Abstract

Statistical pattern-recognition methods are applied to the classification of the reflectance spectra of growing trees (Scots pine, Norway spruce, and birch). We show by using large training sets that it is possible to develop classification filters that are able to discriminate the tree types with a very high probability. Our approach may offer a reference coordinate system for multispectral remote sensing of different levels of forest damage.

© 1994 Optical Society of America

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