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The radar signal recorded by earth observation (EO) satellites is sensitive to soil moisture and surface roughness, which both influence the onset of runoff. This paper focuses on inversion of these parameters using a multi-angular approach based on RADARSAT-1 data with incidence angles of 35° and 47° (in mode S3 and S7). This inversion was performed with three backscatter models: Geometrical Optics Model (GOM), Oh Model (OM), and Modified Dubois Model (MDM), which were compared to obtain the best configuration. Mean absolute errors of 1.23, 1.12, and 2.08 cm for roughness expressed in rms height and for dielectric constant, mean absolute errors of 2.46 – equal to 3.88 (m3 m−3) in volumetric soil moisture, – 4.95 – equal to 8.72 (m3 m−3) in volumetric soil moisture – and 3.31 – equal to 6.03 (m3 m−3) in volumetric soil moisture – were obtained for the MDM, GOM, and OM simulation, respectively. These results indicate that the MDM provided the most accurate data with minimum errors. Therefore, the latter inversion algorithm was applied to images, and the final results are presented in two different maps showing pixel and homogeneous zones for surface roughness and soil moisture

An inversion method based on multi-angular approaches for estimating bare soil surface parameters from RADARSAT-1