One goal of this project is to develop techniques to characterize grassland management using remote sensing data from EOS-MODIS. This work is focused on detection and assessment of grazing management at Central Plains Experimental Range (CPER, in eastern Colorado), which has grazing of varying intensity, and at Crescent Lakes National Wildlife Refuge (CLNWR, in central Nebraska) where recent history of grazing varies between different paddocks. Ground-truth measurements of aboveground net primary productivity (ANPP) and leaf area index (LAI) were used to validate estimates derived from remotely sensed surface reflectance. Ground-based results indicate that ANPP and LAI are strongly related during the wetter part of the growing season, but not during drier periods. At CPER, remotely sensed average LAI and the seasonal distribution of LAI can be used to distinguish heavily grazed plots from ungrazed plots, while at CLNWR, those paddocks that are regrowing are discernible from those that are grazed using remote sensing. Overall, our results suggest that remotely sensed data can be used to characterize management impacts at divergent sites across the Great Plains and this information is likely to be useful for driving ecosystem models to assess management impacts on soil C stocks.