What question did this study set out to answer?

This research aims to develop a comprehensive method for enhancing tree structural stability through optimized pruning techniques.

May 9, 2026Open Access

Improving tree stability with optimized pruning: a comprehensive cycle method

Key Points

This research aims to develop a comprehensive method for enhancing tree structural stability through optimized pruning techniques.
Developed a computational cycle integrating LiDAR scanning, Finite Element Modeling (FEM), and Topology Optimization (TO).
Applied the method to a Tipuana tipu tree using the new pruning algorithm for structural assessment.
Utilized LiDAR data in conjunction with FEM software to simulate wind load effects on tree stability.
Demonstrated significant structural response improvements for Tipuana tipu under simulated wind loads.
Showed the potential to lower tree fall risks through optimized pruning strategies.
Provided a decision-support tool for urban tree management that can be adapted for various tree species.

Abstract

Abstract Key message A new, comprehensive computational cycle that integrates LiDAR scanning, Finite Element Modeling (FEM), and Topology Optimization (TO) can help guide pruning decisions. This process aims to restore or improve a tree’s structural stability, lowering the risk of failure from wind and boosting long-term urban tree resilience. Abstract Frequent incidents of trees falling in São Paulo highlight the need for innovative methods to analyze and modify tree structures. Natural tree growth optimizes its architecture, however improper pruning practices often weaken this balance, leaving trees highly vulnerable under wind conditions that cause falls. Addressing these issues requires a better understanding of tree biomechanics. LiDAR scanning offers precise tree architecture through the creation of laser pulse-based point cloud. The Finite Element Method (FEM) accurately models physical forces acting on trees by solving differential equations for each element. This study introduces a pruning algorithm based on Topology Optimization (TO), which optimizes material distribution within a defined domain based on specific goals. Combining LiDAR, FEM, and the proposed TO pruning algorithm creates a practical cycle for assessing tree structural responses to wind loads and reoptimizing trees after pruning. Using LiDAR data processed with FEM software, this cycle is demonstrated for a Tipuana tipu tree, showing its potential to reduce tree fall risks. In practical terms, this framework provides a decision-support tool to guide pruning strategies that reduce wind-induced failure risk while preserving tree structural performance. Although the current implementation is primarily mechanical and was demonstrated using a single urban case study, the methodology is general and can be applied to different tree species and urban contexts worldwide, with future developments expected to integrate ecophysiological processes and species-specific material properties.

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