Abstract

Two satellite images were acquired from the SPOT High Resolution Visible (HRV) Multispectral Linear Array (MLA) sensor in 1990 and the Landsat Thematic Mapper (TM) sensor in 1985 for a mountainous region in southwest Yukon Territory, Canada. These data were classified using a maximum likelihood decision rule and a new three-stage classifier designed specifically for analysis of mountain environments. Classification results improved from approximately 74% correct when using satellite sensor data alone to 85% correct using the satellite sensor data with geomorphometric variables extracted from a digital elevation model. Further refinement to approximately 88% correct were obtained with the new classifier. The resulting image maps were used to interpret the extent of changes in vegetation cover resulting from fluctuations in river systems and groundwater regimes.

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