Monitoring snow parameters in boreal forest using multi-frequency SAR data

The northern hemisphere is characterized by the presence of boreal forest, a nearly continuous belt of coniferous trees across North America and Eurasia. This region is characterized by a subarctic and cold continental climate, showing severe winters and short summers. Precipitation varies, from about 20 cm of precipitation per year to over 200 cm and for the higher percentage is in the form of snow. Recent studies, which were carried out within the framework of ESA's CoReH2O Phase-A mission, demonstrate that multi-frequency SAR data are able to quantify the amount of snow mass (SWE) on land or glaciers. On the other-hand the presence of forest has a significant impact on the propagation of the radar signal, depending on its structure, biomass, water content and cover fraction. In particular for dense forest scattering of vegetation strongly hides the signal from snow and, consequently, compromises the sensitivity to snow parameters. A method to compensate the vegetation effect and then to retrieve snow in forested areas is presented here. The method is based on the development of an e.m. model for a snow-covered vegetated terrain and the availability of some ancillary data about forest characteristics. An example of the SWE retrieval is provided using SAR airborne data collected over a boreal test site in Finland.