Application of Regularized Filtering Technique to Retrieval of Land Surface Spectral Albedo

Surface bi-directional reflectance distribution function(BRDF) model can be applied to retrieve land surface climatological or biological parameters.However,in geosciences,it is often an ill-posed inverse problem to extract true information of complex surface through BRDF model inversion with limited satellite observations.Based on analysis of the cause of instability in model inversion and the mechanism of data error propagation,regularization filtering technique was adopted to overcome the difficulty due to the discrete ill-posedness in inverting the BRDF model.In order to test the retrieval ability and validity of the presented algorithm,multi-angular POLDER-3/PARASOL BRDF data and MODIS satellite data with deficient looks over the Tibetan Plateau were used.Retrieval results reveal that accuracy of the proposed regularized filtering algorithm is equivalent to that of MODIS AMBRALS code and thus it can be applied to retrieve land surface parameters using sufficient or even sparse observations.