Abstract
Recently we proposed a Polarimetric Two-Scale Model (PTSM) [1-3], able to retrieve surface roughness, ground permittivity and soil moisture content by processing polarimetric Synthetic Aperture Radar (SAR) data. In our model we consider a bare soil surface as composed of large-scale variations on which a small-scale roughness is superimposed. In particular, the large-scale roughness is locally treated by replacing the surface with a slightly rough tilted facet, whose slope is the same of the smoothed surface at the center of the pertinent facet. The facet slopes along azimuth and range directions are modeled as independent Gaussian variables. Unlike what is described in [1-3], here the facet slope means are not forced to be equal to zero and then our retrieval algorithm can be applied even on not flat areas, just considering information provided by Digital Elevation Models (DEM). The facet's tilt causes the rotation of the local incidence plane around the line of sight and the variation of the local incidence angle around the radar look angle. We accounted for both these effects to evaluate analytically the normalized radar cross sections (NRCS), employed to retrieve the roughness and the soil moisture content using the co-pol/cross-pol method.
Published Version
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