Estimation of properties of alpine snow from Landsat thematic mapper
Advances in Space Research 9(1): 207-215
Estimation of snow characteristics from satellite remote sensing data requires that we distinguish snow from other surface cover and from clouds, compensate for the effects of the atmosphere and rugged terrain, and interpolate snow albedo over the entire solar spectrum from measurements at a few wavelengths. We also need to account for topographic effects without requiring that satellite data be precisely registered to digital elevation data, because the poor quality of most digital elevation data introduces considerable noise into calculations of slope and azimuth. From simulation of a range of snow types and various atmospheric profiles, over possible illumination conditions, we can develop typical spectral signatures above the atmosphere over mountainous terrain. Landsat Thematic Mapper data of the southern Sierra Nevada are analyzed to distinguish several classes of snow from other surface covers. Snow can be reliably mapped at all sun angles encountered in the mid-latitudes, and large surface grain sizes can be distinguished from areas where the grain size is finer at the snow surface. Because of saturation in TM band 1, estimation of the degree of contamination by absorbing aerosols is not feasible.