Active sensors, mounted on typical agricultural equipment, can be used to estimate N (nitrogen) status in corn (Zea mays L.) on a sub-field scale.� This gives a producer the potential to improve N fertilizer recommendations for crop production and potentially reduce nitrate loss to the environment.� This study examines the relationship between crop canopy reflectance data and yield in corn fields following corn, soybeans, alfalfa, and soybeans (with manure history) in Central Pennsylvania. �Pre-plant whole-plot treatments included a control, 56 kg N ha^-1 as NH₄NO₃, and 129-185 kg N ha^-1 as manure.� Split-plot treatments included six sidedress rates (0, 22, 45, 90, 135, and 180 kg N ha^-1) and one pre-plant rate (280 kg N ha^-1) as NH₄NO₃ in 9.1 x 4.5 m plots.� Georeferenced canopy reflectance data in the 590nm and 880nm wavelengths were taken each week from early May until mid-July. �This data was used to calculate the Normalized Difference Vegetation Index (NDVI) for each plot.� Preliminary results using Cate-Nelson indicate that the NDVI was able to accurately separate the data into responsive and non-responsive populations. �Further examination of the data from the limited number of responsive sites indicates that there is a general relationship between NDVI and economic optimum N rate (EONR).� Results from the sensor were also similar to those from a SPAD meter, suggesting that previous response studies using the SPAD meter could be used to develop N recommendations based on the sensor.� These results suggest that employing a ground-based active sensor appears to be a viable option for predicting corn response to sidedress N and may provide useful information for recommending sidedress N rates; however, more data in the responsive range is needed to further develop this relationship.