Multilayer soil model for improvement of soil moisture estimation using the small perturbation method

Kaijun Song; Xiaobing Zhou; Yong Fan

doi:10.1117/1.3277666

1 December 2009 Multilayer soil model for improvement of soil moisture estimation using the small perturbation method

Kaijun Song, Xiaobing Zhou, Yong Fan

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 3, Issue 1, 033567 (December 2009). https://doi.org/10.1117/1.3277666

Abstract

A multilayer soil model is presented for improved estimation of soil moisture content using the first-order small perturbation method (SPM) applied to measurements of radar backscattering coefficient. The total reflection coefficient of the natural bare soil including volume scattering contribution is obtained using the multilayer model. The surface reflection terms in SPM model are replaced by the total reflection coefficient from the multilayer soil surface in estimating soil moisture. The difference between the modified SPM model and the original SPM surface model is that the modified SPM model includes both the surface scattering and the volumetric scattering of the natural bare soil. Both the modified SPM model and the original SPM model are tested in soil moisture retrievals using experimental microwave backscattering coefficient data in the literature. Results show that the mean square errors between the measured data and the values estimated by the modified SPM model from all samples are 5.2%, while errors from the original SPM model are 8.4%. This indicates that the capability of estimating soil moisture by the SPM model is improved when the surface reflection terms are replaced by the total reflection coefficients of multilayer soil model over bare or very sparsely vegetation covered fields.

Citation Download Citation

Kaijun Song, Xiaobing Zhou, and Yong Fan "Multilayer soil model for improvement of soil moisture estimation using the small perturbation method," Journal of Applied Remote Sensing 3(1), 033567 (1 December 2009). https://doi.org/10.1117/1.3277666

Published: 1 December 2009

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