Monitoring Vineyard Canopy Management Operations Using UAV-Acquired Photogrammetric Point Clouds

Abstract

Canopy management operations, such as shoot thinning, leaf removal, and shoot trimming, are among the most relevant agricultural practices in viticulture. However, the supervision of these tasks demands a visual inspection of the whole vineyard, which is time-consuming and laborious. The application of photogrammetric techniques to images acquired with an Unmanned Aerial Vehicle (UAV) has proved to be an efficient way to measure woody crops canopy. Consequently, the objective of this work was to determine whether the use of UAV photogrammetry allows the detection of canopy management operations. A UAV equipped with an RGB digital camera was used to acquire images with high overlap over different canopy management experiments in four vineyards with the aim of characterizing vine dimensions before and after shoot thinning, leaf removal, and shoot trimming operations. The images were processed to generate photogrammetric point clouds of every vine that were analyzed using a fully automated object-based image analysis algorithm. Two approaches were tested in the analysis of the UAV derived data: 1) to determine whether the comparison of the vine dimensions before and after the treatments allowed the detection of the canopy management operations; and 2) to study the vine dimensions after the operations and assess the possibility of detecting these operations using only the data from the flight after them. The first approach successfully detected the canopy management. Regarding the second approach, significant differences in the vine dimensions after the treatments were detected in all the experiments, and the vines under the shoot trimming treatment could be easily and accurately detected based on a fixed threshold.

Vineyard Pruning Weight Prediction Using 3D Point Clouds Generated from UAV Imagery and Structure from Motion Photogrammetry

“…That methodology yields a geometric figure adjusted to the irregular shape of the vine structures that enhances the quantitative estimates of parameter values, in which the presence of voids in the vegetation is also taken into consideration [20]. The R 2 = 0.74 coefficient of determination found in this study for the relationship between pruning weight and the volume so calculated supports the viability of using SfM to determine vine quantitative variables, a finding in line with earlier reports [20,50,51].…”

Comparison of Aerial and Ground 3D Point Clouds for Canopy Size Assessment in Precision Viticulture

“…UAV technology was widely used to assess canopy volumes and it was shown to be a quick and low-cost solution compared to ground measurements of canopy size parameters [50, 60,[64][65][66][67][68][69]. The UAV point cloud processing led to similar results in canopy volume values concerning other research, but they used a voxel method [70] and an alphashape approach [38,71]. Therefore, direct comparison is not possible.…”

Quantification of dwarfing effect of different rootstocks in ‘Picual’ olive cultivar using UAV-photogrammetry

“…It does not need any user intervention, and was designed using Cognition Network programming language in eCognition Developer 9.3 software (Trimble GeoSpatial, Munich, Germany). The algorithm was created for the analysis of vineyards in trellis systems (López-Granados et al, 2020), but it was adapted and re-parameterized to be applied in an olive hedgerow scenario due to the…”