Optimal Point Density of Airborne LiDAR Data Collection for Hazards in Mountainous Areas

Objectives: This research focuses on the application of Airborne Light Detection and Ranging (LiDAR) technology in geological hazard investigation in mountainous areas with dense vegetation. Airborne LiDAR is able to penetrate vegetation cover to acquire a large range of surface data quickly and accurately, which is critical for identifying and analyzing geological hazards. However, on the one hand, in densely vegetated areas, especially in the field of remote sensing survey of geological hazards, airborne LiDAR point cloud density lacks a uniform standard. On the other hand, it is difficult for operators to evaluate the number of ground points under different canopy conditions, resulting in data redundancy and increased costs. Methods: To solve the above problems, this paper presents a method for calculating the optimal collection point density. On the basis of satisfying the surveying standard and combining the effect of visual interpretation, the local terrain complexity is used as the criterion to evaluate DEM, then using the discrete difference peak search method to determine the optimal collection point density under different scale and canopy density. Results: In order to obtain precise DEM for geological hazard interpretation in densely vegetated areas under 1:200 survey scale, an average collection point density of not less than 147 points/m² is required; 1:500 corresponds to 70 points/m²; 1:1000 corresponds to 56 points/m²; 1:2000 corresponds to 47 points/m². Conclusion: This study provides guidance for airborne LiDAR point cloud data collection in dense vegetation areas, new ideas and methods for geological hazard interpretation and other related fields as well.