Abstract
We propose a 3D-approach of the soil surface height variations, either for the roughness characterization by the mean of the bidimensional correlation function, or as input of a backscattering model. We consider plots of 50cm by 50cm and two states of roughness of seedbed surfaces: an initial state just after tillage and a second state corresponding to the soil roughness evolution under a rainfall event. We show from stereovision data that the studied surfaces can be modelled as isotropic Gaussian processes. We study the change of roughness parameters between the two states. To discuss the relevance of their difierences, we flnd from Monte-Carlo simulations the bias and variance of estimator for each roughness parameters. We study the roughness and moisture combined in∞uences upon the direct backscattering coe-cients by means of an exact method based on Maxwell's equations written in a nonorthogonal coordinate system and by averaging the scattering amplitudes over several realizations. We discuss results taking into account the numerical errors and the precision of radar. We show that the ability of the radar to discriminate the difierent states of seedbed surfaces is clearly linked to its precision.
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