Soil moisture is a key parameter in numerous environmental studies, including hydrology, meteorology, and agriculture. Soil moisture plays an important role in the interaction between the land surface and the atmosphere, as well as in the partitioning of precipitation into runoff and groundwater storage. Despite its importance, soil moisture has not found a widespread application in the modeling of hydrological and biogeochemical processes and related ecosystem dynamics, in part because soil moisture is a difficult parameter to measure on a large-area, cost-effective, and routine basis.

It is well known that return signals from synthetic aperture radar (SAR) are affected by surface characteristics, such as the roughness, the correlation length, and the dielectric constant of the soil. Some earlier studies (Wang et al. 1986 [1]; Dobson and Ulaby 1986 [2]) using single-frequency and single-polarization Shuttle Imaging Radar-B (SIR-B) imagery could only describe the dependence of backscattering coefficient σ0 on these surface parameters separately. Estimation of surface soil wetness was usually obtained by employing an empirical relationship to convert the measured σ0 into volumetric soil moisture mv (Jackson and Shiebe 1993 [3]). Several research groups have, for example, reported a linear relationship between the observed radar backscatter expressed in decibels (dB) and the volumetric soil moisture of the surface (Schneider ...

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