The Integral Equation Model (IEM) predicts the normalized radar cross section (NRCS) of dielectric surfaces given surface and radar parameters. To derive the surface parameters from the NRCS using the IEM, the model needs to be inverted. We present a fast method of this model inversion to derive soil surface roughness parameters from synthetic aperture radar (SAR) remote sensing data. The model inversion is based on two different collocated SAR images of different bands, the derivation of the parameters cannot be done using one band alone. The computation of the model and the model inversion are very time consuming tasks and therefore may be impractical for large remote sensing data. We present an approach that is based on a few model assumptions to speed up the computation of the surface parameters. We applied the algorithm to detect the correlation length of the surface for dry-fallen areas in the World Cultural Heritage "Wadden Sea", a coastal tidal flat at the German Bight (North Sea). The results are very promising and may be used for a classification of the area in future steps.