in arid regions.
Disclosure statement
No potential conflict of interest was reported by the authors.