Sensitivity analysis of the methodology for quantifying cliff erosion using airborne LiDAR - Examples from Cornwall, UK

The widespread problem of coastal cliff erosion and the management of the risk to infrastructure and property calls for robust quantification of cliff erosion rates. Quantification of sea-cliff rates of retreat on an annual to decadal time scale has typically been limited to rapidly eroding soft rock coastlines. This study uses airborne LiDAR technology to estimate cliff volume changes in hard rock environments to determine linear retreat rates. One epoch of LiDAR data was analysed (2007/2008-2010/2011) for ten sites around the coast of the southwest of England (Cornwall), selected due to the spatial variability in regional morphological processes, lithology and wave climate. Quantifying cliff recession rates using two LiDAR-derived Digital Elevation Models (DEM) requires selection of an elevation change threshold, below which the morphology is assumed to have undergone no significant change, referred to as the 'vertical change threshold'. The errors inherent in using LiDAR and the various thresholds at which the data could be evaluated were tested. Linear rates of retreat were found to vary according to the threshold of error chosen, providing decreasing rates with an increase in threshold above 0.2-0.3 m. The rates of retreat observed at some low energy sites was of the same magnitude and in some cases lower (0.01-0.03 m yr-1) than the threshold of error inherent in the LiDAR data (0.03-0.1 m). The results were compared with the rates of retreat obtained from analysis of historic maps in Shoreline Management Plans which are non-statutory strategic assessments of the risks associated with coastal erosion that ultimately inform local and regional policy. Analysis of coastal erosion using LiDAR data tended to highlight the localised failures that occur episodically and which are averaged out in the rates derived from longer term analysis of historic maps. © Coastal Education & Research Foundation 2013.