The potential of InSAR for quantitative surface parameter estimation

Abstract

Although the problems of soil moisture and surface roughness estimation of bare surfaces have been extensively analyzed in terms of conventional polarimetric synthetic aperture radar (SAR) data, the information content of polarimetric interferometric SAR (Pol-InSAR) data regarding surface parameters has not yet been fully investigated. We consider this problem and show that the main contribution to roughness and moisture dependence of coherent surface scattering in Pol-InSAR is the signal-to-noise ratio (SNR). For the estimation of surface parameters, a new hybrid surface scattering model has been developed which is based on the polarization dependence of SNR and its impact on the observed coherences. We show that the model is invertible and allows us to recover surface roughness and moisture estimates from the ratios of measured InSAR coherence. Further, the hybrid model is used for a study of sensitivity analysis. Lastly, we show validation results from experimental Pol-InSAR data from the Deutsche Forschungsanstalt fur Luft-und Raumfahrt (German Aerospace Center (DLR)) E-SAR system at L-band. These results indicate that Pol-InSAR has high potential, to be used as an alternative method, for quantitative moisture and roughness estimates of bare surfaces.