Approach for modeling single branches of meadow orchard trees with 3D point clouds

TL;DR

This paper presents a method to automatically model single orchard trees from 3D point clouds to identify pruning points, aiding sustainable orchard management and biodiversity conservation.

Contribution

It introduces a novel algorithm that constructs accurate skeleton models of trees from segmented 3D point clouds, enabling automated pruning point detection.

Findings

Achieved 95.19% accuracy in branch assignment and modeling.

Successfully generated virtual tree models for pruning analysis.

Demonstrated potential for automated orchard management tools.

Abstract

The cultivation of orchard meadows provides an ecological benefit for biodiversity, which is significantly higher than in intensively cultivated orchards. The goal of this research is to create a tree model to automatically determine possible pruning points for stand-alone trees within meadows. The algorithm which is presented here is capable of building a skeleton model based on a pre-segmented photogrammetric 3D point cloud. Good results were achieved in assigning the points to their leading branches and building a virtual tree model, reaching an overall accuracy of 95.19 %. This model provided the necessary information about the geometry of the tree for automated pruning.