A new empirical model for radar scattering from bare soil surfaces

The objective of this paper is to propose a new semi-empirical radar backscattering model on bare soil surfaces based on the Dubois model using a wide dataset of backscattering coefficients extracted from SAR (synthetic aperture radar) images and in situ soil surface parameter measurements (moisture content and roughness). The retrieval of soil parameters from SAR images remains challenging because the available backscattering models have limited performances. Unfortunately, existing models, physical, semi-empirical or empirical, do not allow for a reliable estimate of soil surface geophysical parameters for all surface conditions. The proposed model, developed in HH, HV and VV polarizations, uses a formulation of radar signals based on physical principles that has been validated in numerous studies. Never before has a backscattering model been built and validated on such an important dataset as the one proposed in this study: containing a wide range of incidence angles (18°-57°) and radar wavelengths (L, C, X), well distributed geographically over regions with different climate conditions (humid, semi-arid and arid sites) and involving many SAR sensors. The results show that the new model shows very good performance for different radar wavelength (L, C, X), incidence angles, and polarizations (RMSE about 2 dB). This model is easy to invert and could provide a way to improve the retrieval of soil parameters.