An Adaptive Two-Component Model-Based Decomposition on Soil Moisture Estimation for C-Band RADARSAT-2 Imagery Over Wheat Fields at Early Growing Stages.

Huang, X.Q., Wang, J.-G, and Shang, J. (2016). "An Adaptive Two-Component Model-Based Decomposition on Soil Moisture Estimation for C-Band RADARSAT-2 Imagery Over Wheat Fields at Early Growing Stages.", IEEE Geoscience and Remote Sensing Letters, 13(3), pp. 1-5. doi : 10.1109/LGRS.2016.2517082  Access to full text

Abstract

In this letter, we attempt to improve existing model-based decomposition methods to estimate the soil moisture for C-band RADARSAT-2 data. An adaptive two-component decomposition (ATCD) is developed that considers the surface and volume scattering caused by the soil and crop canopy, respectively. The surface scattering adopted is an X-Bragg scattering, with the orientation angle induced by the azimuthal slope under a zero-mean normal distribution function, whereas the volume scattering model is constructed based on the nth power of sine and cosine probability distribution functions. Five sets of fully polarimetric RADARSAT-2 data acquired, in 2013 and 2015, over two study areas, were used to demonstrate the proposed technique, showing that the volumetric soil moisture derived from the ATCD is more consistent with the verifiable ground conditions compared with other model-based decomposition methods.

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