## 1 Introduction
For example, the agricultural insurance industry has been exploring satellite remote-sensing-based monitoring programs and is interested in evaluating the accuracy of yield estimation in an effort to enhance customer confidence [34]. This interest influenced the goals of this research, which were to evaluate how effectively NDVI from different common satellite sensors can estimate spatial and interannual patterns of grassland yield, and how satellite measurements compare to biomass harvests and NDVI from ground measurement. A common practice in assessing the utility of remote sensing for rangeland management is to conduct studies over a single growing season, such that evaluation of the impacts of year-to-year variability in precipitation is limited [29]. Many other studies forego any intensive ground sampling with field spectrometers and rely only on data derived from broad-band satellite sensors [20], leaving issues of satellite validation unresolved. Furthermore, the lack of a single, universal NDVI formulation due to the many band and sampling configurations of existing satellite sensors requires independent calibrations be conducted. Satellite calibration and validation (\"CalVal\") efforts have often focused on a limited number of core sites [35], and have been less concerned with evaluating the management applications of such sensors in the context of environmental change,leaving many aspects of validation to the scientific or end-user community. Consequently, there is an ongoing need to evaluate satellite sensors by comparing their output with field measurements, particularly when accurate data are needed for management regimes, carbon markets, or insurance purposes. Validation efforts comparing satellite measurements and traditional field sampling must, by definition, compare data collected on vastly different scales, necessitating some kind of scaling regime [36], adding to the challenges of quantitative yield estimates from satellites. In this study we analyzed data from the SPOT, MODIS Terra and Aqua platforms, and ground spectrometry to calculate NDVI. We then compared the resulting NDVI values to harvested biomass from southern Albertan mixed-grass prairies over two consecutive summers (2009 and 2010) having contrasting rainfall regimes. The objectives of the study were to (1) determine whether NDVI time-series from satellite systems that are currently utilized for estimating productivity are comparable to measurements from a ground spectrometer and harvested biomass; (2) determine whether variations in productivity as a result of contrasting weather conditions over two consecutive summers are clearly detectable, which could indicate the utility of remote sensing for monitoring long-term or year-to-year climate variability in prairie systems; and (3) determine the practical utility of NDVI for estimating above-ground biomass (\"yield\") in the mixed prairie. Addressing the last objective is an essential foundation for cost-effective satellite-based rangeland insurance or carbon management programs. Since accuracy is crucial for carbon markets and insurance programs, we also considered the relative performance of two satellite sensors, SPOT and MODIS (Aqua and Terra), using ground NDVI measurements as a reference.