Normalization and Calibration of Digital Aerial Imagery for Nitrogen Management Assessment.

We are seeing dramatic technological advancements in collecting digital aerial imagery (DAI) due to new imagery collection (both aircraft and unmanned aerial vehicles) and web-based imagery delivering systems. Vegetative indices (VI) derived from DAI can be used for different purposes visually identifying fertilizer application problems, guiding infield sampling strategies and quantifying the degree of crop nitrogen stress. For maximum utilization of VI in analyses of crop canopy over time and across large areas, DAI should be radiometrically calibrated, similarly to satellite imagery. Unfortunately, the majority of DAI on the market now is not calibrated. This presentation will show examples how to normalize (psedocalibration) aerial imagery to make the digital counts on the same scale and enhance the visual appearance at the same time. The emphasis will be on methods of empirical imagery calibration using calibration tarps. The issue of linearity and nonlinear relationship between reference digital counts and observed digital counts will be discussed. Examples will include also using aerial imagery in survey studies to quantify within-field area with deficient and sufficient nitrogen status.