Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
The advent of large digital datasets from unmanned aerial vehicle (UAV) and satellite platforms now challenges our ability to extract information across multiple scales in a timely manner, often meaning that the full value of the data is not realised. Here we adapt a least-cost-path solver and sp...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-12-01
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| Series: | Solid Earth |
| Online Access: | https://www.solid-earth.net/8/1241/2017/se-8-1241-2017.pdf |
| Summary: | The advent of large digital datasets from unmanned aerial vehicle (UAV) and
satellite platforms now challenges our ability to extract information across
multiple scales in a timely manner, often meaning that the full value of the
data is not realised. Here we adapt a least-cost-path solver and specially
tailored cost functions to rapidly interpolate structural features between
manually defined control points in point cloud and raster datasets. We
implement the method in the geographic information system QGIS and the point
cloud and mesh processing software CloudCompare. Using these implementations,
the method can be applied to a variety of three-dimensional (3-D) and
two-dimensional (2-D) datasets, including high-resolution aerial
imagery, digital outcrop models, digital elevation models (DEMs) and
geophysical grids.
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We demonstrate the algorithm with four diverse applications
in which we extract (1) joint and
contact patterns in high-resolution orthophotographs, (2) fracture patterns
in a dense 3-D point cloud, (3) earthquake surface ruptures of the Greendale
Fault associated with the <i>M</i><sub>w</sub>7.1 Darfield earthquake (New Zealand)
from high-resolution light detection and ranging (lidar) data, and
(4) oceanic fracture zones from bathymetric data of the North Atlantic. The
approach improves the consistency of the interpretation process while
retaining expert guidance and achieves significant improvements
(35–65 %) in digitisation time compared to traditional methods.
Furthermore, it opens up new possibilities for data synthesis and can
quantify the agreement between datasets and an interpretation. |
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| ISSN: | 1869-9510 1869-9529 |