Automated Mapping of Nearshore, Beach, and Dune Morphology and Linkages to Coastal Processes

Process linkages between the nearshore, beach, and dune and resulting morphology provide an indication of the response of coastal systems to ambient environmental conditions, storm events, and longer-term climate change such as a sea level rise (SLR). With increasing access to large topo-bathymetric datasets, observing the evolution of nearshore and backshore landforms allows for an improved record of change in response to environmental and anthropogenic drivers and can be used to test the validity of conceptual and numerical models at scales previously not possible. Studies that delineate boundaries in the coastal zone (e.g., position of the dune toe) have often used a number of semi-automated extraction techniques based on the 2D shape of the beach-dune profile or from Machine Learning (ML) models that create custom classifiers based on expert interpretation of profiles. While these studies do provide methodologies to efficiently dissect the landscape, they usually require subjective user inputs that limits the repeatability and comparability of these works. As a result, attempts to monitor the response of these systems to storm impacts or SLR are likely to vary between methodologies and the user who deploys them. The purpose of this work is to introduce a user friendly and consistent 3D Relative Relief (RR) approach to automatically map nearshore bar, beach, and dune morphology to better identify coastal landforms and the along- and cross-shore transfer of sediment through time. Preliminary results indicate that the RR methodology used in this study consistently identifies the 3D structure of coastal landforms and outperforms other morphological or ML extraction techniques. This approach can also handle varying beach types (e.g., reflective to dissipative) and multi-temporal change with limited user input, allowing for a repeatable method to map a wide range of sandy coastlines. Ultimately, the goal is to provide a set of opensource mapping tools with broad applications in coastal research that will improve the consistency of observations of coastal landforms and our understanding of their response to climate change.