Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry
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ABSTRACT Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process‐oriented investigations of flow hydraulics, sediment dynamics and in‐stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through‐water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. While the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM‐photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary‐winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50–100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM‐photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). Copyright © 2014 John Wiley & Sons, Ltd.
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In lotic settings, the recent use of small UAV and SfM photogrammetric processing has provided a significant improvement in the objectivity, accuracy, and efficiency of physical habitat data collection.
“In lotic settings, the recent use of small unmanned aerial vehicles (UAV) and structurefrom motion (SfM) photogrammetric processing has provided a significant improvement in the objectivity, accuracy, and efficiency of physical habitat data collection (Woodget et al. 2015).”
From Pond ecology and conservation: research priorities and knowledge gaps (2021) · cites this paper as Woodget et al. 2015
The Introduction identifies physical habitat assessment as an application of fluvial topography data and calls for objective, repeatable measurement. Section 5.3 reports that UAS–SfM can produce accurate, precise topographic models and that data collection is relatively rapid. It does not establish a significant improvement in all three qualities for physical habitat data collection; its comparison finds precision at best in line with traditional photogrammetry and sometimes below it. (LLM, conf=0.86)
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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 · see citing works
Riverine landscapes: Biodiversity patterns, disturbance regimes, and aquatic conservation
Ward, J. V. (1998) · Biological Conservation · doi:10.1016/s0006-3207(97)00083-9 · Cited by 731 · cited 1× · see citing works
“…elements of a wider terrestrial landscape (as per Vannote et al., 1980’s River Continuum Concept) to those characterized by high spatial and temporal heterogeneity (Ward, 1998; Lapointe, 2012), and makes this heterogeneity the focus of assessment (Ward, 1998; Fausch et al., 2002; Legleiter, 2014b).”
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Pond ecology and conservation: research priorities and knowledge gaps
Hill, M. J., Greaves, H. M., Sayer, C. D., Hassall, C., Milin, M., Milner, V. S., Marazzi, L., Hall, R., Harper, L. R., Thornhill, I., et al. (2021) · Ecosphere · doi:10.1002/ecs2.3853 · Cited by 156 · see citing works
- Authors
- Woodget, A. S., Carbonneau, P. E., Visser, F., & Maddock, I. P.
- Affiliations
- University of Worcester (GB)
- Durham University (GB)
- Corresponding author
- Woodget, A. S.
- Venue
- Earth Surface Processes and Landforms
- Publisher
- Wiley
- Published
- 2014-08-05
- Volume
- 40
- Issue
- 1
- Pages
- 47-64
- ISSN
- 0197-9337 (ISSN-L)
- 1096-9837
- OpenAlex
- W1773543203
- Cited by
- 424
- References
- 2
- Citations by year
- 2026: 20 · 2025: 23 · 2024: 26 · 2023: 26 · 2022: 36 · 2021: 44 · 2020: 66 · 2019: 43 · 2018: 52 · 2017: 32 · 2016: 37 · 2015: 16 · 2014: 2 · 2013: 1
- FWCI
- 41.93
- Type
- journal article
- Language
- en
- Open access
- green
- orcid.org
- Locations
- Earth Surface Processes and Landforms (publishedVersion)
- Worcester Research and Publications (University of Worcester) (acceptedVersion)
- Durham Research Online (Durham University) (acceptedVersion)
- Durham Research Online (Durham University) (submittedVersion, cc-by)
- Loughborough University Institutional Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Loughborough University Research Repository (Loughborough University) (submittedVersion, cc-by-nc-nd)
- Funders
- British Society for Geomorphology
- Geological Remote Sensing Group
- Institute of Science and Environment, University of Worcester
- Topics
- Physical Sciences › Earth and Planetary Sciences › Geology › 3D Surveying and Cultural Heritage
- Physical Sciences › Environmental Science › Ecology › Hydrology and Sediment Transport Processes
- Physical Sciences › Engineering › Ocean Engineering › Satellite Image Processing and Photogrammetry
- Keywords
- river bedforms, structure-from-motion photogrammetry, unmanned aerial systems, digital elevation model, refraction correction, fluvial geomorphology
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