Statistical pattern-recognition methods are applied to the classificat
ion of the reflectance spectra of growing trees (Scots pine, Norway sp
ruce, and birch). We show by using large training sets that it is poss
ible to develop classification filters that are able to discriminate t
he tree types with a very high probability. Our approach may offer a r
eference coordinate system for multispectral remote sensing of differe
nt levels of forest damage.