Effective roadside vegetation management is vital for safety, visibility, and infrastructure longevity. Traditional methods are often labour-intensive, time-consuming, and difficult to scale. This paper presents a novel approach leveraging LiDAR (Light Detection and Ranging) data and geospatial analysis for large-scale roadside vegetation management. We introduce the Vegetation Free Volume (VFV), a spatial boundary defining clear roadside space. Using high-resolution Li DARpointcloudsandadvancedgeospatialprocessing, wedetectandquantifyovergrownvegetation encroaching into the VFV. The method transforms point clouds into a homogeneous coordinate system, applies geometric queries to identify breaches, and generates horizontal and vertical density profiles to visualise overgrowth. Structured machine- and human-readable reports provide actionable insights for automated systems and field crews. Furthermore, we simulate vegetation growth and pruning cycles at the LiDAR-point level to support maintenance scheduling and re source optimisation. Results demonstrate that integrating LiDAR and geospatial analysis enhances precision, efficiency, and scalability in roadside vegetation management.
Reja et al. (Tue,) studied this question.