Development of an automatic delineation of cliff top and toe on very irregular planform coastlines (CliffMetrics v1.0)

Abstract

Abstract. We describe a new algorithm that automatically delineates the cliff top and toe of a cliffed coastline from a digital elevation model (DEM). The algorithm builds upon existing methods but is specifically designed to resolve very irregular planform coastlines with many bays and capes, such as parts of the coastline of Great Britain. The algorithm automatically and sequentially delineates and smooths shoreline vectors, generates orthogonal transects and elevation profiles with a minimum spacing equal to the DEM resolution, and extracts the position and elevation of the cliff top and toe. Outputs include the non-smoothed raster and smoothed vector coastlines, normals to the coastline (as vector shape files), xyz profiles (as comma-separated-value, CSV, files), and the cliff top and toe (as point shape files). The algorithm also automatically assesses the quality of the profile and omits low-quality profiles (i.e. extraction of cliff top and toe is not possible). The performance of the proposed algorithm is compared with an existing method, which was not specifically designed for very irregular coastlines, and to manually digitized boundaries by numerous professionals. Also, we assess the reproducibility of the results using different DEM resolutions (5, 10 and 50 m), different user-defined parameter sets related to the degree of coastline smoothing, and the threshold used to identify the cliff top and toe. The model output sensitivity is found to be smaller than the manually digitized uncertainty. The code and a manual are publicly available on a GitHub repository.

A Method to Extract Measurable Indicators of Coastal Cliff Erosion from Topographical Cliff and Beach Profiles: Application to North Norfolk and Suffolk, East England, UK

“…As it was not clear from [3] how the cliff top and BWA were calculated, we have described how the cliff top, toe, and BWA are extracted from elevation profile data, and provided the scripts used as Supplementary Materials for anyone interested in repeating the analysis elsewhere. This automatic extraction of the cliff top and toe locations and BWA is an extension of the ClifMetrics approach presented by [19]. In particular, we have shown how cliff top and toe locations can be more accurately estimated by a two-step detrending process of the elevation profiles ( Figure 2b).…”

“…We extracted the cliff top and toe locations from the topographic elevation profiles following a two-step detrending method, as illustrated in Figure 2. This iterative method is an extension of the method proposed by [19], where the cliff top and toe were extracted as the maximum and minimum, respectively, from the detrended elevation profile. We noticed that for some geometries, the cliff top and toe locations might differ from what intuitively would have been noted by a human (i.e., this was also noticed in [19]), resulting in unrealistically different cliff top erosion rates from the ones reported by Lee [3].…”

“…This iterative method is an extension of the method proposed by [19], where the cliff top and toe were extracted as the maximum and minimum, respectively, from the detrended elevation profile. We noticed that for some geometries, the cliff top and toe locations might differ from what intuitively would have been noted by a human (i.e., this was also noticed in [19]), resulting in unrealistically different cliff top erosion rates from the ones reported by Lee [3]. This misplacement of the cliff top and toe is due to the sensitivity of the detrended maximum and minimum horizontal locations to the landward and seaward limits used for detrending.…”

The application of data innovations to geomorphological impact analyses in coastal areas: An East Anglia, UK, case study

“…Top/Base of cliff values were then compared for two or more epochs (Figure 7). This method bypasses requirements for manual digitisation, as do other recently developed techniques (Payo et al, 2018a). Within the BDB software there is also an option to complete volume calculations relative to a vertical or inclined reference plane.…”

IoT-Based Geotechnical Monitoring of Unstable Slopes for Landslide Early Warning in the Darjeeling Himalayas

“…These thresholds can be used to determine the temporal probability of the occurrence of landslides as a part of a landslide early warning system (LEWS). The thresholds can be estimated using empirical methods [9][10][11][12], probabilistic methods [8,13,14], and/or physical methods [15,16], and we can use other tools like geographic information system (GIS) [17] and global positioning system (GPS) [18,19] and new technologies in order to make the calculation processes automatic [20,21]. When long-term monitoring data is not available for the study area, it is often difficult to identify the triggering rainfall corresponding to landslides [22].…”