Sagebrush ecosystems offer many benefits to the state of Wyoming, such as habitat for wildlife. Recently, sagebrush ecosystems in Wyoming have been subjected to many anthropogenic disturbances. The consequences that these disturbances have upon sagebrush ecosystems can be very important to wildlife and sagebrush ecosystems. Remote sensing and GIS are tools that may help in the processing and gathering of sagebrush data; yet, there is limited research supporting best practices for remote sensing of sagebrush in disturbed environments. This thesis addresses the issue of using remote sensing to evaluate sagebrush cover in disturbed areas. To accomplish this goal three objectives were met. These included (1) The investigation of best approaches for the collection and aggregation of field data, (2) The development of approaches for scaling field data using high resolution imagery to provide a basis for determining the amount of sagebrush that occurs in each pixel of commonly available coarse resolution data, and, (3) The evaluation of whether texture, slope, aspect, and elevation can improve the ability of coarser spatial resolution imagery to predict the amount of sagebrush cover in a given location. In the completion of these objectives it was found that the prediction of sagebrush cover can be reasonably accomplished by using binary logistic regression, ocular estimation, and various spectral and ancillary data layers.