Abstract
Forest or wildland vegetation classification is one of the most challenging applications of LANDSAT‐MSS data, because of the common heterogeneity of this cover type and the numerous factors affecting its spectral response. Vegetation classes are difficult to define on the basis of their spectral characteristics alone, they are better characterized by a spatially distributed pattern of spectral responses. Studies having indicated that spectral data analysis is a limited tool for classifying vegetation, in 1978 the Laurentian Forest Research Centre (LFRC), facing the problem of choosing an operational methodology to produce vegetation mapping over large areas, adopted a method that takes advantage of human interpretation and computer capabilities: the interpretation of digital enhancements based on principal component analysis. The main steps of the enhancement methodology are given, from the delineation of training areas for statistic generation to various histogram stretches of the output components mappe...
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