Webcast

Optical RS Snow Products: Theory

Snow on the ground differs from most of the Earth surfaces by its high reflectance or albedo in the visible and near-infrared wavelengths (0.350 to 1 μm). For longer, the snow’s reflectance decreases significantly. In these wavelengths,snow is even less reflective than certain types of vegetation. Most of the incident radiation in these wavelengths is absorbed in the snowpack. These unique spectral characteristics are used in optical remote sensing to distinguish between snow and other types of surfaces. The numerous validation studies indicate that the satellite snow products have large snow mapping accuracy with respect to ground snow observations for cloud-free conditions, which varies between 69 and 94% in the winter seasons. The main limitation of existing optical platforms operating at a daily timescale is cloud coverage, which significantly reduces the availability of snow cover information.

In this session, algorithms used to retrieve HSAF snow products; snow mask (H31, H34) and effective snow cover area (H32, H35) from opticalsatellite data are presented. The challenges and the opportunities in retrieving snow cover mapsfrom optical data are discussed.

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