Assessing the canopy characteristics of the trees is essential for optimizing agronomic management. In fact, it has been shown that there is a strong relationship between the geometric characteristics (i.e. size and volume) of the tree and quantity of water and fertilizer used for crop management. Normally, tree measurements are carried out using manual method, that is time consuming so seems to be more feasible on few trees. For the first time, this study tested the UAV technology on intensive and high-density hazelnut orchards. The aim was to propose a new automated method for the hazelnut canopy characterization, using a DJI Phantom 4 Multispectral UAV. The results showed a good performance of the method proposed for evaluating the width and the actual volume of the canopy. A criticism was revealed for the height of the canopy probably due to the UAV survey. Anyway, the measurements conducted on the point cloud resulted less time-consuming per each tree and more punctual than manual ones, so less exposed to errors.

Assessment of the geometrical characteristics of hazelnut intensive orchard by an Unmanned Aerial Vehicle (UAV)

Vinci A.
;
Traini C.;Brigante R.;Farinelli D.
2022

Abstract

Assessing the canopy characteristics of the trees is essential for optimizing agronomic management. In fact, it has been shown that there is a strong relationship between the geometric characteristics (i.e. size and volume) of the tree and quantity of water and fertilizer used for crop management. Normally, tree measurements are carried out using manual method, that is time consuming so seems to be more feasible on few trees. For the first time, this study tested the UAV technology on intensive and high-density hazelnut orchards. The aim was to propose a new automated method for the hazelnut canopy characterization, using a DJI Phantom 4 Multispectral UAV. The results showed a good performance of the method proposed for evaluating the width and the actual volume of the canopy. A criticism was revealed for the height of the canopy probably due to the UAV survey. Anyway, the measurements conducted on the point cloud resulted less time-consuming per each tree and more punctual than manual ones, so less exposed to errors.
2022
978-1-6654-6998-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1537553
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