Assessment of shoreline change from SAR satellite imagery in three tidally controlled coastal environments
Ver/ Abrir
Registro completo
Mostrar el registro completo DCAutoría
Savastano, Salvatore; Gomes da Silva, Paula; Martinez Sanchez, Jara; García Tort, Arnau; Payo, Andrés; Pattle, Mark E.; Garcia-Mondéjar, Albert; Castillo, Yeray; Monteys, XavierFecha
2024-01-15Derechos
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution( CC BY) license.
Publicado en
Journal of Marine Science and Engineering, 2024, 12, 163
Editorial
MDPI
Enlace a la publicación
Palabras clave
Coastal erosion
Earth observation
Remote sensing
Shoreline
SAR
Resumen/Abstract
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.
Colecciones a las que pertenece
- D56 Artículos [243]