Snowcover Mapping by Machine Processing of Skylab and Landsat Mss Data

SKYLAB and LANDSAT MSS data were analyzed using computer-aided analysis techniques (CAAT) developed at LARS. Results indicated that the middle infrared wavelength bands of the SKYLAB S-192 scanner would allow effective discrimination between snowcover and water-droplet clouds, whereas the limited spectral response of the LANDSAT-1 or 2 scanners do not allow such spectral discrimination. In the next phase of the current investigation, five spectral classes of snowcover were defined and mapped. These classes were found to be related to differences in the proportion of snow and forest cover in the individual resolution elements. In addition, topographic data (elevation, slope, and aspect) were digitally registered onto the SKYLAB and LANDSAT data to determine their influence on snowpack characteristics. Combining these results with the digital topographic data allowed acreage estimates of the various classes of snowcover to be tabulated according to elevational zones for either the entire data set or on an individual watershed basis. This research was funded under NASA Contract NAS9-13380. 295 https://ntrs.nasa.gov/search.jsp?R=19760009494 2017-11-03T01:40:15+00:00Z