The Bureau of Land Management (BLM) manages 9.3 million hectares of land in Utah and has implemented an Emergency Stabilization and Rehabilitation (ESR) Program to protect life and property, combat soil erosion, and reduce the invasion of exotic/noxious weeds following wildland fire. In highly vulnerable sites, seeding treatments may be applied to establish an interim landcover to stabilize the soil and competitively exclude weed invasions. Monitoring treatment effectiveness is mandated through ESR guidelines and necessary for the submission of annual Accomplishment Reports for the first three years following fire containment. Ground monitoring has been the traditional approach to fulfilling this ESR monitoring mandate. Ground monitoring of vegetation within a large burn can be complicated or rendered infeasible by the logistical constraints presented by size, topography, and remoteness. The inherent weaknesses of ground monitoring in large remote areas provide the impetus for augmenting these approaches with remotely sensed data. The Rattle Fire Complex (RFC) is a 2002 burn that demonstrates a need and an opportunity to develop a remote sensing-based monitoring tool. This project utilized high spatial resolution Quickbird imagery and ground data to monitor treatment effectiveness and vegetative recovery within the RFC ESR project area and shows that remote sensing and statistical modeling can significantly improve knowledge regarding ESR treatment effectiveness when combined with traditional ground monitoring methods. The image acquisition cost and labor investment may be prohibitive, making this approach feasible only on large, high priority projects. This methodology arguably represents the simplest approach from both a remote sensing and statistical modeling approach and was accomplished using software currently available within the Bureau of Land Management computer network. It is unlikely that current technology can provide a cheaper or simpler alternative. Testing of this methodology on other projects will provide better insight into its utility and transferability.