The novel use of proximal photogrammetry and terrestrial LiDAR to quantify the structural complexity of orchard trees

Abstract

Within the agrifood sector, the production of high yields is a driver for UK orchard husbandry. Currently, orchard tree management is typically a non-discriminatory method with all trees subjected to the same interventions. Previous studies indicate that structural complexity of individual orchard trees is an indicator for future yield, which can guide the management of individual trees. However, data on the structure of individual trees is often limited. This study investigated the suitability of using remote sensing methods to capture data that can be used to quantify tree structure. Descriptive metrics based on the mathematical assessment of self-affinity and dimensionality were applied to the remotelysensed data to quantify tree structure, and were also analysed for suitability as a predictor of fruit yield. The findings suggest that while proximal photogrammetry is informative, terrestrial LiDAR data can be used to quantify structural complexity most effectively and this approach holds greater potential for informing orchard management.

Canopy density estimation in perennial horticulture crops using 3D spinning lidar SLAM

“…To generate a complete 3D representation of a scene, a TLS system is placed manually around objects of interest at multiple view angles. Often artificial, fixed reference targets are placed in the scene to provide spatial control points for alignment (i.e., registration) of all 3D point clouds to generate a complete 3D representation and also avoid occlusion (Fernández‐Sarría et al, 2019; Moorthy et al, 2011; Murray et al, 2019).…”

“…Lidar beams often get obscured by the outer layers of the canopy which results in underestimation of structure information (sparsity) within the canopies. Due to the high‐density nature of the perennial agricultural crops and lack of diverse lidar beams (distances and angles) intersecting with inside the canopies, the within parts are less observed and the canopy structure attributes such as density, porosity, and vigor are underestimated (Murray et al, 2019).…”

“…To collect lidar data at the whole field scale, most studies mount a fixed 2D line‐scan lidar (Moreno et al, 2020; Siebers et al, 2018) or a 3D multi‐beam lidar (Chakraborty et al, 2019; Gené‐Mola et al, 2019) on a moving platform to scan the crop rows from a side view. However, due to the high‐density nature of the perennial agricultural crops, many previous studies have shown these push‐broom lidar settings do not provide accurate estimation of more complex canopy structure attributes such as density, porosity, and vigor (Murray et al, 2019). The data resulting from these push‐broom lidar systems tend to be relatively sparse inside the dense canopies.…”

Tree Shape Variability in a Mixed Oak Forest Using Terrestrial Laser Technology: Implications for Mating System Analysis

“…Ecologically speaking, the arrangement of tree branches represents optimized adaptations to site conditions [5]. Biophysical processes related to carbon and water storage-photosynthesis and evapotranspiration-are also influenced by the tree architecture [6,7]. Tree architecture is also crucial to pollination and mating in wind-pollinated species.…”

Εφαρμογή Γεωργίας Ακριβείας Σε Καλλιέργεια Επιτραπέζιων Σταφυλιών

“…για τη δημιουργία τρισδιάστατων μοντέλων φυτών αλλά και για την εκτίμηση παραμέτρων που σχετίζονται με το φύλλωμα (π.χ. δείκτης φυλλικής επιφάνειας), τον όγκο, το ύψος, την βιομάζα των φυτών και την παραγωγή(Koenig et al, 2015, Murray et al, 2019, Gené-Mola et al., 2020 …”