Chairperson, Graduate Committee: Rick L. Lawrence.Savage, Shannon Lea2013-06-252013-06-252005https://scholarworks.montana.edu/handle/1/2183The Northern Range (NR) of Yellowstone National Park (YNP) is currently a critical area of analysis in the Greater Yellowstone Ecosystem (GYE). The complex dynamic ecosystems in the NR provide outstanding field laboratories for long-term scientific investigations to evaluate management techniques. Grassland and shrubland ecosystems serve as important habitat for a wide variety of animal species in the NR and empirical knowledge of these systems enables managers to better understand the ecological complexities and make informed management decisions. Accurate vegetation maps are useful tools for these land managers, as is the ability to detect changes in vegetation over time. An inexpensive and easily reproducible method for mapping rangelands over the NR was developed utilizing Landsat Enhanced Thematic Mapper Plus (ETM+) satellite imagery. A classification hierarchy of non-forest vegetation was produced with 5 levels, ranging from very broad vegetation types such as woodland, shrubland, or herbaceous vegetation (Level 1) to specific vegetation types such as aspen (Populus tremuloides), tufted hairgrass/sedge (Deschampsia cespitosa/Carex spp.), or big sagebrush/Idaho fescue (Artemisia tridentata/Festuca idahoensis) (Level 5). A 1999 base map of nonforest vegetation in the NR was created using classification tree analysis (CTA) combined with boosting. Overall accuracies of the final maps ranged from 72.30% for Level 5 to 83.65% for Level 1, providing evidence that this method can be successful for mapping non-forest vegetation in the NR. A 1985 Landsat Thematic Mapper (TM) satellite image was chosen for performing a change detection analysis from 1985 to 1999. Tasseled Cap space was utilized to choose a threshold of change in a change vector analysis (CVA). Areas of no change in the 1999 image were used to train areas of potential change on the 1985 image to produce a final map of the NR for 1985. Overall accuracies of the final maps ranged from 72.60% for Level 5 to 88.73% for Level 1. Managers are able to analyze this change information and modify their management techniques as needed. With the 1999 base map the CVA method enables managers to detect vegetation change in the NR on a regular basis.enRangelandsPlantsThesisCopyright 2005 by Shannon Lea Savage