Articles | Volume 8, issue 6
https://doi.org/10.5194/se-8-1241-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-8-1241-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
Lachlan Grose
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
Anindita Samsu
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
Steven Micklethwaite
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
Stefan A. Vollgger
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
Alexander R. Cruden
School of Earth, Atmosphere and Environment, Monash University,
Melbourne, 3800, Australia
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- Review of drones, photogrammetry and emerging sensor technology for the study of dykes: Best practises and future potential G. Dering et al. 10.1016/j.jvolgeores.2019.01.018
- Modelling the Influence of Geological Structures in Paleo Rock Avalanche Failures Using Field and Remote Sensing Data L. He et al. 10.3390/rs14164090
- Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland M. Sayab et al. 10.3390/rs10081296
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- 3D digital outcrop modelling of the Lower Cretaceous Los Santos formation sandstones, Mesa de Los Santos region (Colombia): Implications for structural analysis C. Villarreal J et al. 10.1016/j.jsg.2020.104214
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Discussed (final revised paper)
Discussed (preprint)
Latest update: 28 Sep 2023
Short summary
We demonstrate a new method that enhances our ability to interpret large datasets commonly used in the earth sciences, including point clouds and rasters. Implemented as plugins for CloudCompare and QGIS, we use a least-cost-path solver to track structures and contacts through data, allowing for expert-guided interpretation in a way that seamlessly utilises computing power to optimise the interpretation process and improve objectivity and consistency.
We demonstrate a new method that enhances our ability to interpret large datasets commonly used...