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http://dx.doi.org/10.7474/TUS.2021.31.1.010

Technical Development for Extraction of Discontinuities in Rock Mass Using LiDAR  

Lee, Hyeon-woo (Dept. of Integrated Energy and Infra system, Kangwon National University)
Kim, Byung-ryeol (Korea Institute of Limestone & Advanced Materials)
Choi, Sung-oong (Dept. of Energy and Resources Engineering/Integrated Energy and Infra system, Kangwon National University)
Publication Information
Tunnel and Underground Space / v.31, no.1, 2021 , pp. 10-24 More about this Journal
Abstract
Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.
Keywords
Rock mass classification; Discontinuity; Point cloud; LiDAR;
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