This paper presents the ground-truthing of remote sensing data of citrus plants collected from unmanned aerial vehicles (UAVs). The main advantage of the UAV-based remote sensing is the reduced cost and immediate availability of high resolution data. This helps detect crop stresses throughout the crop season. Near infrared (NIR) images obtained using remote sensing techniques help determine the crop performances and stresses of a large area in a short amount of time for precision agriculture, which aims to optimize the amount of water, fertilizers, and pesticides using site-specific management of crops. However, to be useful for the real-world applications, the accuracy of remote sensing data must be validated using the proven ground-based methods. UAVs equipped with multispectral sensors were flown over the citrus orchard at Cal Poly Pomona’s Spadra Farm. The multispectral/hyperspectral images are used in the determination of vegetation indices that provide information on the health of the plant. Handheld spectroradiometer, water potential meter, and chlorophyll meter were used to collect ground-truth data. Correlations between the vegetation indices calculated using airborne data and proximal sensor data are shown.
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