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Aerial images obtained using an unmanned aerial system (UAS) were used to create a classified image showing tree canopy health in a macadamia orchard. The resulting map was used to modify management of a macadamia plantation. Vegetation indices, principally the Canopy Chlorophyll Content Index (CCCI), derived from both UAS and WorldView2 satellite imagery, were compared and correlated with spectral radiometry and leaf nitrogen levels determined by field sampling. Classified CCCI images from both sensor types were integrated into farm management software (PAM Ultracrop) and processed into a suitable format for driving a GPS-controlled fertilizer spreader for more effective control of nitrogen application rates. Applying fertilizer at a variable rate according to tree health will result in cost savings to the industry and potentially increase production.
Felderhof et al. (2011) studied this question.