Abstract
Satellite data provide the only practical way to obtain the necessary spatial and temporal coverage of areal extent of snow cover required for hydrometeorological applications. A new procedure has been developed which: (1) accurately separates snow and cloud from clear land in a terrestrial scene; and (2) uses other criteria to separate both cold, high clouds and warm, low clouds from snow. A mixed pixel class is also identified and pixels in this class can be assigned a percentage composition (cloud, snow, and land) using a linear mixing model. The procedure has been ground-truthed with both Landsat data and SNOTEL (SNOwTELemetry) observations. Classification skill, based on a statistical comparison with SNOTEL observations, is about 97%. Application of the procedure to a wide variety of terrestrial environments is demonstrated.
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