Towards Calibrated Vegetation Indices From UAS-Derived Orthomosaics

Abstract: Crop advisors and farmers increasingly use drone data as part of their decision making. However, the vast majority of UAS-based vegetation mapping services support only the calculation of a relative NDVI derived from compressed JPEG pixel values and do not include the possibility to include more complex aspects like soil correction. In our ICPA12 contribution, we demonstrated the effects and consequences of the above shortcomings. Here, we present the stepwise development of a solution to ensure reliable input for crop advisors as a basis for site-specific crop management based on drone data. UAS flights are executed with a Trimble UX5 (HP) over a Belgian farm comprising four different crop types during a 3 month interval. Vegetation index maps derived from compressed JPEG imagery as well as preprocessed raw sensor data from a modified conventional CIR camera are evaluated against those from a true multispectral camera, and we examine the ability to calibrate the maps. Resulting maps are compared to NDVI values from the active close-range Trimble GreenSeeker crop sensor. Based on the results, we discuss under which conditions the three different data types can be used to complement traditional measurements in addressing within-season crop variability.

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Authors: Klaas Pauly

Associations: Unmanned Aircraft Systems, Trimble Navigation Ltd., Belgium