The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology
Open accessAbstract
This contribution reviews the use of modern 3D photo-based surface reconstruction techniques for high fidelity surveys of trenches, rock exposures and hand specimens to highlight their potential for paleoseismology and structural geology. We outline the general approach to data acquisition and processing using ground-based photographs acquired from standard DSLR cameras, and illustrate the use of similar processing approaches on imagery from Unmanned Aerial Vehicles (UAVs). It is shown that digital map and trench data can be acquired at ultra-high resolution and in much shorter time intervals than would be normally achievable through conventional grid mapping. The resulting point clouds and textured models are inherently multidimensional (x, y, z, point orientation, colour, texture), archival and easily transformed into orthorectified photomosaics or digital elevation models (DEMs). We provide some examples for the use of such techniques in structural geology and paleoseismology while pointing the interested reader to free and commercial software packages for data processing, visualization and 3D interpretation. Photogrammetric models serve to act as an ideal electronic repository for critical outcrops and observations, similar to the electronic lab book approach employed in the biosciences. This paper also highlights future possibilities for rapid semi-automatic to automatic interpretation of the data and advances in technology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., & Reynolds, J. M. (2012) · Geomorphology · doi:10.1016/j.geomorph.2012.08.021 · Cited by 4,044
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
(2015) · doi:10.1109/cvpr31182.2015 · Cited by 3,737
Accurate, Dense, and Robust Multiview Stereopsis
Furukawa, Y., & Ponce, J. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.161 · Cited by 3,019
Photo tourism: exploring photo collections in 3D
Snavely, N., Seitz, S. M., & Szeliski, R. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141964 · Cited by 2,866
Modeling the World from Internet Photo Collections
Snavely, N., Seitz, S. M., & Szeliski, R. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0107-3 · Cited by 2,155
Topographic structure from motion: a new development in photogrammetric measurement
Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L., & Carbonneau, P. E. (2013) · Earth Surface Processes and Landforms · doi:10.1002/esp.3366 · Cited by 1,126
James, M. R., & Robson, S. (2012) · Journal of Geophysical Research: Earth Surface · doi:10.1029/2011jf002289 · Cited by 1,116
Self-citationTowards Internet-scale multi-view stereo
Furukawa, Y., Curless, B., Seitz, S. M., & Szeliski, R. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539802 · Cited by 751
Cited by
Structure from motion photogrammetry in physical geography
Smith, M. W., Carrivick, J. L., & Quincey, D. J. (2016) · Progress in Physical Geography: Earth and Environment · doi:10.1177/0309133315615805 · Cited by 772
Applications of UAVs in Civil Infrastructure
Greenwood, W. W., Lynch, J. P., & Zekkos, D. (2019) · Journal of Infrastructure Systems · doi:10.1061/(asce)is.1943-555x.0000464 · Cited by 266
Carbonneau, P. E., & Dietrich, J. T. (2017) · Earth Surface Processes and Landforms · doi:10.1002/esp.4012 · Cited by 258
Metadata
- Authors
- Bemis, S. P., Micklethwaite, S., Turner, D., James, M. R., Akciz, S., Thiele, S. T., & Bangash, H. A.
- Venue
- Journal of Structural Geology
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 69
- Pages
- 163-178
- ISSN
- 0191-8141 (ISSN-L)
- OpenAlex
- W2088331957
- Cited by
- 717
- References
- 38
- FWCI
- 54.28
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology. https://app.cochat.ai/papers/10.1016/j.jsg.2014.10.007
- The paper
- Bemis, S. P., Micklethwaite, S., Turner, D., James, M. R., Akciz, S., Thiele, S. T., & Bangash, H. A. (2014). Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology. Journal of Structural Geology. https://doi.org/10.1016/j.jsg.2014.10.007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.