ArticleScientific reports2025
Analyzing coastal dynamics by means of multi-sensor satellite imagery at the East Frisian Island of Langeoog, Germany.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Monitoring coastal dynamics is critical for the effective protection of coastal environments. Satellite remote sensing data offers significant potential to support this monitoring while also addressing the considerable challenges posed by the rapidly changing environmental conditions in coastal regions, such as tidal levels and currents. These challenges are particularly pronounced in meso- and macrotidal coastal areas. The goal of this study is to evaluate the effectiveness of a multi-sensor satellite remote sensing-based approach to assess coastal dynamics in a mesotidal environment, using the Island of Langeoog, Germany, as a case study. This approach also addresses the often limited availability of in-situ data in such regions. We employed high-resolution (HR) and medium-resolution (MR) optical data, alongside very high-resolution (VHR) Synthetic Aperture Radar (SAR) data, to detect coastal changes by analyzing several proxies, including the migration of sand bars, waterline position, dune toe location, and the extent of dry sandy coastal areas. To achieve this, we assessed and integrated thresholding and classification methods based on their suitability for specific sensors and proxies. Our findings demonstrate that combining different sensor types enables a more comprehensive analysis of various proxies of coastal dynamics. We successfully extracted instantaneous waterlines and identified migrating sand bars, linking these results to shoreline positions. Furthermore, our analysis revealed the direct influence of replenishment measures on beach conditions and suggested a stabilizing effect on the protective dune system. The findings display the uncertainties due to wave run-up and short-term variations in water level associated with analyzing dynamic meso-tidal sandy beach areas. Our results underscore the significant potential of multi-sensor data integration and diverse methodological approaches for supporting coastal protection authorities assessing the state of beaches.
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