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Automated Mapping of Montane Snow Cover at Subpixel Resolution from the Landsat Thematic Mapper
Author(s) -
Rosenthal Walter,
Dozier Jeff
Publication year - 1996
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/95wr02718
Subject(s) - thematic mapper , subpixel rendering , remote sensing , snow , thematic map , pixel , vegetation (pathology) , environmental science , geology , cartography , satellite imagery , geography , computer science , artificial intelligence , geomorphology , medicine , pathology
A fully automated method uses Landsat Thematic Mapper data to map snow cover in the Sierra Nevada and make quantitative estimates of the fractional snow‐covered area within each pixel. We model winter and spring reference scenes as linear mixtures of image end member spectra to produce the response variables for tree‐based regression and classification models. Decision trees identify cloud cover and fractional snow‐covered area. We test the algorithm on a different Thematic Mapper scene and verify with high‐resolution, large‐format, color aerial photography. The accuracy of the automated classification of Thematic Mapper data equals that obtainable from the aerial photographs but is faster, cheaper, and covers a vastly larger area. The mapping method is insensitive to the choice of lithologic or vegetation end members, the water equivalent of the snow pack, snow grain size, or local illumination angle.