FOREST MAPPING AT LASSEN-VOLCANIC-NATIONAL-PARK, CALIFORNIA, USING LANDSAT TM DATA AND A GEOGRAPHICAL INFORMATION-SYSTEM

Knowledge of forest species composition is an integral part of designi ng and implementing resource manangement policies in a national park. Managers must rely on cost-effective methods of vegetation mapping, na mely, use. of remotely sensed data coupled with digital geographic dat a, to help them meet their management goals. In this study, we demonst rate that genus-level maps can be generated from unsupervised classifi cations of Landsat TM data at an accuracy level of 73 percent. Species -level maps can be created to an accuracy level of 58 percent by post- stratification of the spectral classification with topographic data in a geographic information system (GIS). This modification method is a rule-based system whereby spectral forest classes ore sorted based on elevation and soil-moisture gradients established for each species thr ough ecological research. Our observations illustrate that spectral cl assification is optimized by using all six reflective TM bands and tha t classification accuracy is affected by canopy cover and understory v egetation. Modifying spectral classifications by environmental data in a GIS is a useful way of defining species composition of forests in a n area where access to forests is limited but need for map information is great.