Abstract

Abstract. Correct quantification of coastal cliff erosion requires accurate delineation of the cliff face bounded by the cliff top and base lines. Manual mapping is time consuming and relies on the mapper's decisions and skills. Existing algorithms are generally site specific and may be less suitable for areas with diverse cross-shore cliff geometries. Here we describe CliffDelineaTool (v1.2.0), a MATLAB/Python-based algorithm that identifies cliff base and top positions on complex cliffs using cross-shore transects extracted from digital elevation models. Testing on four 750–1200 m cliffed coastlines shows that the model performance is comparable to manual mapping and provides some advantages over existing methods but provides poor results for cliff sections with ambiguous cliff top edges. The results can form the basis for a range of analyses, including coastal inventories, erosion measurements, spatiotemporal erosion trends, and coastline evolution modeling.

Highlights

  • Correct quantification of cliff erosion for scientific and management purposes requires accurate delineation of coastal cliff faces

  • Cliff base locations were more consistent between manual mappers and CliffDelineaTool compared to the cliff tops

  • CliffMetrics generally performed better than the distance-to-trendline method, but it had a higher root mean squared error (RMS) compared to CliffDelineaTool

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Summary

Introduction

Correct quantification of cliff erosion for scientific and management purposes requires accurate delineation of coastal cliff faces. Cliff base and top positions are often digitized manually on georeferenced maps, aerial photographs, orthophotographs, and digital elevation models (DEMs) (e.g., Dornbusch et al, 2008; Hapke et al, 2009; Brooks et al, 2012; Orviku et al, 2013; Swirad et al, 2017; Young, 2018). Payo et al (2018) suggested that, for consistency, the mapping should be performed at the same time for the entire dataset, and by one mapper. This becomes problematic for multitemporal studies, and those that build on previous efforts

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