Erosion and slope instability poses a significant hazard to communities and infrastructure located is 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 m 3. 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.

Roger (2019) Detection and analysis of mass wasting events in chalk sea cliffs using UAV photogrammetry. Engineering Geology, 25. pp. 101-112.

Coastal cliff erosion represents a significant geohazard for people and infrastructure. Forecasting future erosion rates is therefore of critical importance to ensuring the resiliency of coastal communities. We use high precision monitoring of chalk cliffs at Telscombe, UK to generate monthly mass movement inventories between August 2016 and July 2017. Frequency-magnitude analysis of our inventories demonstrate negative power law scaling over 7 orders of magnitude and, for the first time, we report statistically significant correlations between significant wave height (H s ) and power law scaling coefficients (r 2 values of 0.497 and 0.590 for β and s respectively). Applying these relationships allows for a quantitative method to predict erosion at the site based on H s probabilities and sea level forecasts derived from the UKCP09 medium emission climate model (A1B). Monte-Carlo simulations indicate a range of possible erosion scenarios over 70 years and we assess the impact these may have on the A259 coastal road which runs proximal to the cliffs. Results indicate a small acceleration in erosion compared with those based on current conditions with the most likely scenario at the site being 21.7 m of cliff recession by 2090. However, low-probability events can result in recession an order of magnitude higher in some scenarios. In the absence of negative feedbacks, we estimate an~11% chance that the A259 will be breached by coastal erosion by 2090.

Prediction of rock slide events remains a difficult task for geoscientists. Kinematic analysis provides an indication of possible modes of failure at a site. However, the highly variable nature of chalk compressive strength due to variations in water content and salt weathering is such that parameterizing models of slope stability can result in large variations in the resultant factor of safety. In this work, we use high-precision monitoring data of an eroding coastal cliff to characterize the geometry a large wedge failure in chalk. We use these data in conjunction with published material properties to model the joint compressive strength of the chalk at the time of failure through back analysis. Results indicate a strength of 7.19 KPa for the chalk suggesting that the joint surface was close to saturation at the time of failure.