An Inversion of a Modified Water Cloud Model for Soil Moisture Content Estimation Through Sentinel-1 and Landsat-8 Remote Sensing Data.

A novel alteration of the Water Cloud Model (WCM) and its inversion is proposed in this research work to improve the accuracy of Soil Moisture Content (SMC) mapping. This paper suggests using the Optical Trapezoid Model as the sole vegetation descriptor in the WCM, as well as the use of a specific configuration of parameters derived from a function of radar frequency, polarization, dielectric particle size, and orientation distribution. The proposed inversion scheme is applied on Sentinel-1 data along with the Landsat-8 images component. The proposed approach achieves higher SMC estimation accuracies compared to those produced by tested methods. Indeed, the designed approach achieved improvements in terms of accuracy as demonstrated by a decrease of Root Mean Square Error values in the order of 0.3% and 0.55% in the Blackwell farms and Sidi Rached study areas respectively.