期刊
ISRM EUROPEAN ROCK MECHANICS SYMPOSIUM EUROCK 2017
卷 191, 期 -, 页码 838-845出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.proeng.2017.05.251
关键词
SfM; LiDAR; rock mass; discontinuity; orientation
资金
- University of Alicante [vigrob-157, GRE 14-04]
- Generalitat Valenciana [GV/2011/044, ACOMP/2014/136]
- Spanish Ministry of Economy and Competitiveness (MINECO)
- EU FEDER [TIN2014-55413-C2-2-P]
- H2020 Marie Curie Intra European Fellowship
Discontinuities play a key role in the mechanical, hydraulic and deformational behaviour of rock masses, frequently having a considerable influence on the stability of rock slopes. They can be characterized by several geometric parameters as the orientation, persistence, spacing, etc. Although orientation has been traditionally measured through well-known techniques as a compass, more recent remote sensing techniques such as 3D laser scanning allow deriving both strike and dip direction of discontinuities. The novel SfM (Structure from Motion) technique, which is much less expensive than 3D laser scanning, is becoming mainstream within the research community. This paper examines the generation of 3D point clouds of a rock slope obtained from both, 3D laser scanning and SfM techniques, and their application to the extraction of the orientations of the main discontinuity sets. To this aim, a selected sector from a cretaceous sedimentary rock cut slope placed in Alicante (Spain) is analyzed using both photogrammetric and terrestrial laser scanner (TLS) point clouds. Using ground control points extracted from printed targets scanned by means of TLS provided very accurate coordinates. As a result of this, the obtained adjustment error was minor than 3 mm. The comparison of the resulting point clouds shows a good correlation when the surface is orthogonal to the line of sight. On the contrary, the SfM dataset showed inaccuracies on sub-horizontal and oblique surfaces. Finally, a geometrical analysis was performed by means of DSE software. Three discontinuity sets were extracted from both point clouds. However, one more was extracted from the TLS dataset, but not from the SfM dataset. (C) 2017 The Authors. Published by Elsevier Ltd.
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