Objectives Geohazard recognition and inventory mapping are the basis for geohazard susceptibility mapping, monitoring and early warning.However, it has been challenging to implement geohazard recognition and inventory mapping in mountainous areas with complex topography and vegetation cover though manual field survey or satellite remote sensing.Progress in the light detection and ranging(LiDAR) technology provides a new possibility for geohazard recognition in such areas.
Methods A high-resolution digital elevation model (DEM) was generated through the LiDAR point filtering and spatial interpolation, and combined with the DEM visualization method of sky view factor(SVF). Subsequently, the geohazard recognition work of Danba County and its surrounding area with a total area of 135 km2 was carried out.
Results A total of 146 geohazards are remotely mapped and classified as slides, rock fall, debris flows based on morphologic characteristics, it shows nearly one-third of the study area is dominated by geohazards. Field validation indicate the success rate of LiDAR-derived DEM in recognition and mapping landslides with higher precision and accuracy. On the basis of this, the spatial distribution characteristics and influencing factors of the geohazards were analyzed and it indicate these mapped geohazards lie along both sides of the river, and their spatial distributions are related highly to human engineering activities, such as road excavation and slope cutting.
Conclusions The research results provide references for geohazard recognition and mapping in mountainous areas with complex topography and vegetation cover and provide data support for the geohazard prevention and risk assessment for Danba county.