Integrated perspectives on shoreline and submerged morphology: an innovative geospatial approach to coastal monitoring

Accurate shoreline mapping in micro-tidal and tectonically active environments is often constrained by sensor limitations and hydrodynamic variability. This study evaluates the positional accuracy of shorelines derived from Sentinel-2, Landsat-8, Sentinel-1, and Copernicus DEM datasets using a scalable Google Earth Engine workflow. Centimeter-scale UAV-SfM models served as the reference in two contrasting coastal areas in northwestern Türkiye: the rocky coast of Güneyli and the urbanized sandy shoreline of Altınova. Transect-based analyses reveal comparable positional uncertainties among all satellite products, with RMSE values typically ranging from 8-15 m. Results indicate that shoreline accuracy is primarily limited by environmental noise, particularly wave run-up, rather than sensor resolution alone. Accordingly, we propose a tiered monitoring framework that integrates satellite observations for high-frequency regional mapping with UAV-SfM surveys for high-precision baselines. Satellite imagery enables horizontal shoreline mapping, while UAV photogrammetry provides 3D reconstruction of submerged coastal features relevant to coastal evolution and tectonic deformation.