Geometrical Characterization of Hazelnut Trees in an Intensive Orchard by an Unmanned Aerial Vehicle (UAV) for Precision Agriculture Applications

Knowledge of tree size is of great importance for the precision management of a hazelnut orchard. In fact, it has been shown that site-specific crop management allows for the best possible management and efficiency of the use of inputs. Generally, measurements of tree parameters are carried out using manual techniques that are time-consuming, labor-intensive and not very precise. The aim of this study was to propose, evaluate and validate a simple and innovative procedure using images acquired by an unmanned aerial vehicle (UAV) for canopy characterization in an intensive hazelnut orchard. The parameters considered were the radius (R-c), the height of the canopy (h(c)), the height of the tree (h(tree)) and of the trunk (h(trunk)). Two different methods were used for the assessment of the canopy volume using the UAV images. The performance of the method was evaluated by comparing manual and UAV data using the Pearson correlation coefficient and root mean square error (RMSE). High correlation values were obtained for R-c, h(c) and h(tree) while a very low correlation was obtained for h(trunk). The method proposed for the volume calculation was promising.

Automated summary

A simple and innovative procedure using images acquired by a UAV was proposed, evaluated, and validated for canopy characterization in a hazelnut orchard. The method showed promising results for estimating parameters like radius, canopy height, and tree height, except for trunk height. The performance of the method was evaluated by comparing manual and UAV data using correlation coefficients and RMSE.