Behavior and biology of many forest pests are tied to major forest disturbances and succession. The principle disturbance in the forests of the western United States is fire. Fire regimes as well as distribution and behavior of forest pests and beneficial microbes such as pathogenic and saprophytic Armillaria are all strongly associated with plant communities. Thus, mapping of plant communities would facilitate our ability to understand, predict, and manage interaction among these ecological processes. Preliminary attempts to map potential vegetation subseries (subdivision of climax forest series) using Landsat images and a solar insolation model produced a "reasonable” classification for a portion of the Eagle Cap Wilderness on the Wallowa Whitman National Forest in northeastern Oregon and suggested a potential mapping method. This paper compares the accuracy of two methods of vegetation mapping on a watershed in the Priest River Experimental Forest in northern Idaho. The first method integrates satellite imagery, insolation and several other variables using most similar neighbor analysis (MSN). MSN assigns values using a multivariate difference function to create classes based on the similarity of the training samples to the global variables. The second approach merges a potential vegetation coverage based on a landtype classification system and an aggregation of insolation coverage to create a classification based on preexisting vegetation data. Plant communities were determined on 300 ground-truth plots of 15-rn radius (506 in2) on the 780-hectare watershed. The center of each plot was established using differential GPS. The final product of this endeavor will be a subseries map of the watershed that should facilitate understanding interactions among fire, decomposition, soil moisture, and pest regimes.