Impact-Detection Algorithm That Uses Point Clouds as Topographic Inputs for 3D Rockfall Simulations

Geosciences

Jacques Locat¹  Michel Jaboyedoff²  François Noël²  Catherine Cloutier³ 

[1] Natural Hazards Study Laboratory (LERN), Department of Geology and Geological Engineering, Laval University, Québec, QC G1V 0A6, Canada;Risk Analysis Group, Institute of Earth Sciences, University of Lausanne, CH-1015 Lausanne, Switzerland;Rock Mechanics Sector, Department of Geology and Geotechnics, Québec Transport Ministry (MTQ), Québec, QC G1R 5H1, Canada;

关键词: rockfall;    simulation;    impact;    point cloud;    photogrammetry;    SfM;   

DOI  :  10.3390/geosciences11050188

来源: DOAJ

【 摘 要 】

Numerous 3D rockfall simulation models use coarse gridded digital terrain model (DTM raster) as their topography input. Artificial surface roughness is often added to overcome the loss of details that occurs during the gridding process. Together with the use of sensitive energy damping parameters, they provide great freedom to the user at the expense of the objectivity of the method. To quantify and limit the range of such artificial values, we developed an impact-detection algorithm that can be used to extract the perceived surface roughness from detailed terrain samples in relation to the size of the impacting rocks. The algorithm can also be combined with a rebound model to perform rockfall simulations directly on detailed 3D point clouds. The abilities of the algorithm are demonstrated by objectively extracting different perceived surface roughnesses from detailed terrain samples and by simulating rockfalls on detailed terrain models as proof of concept. The results produced are also compared to that of rockfall simulation software CRSP 4, RocFall 8 and Rockyfor3D 5.2.15 as validation. Although differences were observed, the validation shows that the algorithm can produce similar results. With the presented approach not being limited to coarse terrain models, the need for adding artificial terrain roughness or for adjusting sensitive damping parameters on a per-site basis is reduced, thereby limiting the related biases and subjectivity.

【 授权许可】

Unknown