Accuracy of wet snow mapping using simulated Radarsat backscattering coefficients from observed snow cover characteristics

Wet snow cover mapping by means of airborne and spaceborne SAR is operation al today and successfully applied in rugged high mountain terrain and in ag ricultural area. This paper proposes a numerical study to estimate the accu racy of wet snow mapping by using a radar backscattering model that simulat es backscattering from a multi-layer snowpack for various snow cover condit ions and for SAR parameters specific to Radarsat (C-HH). Field measurements carried out in numerous sites during the winters of 1994 to 1996 in severa l areas of Quebec (Canada) have allowed to choose some typical snow profile s and the corresponding snow/soil parameters. Results indicate that under t he assumptions used in the model and the simulations, for the standard mode S1 of Radarsat (20 degrees to 27.4 degrees) and in the case of wet snow co ver with liquid water content of 1%, the optimum relative under- and over-e stimation of wet snow pixels are of the order of 23.9% and 13.4%, respectiv ely. For wet snow cover at 2%, the algorithm operates with a relative under -estimation of wet snow pixels around 8.5% and a relative over-estimation o f the order of 1.7%. For wet snow with liquid water content of 4%, the rela tive under- and over-estimation of wet snow pixels is around 0.8% and 0.3%, respectively. They are negligible for wet snow with liquid water content h igher than 4%. With the standard mode S7 of Radarsat (44.9 degrees to 49.4 degrees), the wet snow mapping algorithm leads to a slightly lower performa nce than with the standard mode S1. The accuracy of the method for wet snow mapping demonstrates the high potential of SAR for snow monitoring. It is considered sufficient when the liquid water content of the snowpack is high er than 1% for actual snow conditions similar to those eight observed condi tions used in this study.