Articles | Volume 11, issue 5
https://doi.org/10.5194/se-11-1773-2020
© Author(s) 2020. 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-11-1773-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Sep 2020
Research article |
| 18 Sep 2020
| 18 Sep 2020
Mapping the fracture network in the Lilstock pavement, Bristol Channel, UK: manual versus automatic
Christopher Weismüller
CORRESPONDING AUTHOR
Neotectonics and Natural Hazards, RWTH Aachen University, Aachen,
Germany
Rahul Prabhakaran
Department of Geoscience and Engineering, Delft University of
Technology, Delft, the Netherlands
Department of Mechanical Engineering, Eindhoven University of
Technology, the Netherlands
Martijn Passchier
Structural Geology, Tectonics and Geomechanics, RWTH Aachen
University, Aachen, Germany
Janos L. Urai
Structural Geology, Tectonics and Geomechanics, RWTH Aachen
University, Aachen, Germany
Giovanni Bertotti
Department of Geoscience and Engineering, Delft University of
Technology, Delft, the Netherlands
Klaus Reicherter
Neotectonics and Natural Hazards, RWTH Aachen University, Aachen,
Germany
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Cited
13 citations as recorded by crossref.
- Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data S. Gantimurova & A. Parshin 10.3390/rs16010177
- The influence of subseismic-scale fracture interconnectivity on fluid flow in fracture corridors of the Brejões carbonate karst system, Brazil C. Furtado et al. 10.1016/j.marpetgeo.2022.105689
- Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops R. Prabhakaran et al. 10.1016/j.jsg.2021.104405
- Modelling geological CO2 leakage: Integrating fracture permeability and fault zone outcrop analysis R. Rizzo et al. 10.1016/j.ijggc.2024.104105
- Enhancing fracture network characterization: A data-driven, outcrop-based analysis W. Zhu et al. 10.1016/j.compgeo.2022.104997
- DFN: An Emerging Tool for Stochastic Modelling and Geomechanical Design P. Kolapo et al. 10.3390/eng4010011
- Investigating spatial heterogeneity within fracture networks using hierarchical clustering and graph distance metrics R. Prabhakaran et al. 10.5194/se-12-2159-2021
- Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis A. Marques et al. 10.1109/ACCESS.2022.3151897
- Scale-dependent fracture networks S. Forstner & S. Laubach 10.1016/j.jsg.2022.104748
- Are open-source aerial images useful for fracture network characterisation? Insights from a multi-scale approach in the Zagros Mts. M. Mercuri et al. 10.1016/j.jsg.2023.104866
- The joint sets on the Lilstock Benches, UK. Observations based on mapping a full resolution UAV-based image M. Passchier et al. 10.1016/j.jsg.2021.104332
- A novel multi-scale approach to fault network analysis and visualization: test case Franconian Platform (SE Germany) J. Wiest et al. 10.1016/j.jsg.2025.105481
- Automatically identifying geometrical information of natural joint traces based on Hough transform detection method Z. Li et al. 10.1007/s12303-025-00012-9
13 citations as recorded by crossref.
- Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data S. Gantimurova & A. Parshin 10.3390/rs16010177
- The influence of subseismic-scale fracture interconnectivity on fluid flow in fracture corridors of the Brejões carbonate karst system, Brazil C. Furtado et al. 10.1016/j.marpetgeo.2022.105689
- Large-scale natural fracture network patterns: Insights from automated mapping in the Lilstock (Bristol Channel) limestone outcrops R. Prabhakaran et al. 10.1016/j.jsg.2021.104405
- Modelling geological CO2 leakage: Integrating fracture permeability and fault zone outcrop analysis R. Rizzo et al. 10.1016/j.ijggc.2024.104105
- Enhancing fracture network characterization: A data-driven, outcrop-based analysis W. Zhu et al. 10.1016/j.compgeo.2022.104997
- DFN: An Emerging Tool for Stochastic Modelling and Geomechanical Design P. Kolapo et al. 10.3390/eng4010011
- Investigating spatial heterogeneity within fracture networks using hierarchical clustering and graph distance metrics R. Prabhakaran et al. 10.5194/se-12-2159-2021
- Adaptive Segmentation for Discontinuity Detection on Karstified Carbonate Outcrop Images From UAV-SfM Acquisition and Detection Bias Analysis A. Marques et al. 10.1109/ACCESS.2022.3151897
- Scale-dependent fracture networks S. Forstner & S. Laubach 10.1016/j.jsg.2022.104748
- Are open-source aerial images useful for fracture network characterisation? Insights from a multi-scale approach in the Zagros Mts. M. Mercuri et al. 10.1016/j.jsg.2023.104866
- The joint sets on the Lilstock Benches, UK. Observations based on mapping a full resolution UAV-based image M. Passchier et al. 10.1016/j.jsg.2021.104332
- A novel multi-scale approach to fault network analysis and visualization: test case Franconian Platform (SE Germany) J. Wiest et al. 10.1016/j.jsg.2025.105481
- Automatically identifying geometrical information of natural joint traces based on Hough transform detection method Z. Li et al. 10.1007/s12303-025-00012-9
Latest update: 24 Jun 2025
Short summary
We photographed a fractured limestone pavement with a drone to compare manual and automatic fracture tracing and analyze the evolution and spatial variation of the fracture network in high resolution. We show that automated tools can produce results comparable to manual tracing in shorter time but do not yet allow the interpretation of fracture generations. This work pioneers the automatic fracture mapping of a complete outcrop in detail, and the results can be used as fracture benchmark.
We photographed a fractured limestone pavement with a drone to compare manual and automatic...
