Articles | Volume 8, issue 6
https://doi.org/10.5194/se-8-1241-2017
https://doi.org/10.5194/se-8-1241-2017
Method article
 | 
21 Dec 2017
Method article |  | 21 Dec 2017

Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data

Samuel T. Thiele, Lachlan Grose, Anindita Samsu, Steven Micklethwaite, Stefan A. Vollgger, and Alexander R. Cruden

Viewed

Total article views: 8,355 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,997 3,089 269 8,355 193 199
  • HTML: 4,997
  • PDF: 3,089
  • XML: 269
  • Total: 8,355
  • BibTeX: 193
  • EndNote: 199
Views and downloads (calculated since 15 Aug 2017)
Cumulative views and downloads (calculated since 15 Aug 2017)

Viewed (geographical distribution)

Total article views: 8,355 (including HTML, PDF, and XML) Thereof 7,573 with geography defined and 782 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (final revised paper)

Discussed (preprint)

Latest update: 16 Jun 2024
Download
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.