Kinematic analysis of sea cliff stability using UAV photogrammetry

Barlow, John; Gilham, Jamie; Ibarra, Ignacio

Abstract

Erosion and slope instability poses a significant hazard to communities and infrastructure located in coastal areas. We use point cloud and spectral data derived from close-range digital photogrammetry to perform a kinematic analysis of chalk sea cliffs located at Telscombe, UK. Our data were captured from an unmanned aerial vehicle (UAV) and cover a cliff face that is about 750 m long and ranges from 20 to 49 m in height. The resulting point clouds had an average density of 354 points m−2. The models fitted our ground control network within a standard error of 0.03 m. Structural features such as joints, bedding planes, and faults were manually mapped and are consistent with results from other studies that have been conducted using direct measurement in the field. These data were then used to assess differing modes of failure at the site. Our results indicate that wedge failure is by far the most likely mode of slope instability. A large wedge failure occurred at the site during the period of study supporting our analysis. Volumetric analysis of this failure through a comparison of sequential models indicates a failure volume of about 160 m3. Our results show that data capture through UAV photogrammetry can provide a useful basis for slope stability analysis over long sections of coast. This technology offers significant benefits in equipment costs and field time over existing methods.

Citation

Barlow, J., Gilham, J., & Ibarra, I. (2017). Kinematic analysis of sea cliff stability using UAV photogrammetry. International Journal of Remote Sensing, 38(8-10), 2464-2479. https://doi.org/10.1080/01431161.2016.1275061

• Journal Article Type: Article
• Acceptance Date: Dec 8, 2016
• Online Publication Date: Jan 13, 2017
• Publication Date: 2017
• Deposit Date: Jan 28, 2021
• Journal: International Journal of Remote Sensing
• Print ISSN: 0143-1161
• Electronic ISSN: 1366-5901
• Publisher: Taylor and Francis Group
• Volume: 38
• Issue: 8-10
• Pages: 2464-2479
• DOI: https://doi.org/10.1080/01431161.2016.1275061
• Public URL: https://durham-repository.worktribe.com/output/1253392