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 speci...

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Published in:Solid Earth
Main Authors: Thiele, Samuel T., Grose, Lachlan, Samsu, Anindita, Micklethwaite, Steven, Vollgger, Stefan A., Cruden, Alexander R.
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/se-8-1241-2017
https://se.copernicus.org/articles/8/1241/2017/
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spelling ftcopernicus:oai:publications.copernicus.org:se60748 2023-05-15T17:34:32+02:00 Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data Thiele, Samuel T. Grose, Lachlan Samsu, Anindita Micklethwaite, Steven Vollgger, Stefan A. Cruden, Alexander R. 2018-09-27 application/pdf https://doi.org/10.5194/se-8-1241-2017 https://se.copernicus.org/articles/8/1241/2017/ eng eng doi:10.5194/se-8-1241-2017 https://se.copernicus.org/articles/8/1241/2017/ eISSN: 1869-9529 Text 2018 ftcopernicus https://doi.org/10.5194/se-8-1241-2017 2020-07-20T16:23:29Z 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. 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 M w 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. Text North Atlantic Copernicus Publications: E-Journals New Zealand Solid Earth 8 6 1241 1253
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description 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. 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 M w 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.
format Text
author Thiele, Samuel T.
Grose, Lachlan
Samsu, Anindita
Micklethwaite, Steven
Vollgger, Stefan A.
Cruden, Alexander R.
spellingShingle Thiele, Samuel T.
Grose, Lachlan
Samsu, Anindita
Micklethwaite, Steven
Vollgger, Stefan A.
Cruden, Alexander R.
Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
author_facet Thiele, Samuel T.
Grose, Lachlan
Samsu, Anindita
Micklethwaite, Steven
Vollgger, Stefan A.
Cruden, Alexander R.
author_sort Thiele, Samuel T.
title Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
title_short Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
title_full Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
title_fullStr Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
title_full_unstemmed Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
title_sort rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data
publishDate 2018
url https://doi.org/10.5194/se-8-1241-2017
https://se.copernicus.org/articles/8/1241/2017/
geographic New Zealand
geographic_facet New Zealand
genre North Atlantic
genre_facet North Atlantic
op_source eISSN: 1869-9529
op_relation doi:10.5194/se-8-1241-2017
https://se.copernicus.org/articles/8/1241/2017/
op_doi https://doi.org/10.5194/se-8-1241-2017
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