High-Resolution UAV Imagery for Field Olive (Olea europaea L.) Phenotyping

Remote sensing techniques based on images acquired from unmanned aerial vehicles (UAVs) could represent an effective tool to speed up the data acquisition process in phenotyping trials and, consequently, reduce time and cost of field work. In this study, we assessed ability a UAV equipped with RGB-NIR cameras highlighting differences geometrical spectral canopy characteristics between eight olive cultivars planted at different planting distances hedgerow orchard. The relationships measured estimated height, projected area volume were linear regardless (RMSE 0.12 m, 0.44 m2 0.68 m3, respectively). A good relationship (R2 = 0.95) was found pruning mass material weighted ground its by images. NDVI February 2019 related fruit yield per tree November 2018, whereas no observed due abiotic biotic stresses that occurred before harvest. These results confirm reliability imagery structure motion estimating suggest further potential applications UAVs early discrimination efficiency volume.