Assessment of Shoreline Change from SAR Satellite Imagery in Three Tidally Controlled Coastal Environments

Savastano, Salvatore; Gomes da Silva, Paula; Sánchez, Jara Martínez; Tort, Arnau Garcia; Payo, Andres; Pattle, Mark E.; Garcia-Mondéjar, Albert; Castillo, Yeray; Monteys, Xavier. 2024 Assessment of Shoreline Change from SAR Satellite Imagery in Three Tidally Controlled Coastal Environments. Journal of Marine Science and Engineering, 12 (1), 163. https://doi.org/10.3390/jmse12010163

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Abstract/Summary

Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, potentially offering a higher revision period to map shoreline position and change, but this can only be feasible if we have a better interpretation of what shorelines as extracted from SAR imagery represent on the ground. This study aims to assess the application of shorelines extracted from SAR from publicly available satellite imagery to map and capture intra-annual to inter-annual shoreline variability. This is assessed in three tidally controlled coastal study areas that represent sand and gravel beaches with different backshore environments: low-lying dunes and marsh; steep, rocky cliff; and urban environments. We have found that SAR shorelines consistently corresponded to positions above the high-water mark across all three sites. We further discuss the influence of the scene geometry, meteorological and oceanographic conditions, and backshore environment and provide a conceptual interpretation of SAR-derived shorelines. In a low-lying coastal setting, the annual change rate derived through SAR presents a high degree of alignment with the known reference values. The present study contributes to our understanding of the poorly known aspect of using shorelines derived from publicly available SAR satellite missions. It outlines a quantitative approach to automatically assess their quality with a new automatic detection method that is transferable to shoreline evolution assessments worldwide.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/jmse12010163
ISSN:	2077-1312
Date made live:	09 Feb 2024 15:32 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/536879

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