Satellite-based remote sensing of soil moisture is generally conducted with active (radar) and passive (radiometer) microwave measurements. During active microwave remote sensing the backscattering from the target i.e, the soil surface is adversely affected by the overlaying vegetation, consequently, sending degraded signal back to the radar sensor. This phenomena greatly compromise with the quality of soil moisture measurements. The proposed research presents an algorithm that averts usage of theoretical and empirical backscattering models. The algorithm uses Soil-Vegetation-Atmosphere-Transfer model for soil moisture estimation that is used to quantify the backscattering components of radar signals. The algorithm has simple and valid assumptions that convert the total radar backscattering equations for a particular temporal scale into a set of simple linear systems. The algorithm reasonably estimates the stochastic surface roughness and vegetation backscattering components.
['N. N. Das', 'Binayak P. Mohanty', 'Eni G. Njoku']
Characterization of Backscatter by Surface Features in L-Band Active Microwave Remote Sensing of Soil Moisture