Coupling two radar backscattering models to assess soil roughness and surface water content at farm scale

Remote sensing techniques are useful for agro-hydrological monitoring at the farm scale because the availability of spatially and temporally distributed data improves agricultural models for irrigation and crop yield optimization under water scarcity conditions. This research focuses on the surface water content retrieval using active microwave data. Two semi-empirical models were chosen as these showed the best performances in simulating cross and co-polarized backscatter. Thus, these models were coupled to obtain reliable assessments of both soil water content and soil roughness. The use of the coupled model enables one to avoid using roughness measured in situ. Remote sensing images and in situ data were collected between April and July 2006 within the European Space Agency-funded project AgriSAR 2006. Images dataset includes L-band in HH, VV,and VH polarizations acquired from the airborne E-SAR sensor, operated by German Aerospace Center. Results were validated using in situ soil water content and roughness measurements. Results show that reliable assessment of both soil roughness (r2 up to ~0.8) and soil water content (r2 ~ 0.9)can be retrieved in fields characterized by low fractional coverage.