Sagebrush ecosystems in North America have experienced extensive degradation since European settlement, and continue to further degrade from exotic invasive plants, greater fire frequency, intensive grazing practices, increased oil and gas development, climate change, and other factors. Remote sensing is often identified as a key information source to facilitate broad-area ecosystem-wide characterization, monitoring and analysis, however, approaches that characterize sagebrush with sufficient and accurate local detail across large areas to support ecosystem research and analysis are unavailable. We have developed a new remote sensing sagebrush ecosystem characterization approach for the state of Wyoming, U.S.A. This approach uses a combination of methods to integrate 2.4-m QuickBird, 30-m Landsat TM, and 56-m AWiFS imagery into the characterization of four primary continuous field components (percent bare ground, percent herbaceous cover, percent litter, and percent shrub) and four secondary components (three subdivisions of shrub - percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata spp.), percent Wyoming sagebrush (Artemisia tridentata wyomingensis) - and shrub height), using regression tree classification. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4-m QuickBird, 6.04 to 15.85 for 30-m Landsat, and 6.97 to 16.14 for 56-m AWiFS. Shrub and herbaceous components outperformed the current national standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and an herbaceous component RMSE value of 12.89 versus 14.63. These results offer new advancements in sagebrush ecosystem quantification from remote sensing and provide a foundation to quantitatively monitor these components into the future. Data products include raster spatial grids depicting 30m cell predictions across Wyoming for the eight components described above.