Abstract
This research describes a methodology for acquiring, visualizing, and reconstructing three-dimensional representations of blocky rock masses based on the coordinates of dense surface points. In general, the surface points can be obtained with a variety of sensors and sensor platforms. The workflow described herein considers photogrammetric data sets acquired with Unmanned Aerial Vehicles (UAVs). In the overall, the steps for constructing high resolution 3D geological structural models are: (1) a photogrammetric survey of the investigation area is performed to obtain a true-color georeferenced 3D point cloud; (2) structural geologic measurements are extracted directly from the point cloud or associated digital terrain model (DTM); (3) the 3D rock structure is represented as a discrete fracture network (DFN); (4) identification, computing and visualization of blocks; and (5) on the basis of Block Theory, kinematically removable blocks are identified directly on the point cloud/DTM with embedded DFN and classified according to their criticality.
Original language | English |
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Title of host publication | IAEG/AEG Annual Meeting Proceedings |
Editors | A. Shakoor, K. Cato |
Place of Publication | Cham |
Publisher | Springer International Publishing AG |
Pages | 293-287 |
Number of pages | 5 |
Volume | 1 |
ISBN (Print) | 978-3-319-93124-1 |
DOIs | |
Publication status | Published - 2019 |
Event | 2018 IAEG/AEG Annual Meeting - San Francisco, United States Duration: 17 Sep 2018 → 21 Sep 2018 |
Conference
Conference | 2018 IAEG/AEG Annual Meeting |
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Country/Territory | United States |
City | San Francisco |
Period | 17/09/18 → 21/09/18 |