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A study was carried out to assess the potential of using satellite images to identify a parameter that could characterize land surface condition - i.e. soil roughness, a factor that strongly influences radar backscattering from semi-arid land surfaces.

A simple setting in terms of roughness - the flat Atar desert, Mauritania - was used for data extraction from an ERS-1 image, acid two methods were defined for measuring the statistical parameters of roughness (standard deviation of heights and correlation length) from photographs of the ground. Analysis of these parameters showed that a close relationship exists between correlation length and standard deviation of heights for regs and that a single parameter enables us to describe roughness.

Theoretical models (Small Perturbation Model, Integral Equation Model and Geometrical Optics Model) were then used to establish data sets simulating ERS-1 backscattering coefficients for the different roughness surfaces. Based on the statistical parameters extracted from photographs, good agreement is observed between the modeled backscattering and the recorded backscattering from ERS-1 data. The relationship between the two statistical parameters was then used to simulate several surfaces, with the backscattering behavior being studied through theoretical models. The results show backscattering as a function of the standard deviation of heights and define the possibilities and limitations for extracting roughness parameters.