Quantifying the Link Between 3D Vegetation Structure and Plant Diversity in Urban Parks Using Fused Multi-Platform LiDAR Data

Abstract

Traditional field surveys of urban park biodiversity lack efficiency and scale, whereas LiDAR offers precise 3D vegetation quantification. This study investigates how 3D vegetation structural complexity impacts urban park plant diversity. We integrated Unmanned Aerial Vehicle (UAV) and handheld LiDAR data with ground-based quadrat surveys to capture comprehensive vegetation structures. Using six key 3D structural metrics, we modeled their relationship with plant diversity via Random Forest. Results indicate canopy height standard deviation (Hstd) primarily influences cultivated plant diversity, while the vegetation density index (VDI) drives spontaneous diversity. The model predicted species richness better (30.63% variance explained) than the Shannon index (7.63%). These drivers exhibited significant non-linear effects and potential ecological thresholds. A strong synergy emerged: when the vertical structure is complex and the 3D spatial density is high, the predicted plant diversity initially exhibits a trend of saturation and stabilization. Ultimately, multi-dimensional 3D vegetation structure proves to be a robust indicator of plant diversity. Our proposed multi-platform LiDAR fusion framework enables rapid, precise ecological assessments, providing methodological references and support for the transition from 2D to 3D green quality evaluation in the fine-scale management of similar cities.

Code and data availability

The supplied blocks describe UAV/handheld LiDAR fusion, quadrat surveys, and Random Forest analysis, but contain no public data or code availability statement, no repository deposit, and no authors' URL for datasets, point clouds, or scripts. Supplementary Materials S1–S3 are referenced but no public access location is

No evidence-backed public reproduction asset is currently recorded.