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 can penetrate vegetation cover to acquire a large range of surface data quickly and accurately, which is critical for identifying and analyzing geological hazards. However, in mountainous areas with dense vegetation, especially for remote sensing survey of geological hazards, airborne LiDAR point cloud density lacks a uniform standard. And it is difficult for operators to evaluate the number of ground points under different canopy conditions, resulting in data redundancy and increased cost.

Methods To solve these problems, this paper proposes 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 digital elevation model (DEM). Then the discrete difference peak search method is used 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 with the scale of 1∶200, an average collection point density of not less than 147 points/m² is required, while 70 points/m² corresponding to the scale of 1∶500, 56 points/m² corresponding to the scale of 1∶1 000, and 47 points/m² corresponding to the scale of 1∶2 000.

Conclusions This study provides guidance and reference for airborne LiDAR point cloud data collection in dense vegetation areas, and proposes new ideas and methods for interpretation of geological hazard and other related fields as well.