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Corn is grown for grain and silage by cash-grain & dairy farmers in New York on over 1 million acres of land. In debates on how to optimize estimates of corn yields, opinions range among continuing conventional measurements of soil properties, sampling at greater depth in the root zone, soil health testing, focusing on plant status as an integrator of the conditions that affect growth, and using precision-agriculture methods. Precision agriculture (PA), justified by its ability to address within-field spatial heterogeneity, is used increasingly to improve management toward maximizing profits.However, a number of authors have argued that the basic assumptions of current PA methodologies do not adequately account for the relationship between the nutrient status of soils, spectral properties of imagery, and crop growth pattern (e.g., Baveye and Laba, 2015). New approaches need to be explored, possibly using some of the new technologies that have become available in the last 10 years.Among these new technologies, Unmanned Aerial Systems (UASs) still have been used relatively little in agricultural applications (DeGloria et al., 2014). Nevertheless, the ease with which they allow repeated measurements at a generally low elevation with low ground speed and high spatial resolution can be taken advantage of to gain a better understanding of the relationship between plant yields, soil properties and spectral response patterns. The use of UASs for agricultural purposes is projected to become a multi-billion dollar industry in the next ten years. With one of six national UAS testing sites located in New York, farmers and Cornell Cooperative Extension educators have the unique opportunity to be on the cutting edge of evaluating this new technology.In this general context, the proposed research will involve farmers, researchers and extension agents in an initial evaluation of how UASs can be used to sharpen some of the technical assumptions on the basis of which PA is generally predicated. This information can improve and inform future corn management strategies and increase educators' ability to convey the value of UASs to farmers. We shall use a UAS to monitor bare soil before crop emergence and soil-crop cover of corn before harvest. We will also measure soil nutrient status and plant biomass before harvest. This data will be used to determine how UAS spectral measurements are correlated to soil characteristics and crop yield. These observations will determine when to use UASs, how to make use of the information they provide to improve corn management, and how to use this new technology to maximize crop yields.