Abstract
Geological hazard identification serves as the foundation for disaster susceptibility assessment, monitoring, and early warning. Conventional manual ground surveys and satellite remote sensing encounter substantial difficulties in identifying geological hazards in high-vegetation-covered mountainous regions with complex terrain conditions. The advancement of airborne Light Detection and Ranging (LiDAR) technology offers a novel solution for geological hazard identification in such complex, high-vegetation mountainous areas. Utilizing acquired airborne LiDAR point cloud data, high-resolution Digital Elevation Models (DEM) were generated through point cloud filtering and spatial interpolation. In conjunction with DEM visualization methods incorporating Sky View Factor (SVF), geological hazard identification research was conducted across an area of 135 km² surrounding Danba County in Sichuan Province, China. A total of 146 geological hazards were interpreted, with a combined area of approximately 46.48 km², representing 33.4% of the total study area. The reliability of the airborne LiDAR identification results was validated through field investigations. Subsequently, the spatial distribution patterns of geological hazards in this region and their influencing factors were analyzed. The findings provide a reference for geological hazard identification in high-vegetation-covered complex mountainous areas and provide data support for geological hazard prevention and risk assessment in Danba County.
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Preamble
Geohazard Recognition by Airborne LiDAR Technology in Complex Mountain Areas
Guo Chen¹, Xu Qiang¹, Dong Xiujun¹, Liu Xiaosha¹, She Jinxing²
¹State Key Laboratory of Geohazards Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059
²College of Earth Science, Chengdu University of Technology, Chengdu 610059
Abstract
Geohazard identification is fundamental to disaster susceptibility assessment and monitoring/early warning efforts. However, traditional manual ground surveys and satellite remote sensing encounter significant challenges in topographically complex, high-vegetation mountain areas. Airborne Light Detection and Ranging (LiDAR) technology has emerged as a promising solution for geohazard recognition in such environments.
This study utilized airborne LiDAR point cloud data to generate high-resolution digital elevation models (DEMs) through point cloud filtering and spatial interpolation. By combining these DEMs with a visualization method based on sky view factor (SVF), we conducted comprehensive geohazard identification across a 135 km² area surrounding Danba County in Sichuan Province, China.
A total of 146 geohazards were interpreted, covering approximately 46.48 km² and representing 33.4% of the study area. Field investigations confirmed the reliability of the LiDAR-based identification results. We subsequently analyzed the spatial distribution patterns of these geohazards and their influencing factors in the region.
The findings provide valuable reference for geohazard identification in high-vegetation complex mountain areas and offer critical data support for geohazard prevention and risk assessment in Danba County.
Keywords: geohazard identification; airborne LiDAR; remote sensing interpretation; sky view factor; complex mountain areas