There has been an increase in trees and shrubs on rangeland systems in the past 150 years.1–3 This increase in woody species comes at the expense of perennial grasses whose losses can cause changes in primary production, nutrient cycling, and the accumulation of soil organic matter.4 In order to decrease the loss of inherent ecosystem function, vegetation mortality, and increased runoff associated with rangeland system degradation, it is necessary to utilize effective conservation practices. One such practice is brush management, which typically employs prescribed burning, mechanical methods (e.g., chaining, roller chopping, root plowing, shredding, and bulldozing), chemical methods (i.e., herbicide application), or a combination of these methods to control unwanted woody vegetation.5 Between 1997 and 2003, the United States Department of Agriculture’s (USDA) Natural Resources Conservation Service (NRCS) spent nearly $34 million dollars on conservation practices, over $19 million being for brush management alone, on 188 million ha of central and western rangelands and grazed forests.6 With such a large investment of resources being allocated toward the implementation of brush management, it is essential to have a mechanism for evaluating its effectiveness. The cost combination of labor, equipment, vehicles, travel, and supplies, make traditional ground-based methods of data collection on large scales prohibitively expensive. A pilot study to sample 400 sites (800 points) on 3.1 million ha of rangeland and pinyon-juniper woodlands, reported costs of sampling 448 points by 12 people working 10–12 h per day (data collection and travel) from early June to mid-October at approximately $400,000, with field data collection cost before analysis, averaging $893 per sample point.7 Evaluating nearly 200 million ha solely using on-the-ground resources is simply not feasible. A new large-area method is required.