Earlie, Claire S. ![]() |
Abstract
Coastal cliff erosion is a widespread problem that threatens property and infrastructure along many of the world’s coastlines. Rates of erosion used for shoreline management are generally based on analysis of historic maps and aerial photographs which, in rocky coast environments, does not wholly capture the detail in the processes and the failures occurring across the cliff face. This study uses airborne LiDAR (Light Detection and Ranging) data to gain a quantitative understanding of cliff erosion along rocky coastline where recession rates are relatively low (c. 0.1 m yr−1). It was found that three-dimensional volumetric changes on the cliff face and linear rates of retreat can be reliably calculated from consecutive digital elevation models (DEMs) several years apart. Furthermore, the accuracy of the data on sloping surfaces was tested by applying a threshold below which data that could be construed as error were removed. Using a vertical change threshold of 0.5 m had limited effect on the computed rates of retreat. The spatial variability in recession rates around the coastline was considered in terms of the relationship with the varying boundary conditions (rock mass characteristics, cliff geometries, beach morphology) and forcing parameters (wave climate and wave exposure). Recession rates were statistically correlated with significant wave height (Hs), rock mass characteristics (GSI) and the ratio between the two (GSI/Hs). The current method of assessing rocky cliff recession using maps and aerial photographs tends to not only miss the detail in the three-dimensional nature of the cliff evolution, but may also be too coarse a resolution to capture the small scale changes that contribute to the overall failure. LiDAR data, although limited in its temporal extent due to it being a relatively new technology, is a suitable method of evaluating cliff erosion on a time scale of 3–4 years and provides additional insight into the process occurring in slowly eroding environments.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Earth and Environmental Sciences |
Subjects: | Q Science > QE Geology |
Publisher: | Springer Verlag |
ISSN: | 1400-0350 |
Date of First Compliant Deposit: | 16 January 2017 |
Date of Acceptance: | 15 September 2014 |
Last Modified: | 06 Jan 2024 03:16 |
URI: | https://orca.cardiff.ac.uk/id/eprint/97475 |
Citation Data
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