## 1 Introduction  
Rangelands comprise between 26 to 36 percent of the terrestrial land surface [1; 2]. They consist of many ecosystems, including shrublands, savannas, tundra, deserts, alpine communities, coastal marshes, meadows, and grasslands [3]. Historically, grasslands covered 300 million ha in the United States and 50 million ha in Canada [4]. The mixed prairie, one grassland type, is located in the brown and dark brown soil regions of southern Alberta and Saskatchewan, Canada, and extends southward into northern Texas [5]. Approximately 7 percent of the area of Alberta is covered by the dry mixed-grass prairie subregion, of which 43 percent remains [6]. Climate is the determining factor for production and health in this ecosystem [1; 7; 8], and water availability largely controls productivity [1; 9; 10]. Climate change is expected to increase the amount and duration of growing season drought, as well as alter the frequency and intensity of growing season precipitation [1; 11]. [PERSON] and [PERSON] [10] demonstrated that prairie ecosystems have high production potential and substantial interannual variability, and are likely to be one of the most responsive biomes to future climate change [10]. Human interest in these areas is usually focused on yearly productivity [12] or biomass yields for economic and ecological monitoring purposes. The most common land use in the mixed prairie is rarching, as much of it is too dry to accommodate crop production without irrigation. Consequently, the economy in these regions is dominated by livestock rarching and supporting businesses. An emerging interest in prairie regions is yield assessment for agricultural insurance, which for prariies is limited by the inability to produce a direct, measurable yield; unlike traditional agriculture, a harvested crop yield is not the end product [13]. Prairie vegetation functions to prevent soil erosion and resist landscape degradation, facilitate groundwater recharge, sequester large amounts of carbon dioxide, and support plant and animal diversity [14; 15], which are often positively related to productivity [16; 17]. Due to the potential for biospheric carbon sequestration and other co-benefits, in a period with deepening concerns about anthropogenically-induced climate change, there is also an emerging possibility of targeted carbon markets and economic incentives for proper land stewardship in these areas. These economic and ecological issues require accurate methods of evaluating prairie biomass yield in response to interannual variations in precipitation, especially given the current climate variability and predictions for future climate change. Clearly, accurate monitoring methods are necessary for proper management of the mixed prairie. Traditionally, range management has been accomplished through the subjective evaluation and monitoring of large areas by skilled professionals relying on accumulated judgment and experience [18]. This methodology has limitations for widespread application. Quantitative estimates of prairie productivity have also often been conducted through biomass harvests, which are expensive and time-consuming [18; 19; 20; 21]. Biomass harvests are destructive, so repeated sampling of a single plot is not possible, limiting the temporal practicality of the method. The time-consuming nature of manual field sampling, combined with the expansive size of these ecosystems, further limits the utility of biomass harvests for prairie management [19; 20; 21]. Harvests require measurements to be performed in a representative number of places during a short time period and extrapolated to useful spatial and temporal scales. This often entails measurement errors, inaccuracies inherent in interpolation techniques, and delays in evaluating results that impair effective management. The requirement for a sampling method that limits error introduced by inadequate sample size and distribution often exacerbated by personal bias [18] has led to the exploration of remote sensing techniques for rangeland monitoring.