A soil moisture algorithm using tilted Bragg approximation

A successful soil moisture algorithm using radar data must identify the soil moisture effect and the surface roughness dependence explicitly since rough surface scattering depends on both the roughness and the dielectric constant of an imaged surface. For bare surfaces, several algorithms have been developed to estimate soil moisture using polarimetric radar data. These algorithms were empirically derived from either experimental data or numerical data instead of starting from rough surface scattering theories. In this paper, we present a soil moisture algorithm theoretically derived using the tilted Bragg approximation. With appropriate approximations using the tilted Bragg theory, we have derived both co- and cross-polarization ratios. Then, a soil moisture algorithm is developed based on these two ratios. This new algorithm is compared with the existing empirical methods using input data from the IEM (Integral Equation Method) an experimental radar data. We also briefly discuss the effect of vegetation on this soil moisture algorithm.