Classification and retrieval of dry snow parameters by means of SMM/I data and artificial neural networks

Dry snow temperature, snow water equivalent (SWE) and snow depth have been retrieved by using the 19 and 37 GHz SSM/I brightness temperatures and artificial neural networks (ANNs). The results obtained have been compared with those obtained using other approaches such as the spectral polarization difference, the HUT model-based iterative inversion, the Chang algorithm and linear regressions. In general, it has been noted that the ANN based technique gives better results than the other approaches, which tend to underestimate the unknown parameters.