Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe
Abstract Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. H...
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Nature Portfolio
2024-06-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-63849-4 |
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| author | Bruno Castelle Etiënne Kras Gerd Masselink Tim Scott Aikaterini Konstantinou Arjen Luijendijk |
| author_facet | Bruno Castelle Etiënne Kras Gerd Masselink Tim Scott Aikaterini Konstantinou Arjen Luijendijk |
| author_sort | Bruno Castelle |
| collection | DOAJ |
| description | Abstract Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. Here we validate and analyse satellite-derived-shoreline positions (1984–2021) along the Atlantic coast of Europe using a moving-averaged approach based on coastline characteristics, indicating conservative uncertainties of long-term trends around 0.4 m/year and a potential bias towards accretion. We show that west-facing open coasts are more prone to long-term erosion, whereas relatively closed coasts favor accretion, although most of computed trends fall within the range of uncertainty. Interannual shoreline variability is influenced by regionally dominant atmospheric climate indices. Quasi-straight open coastlines typically show the strongest and more alongshore-uniform links, while embayed coastlines, especially those not exposed to the dominant wave climate, show weaker and more variable correlation with the indices. Our results provide a spatial continuum between previous local-scale studies, while emphasizing the necessity to further reduce satellite-derived shoreline trend uncertainties. They also call for applications based on a relevant averaging approach and the inclusion of coastal setting parameters to unravel the forcing-response spectrum of sandy shorelines globally. |
| format | Article |
| id | doaj-art-95fc57b6a49c4a029912d480fb77ed24 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-95fc57b6a49c4a029912d480fb77ed242025-01-12T12:24:52ZengNature PortfolioScientific Reports2045-23222024-06-0114111510.1038/s41598-024-63849-4Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of EuropeBruno Castelle0Etiënne Kras1Gerd Masselink2Tim Scott3Aikaterini Konstantinou4Arjen Luijendijk5Univ. Bordeaux, CNRS, Bordeaux INP, EPOC UMR 5805DeltaresCoastal Processes Research Group, School of Biological and Marine Sciences, University of PlymouthCoastal Processes Research Group, School of Biological and Marine Sciences, University of PlymouthCoastal Processes Research Group, School of Biological and Marine Sciences, University of PlymouthDeltaresAbstract Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. Here we validate and analyse satellite-derived-shoreline positions (1984–2021) along the Atlantic coast of Europe using a moving-averaged approach based on coastline characteristics, indicating conservative uncertainties of long-term trends around 0.4 m/year and a potential bias towards accretion. We show that west-facing open coasts are more prone to long-term erosion, whereas relatively closed coasts favor accretion, although most of computed trends fall within the range of uncertainty. Interannual shoreline variability is influenced by regionally dominant atmospheric climate indices. Quasi-straight open coastlines typically show the strongest and more alongshore-uniform links, while embayed coastlines, especially those not exposed to the dominant wave climate, show weaker and more variable correlation with the indices. Our results provide a spatial continuum between previous local-scale studies, while emphasizing the necessity to further reduce satellite-derived shoreline trend uncertainties. They also call for applications based on a relevant averaging approach and the inclusion of coastal setting parameters to unravel the forcing-response spectrum of sandy shorelines globally.https://doi.org/10.1038/s41598-024-63849-4Sandy coastClimate indicesSatellite-derived shorelineLong-term erosionInterannual variabilityCoastal settings |
| spellingShingle | Bruno Castelle Etiënne Kras Gerd Masselink Tim Scott Aikaterini Konstantinou Arjen Luijendijk Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe Scientific Reports Sandy coast Climate indices Satellite-derived shoreline Long-term erosion Interannual variability Coastal settings |
| title | Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe |
| title_full | Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe |
| title_fullStr | Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe |
| title_full_unstemmed | Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe |
| title_short | Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe |
| title_sort | satellite derived sandy shoreline trends and interannual variability along the atlantic coast of europe |
| topic | Sandy coast Climate indices Satellite-derived shoreline Long-term erosion Interannual variability Coastal settings |
| url | https://doi.org/10.1038/s41598-024-63849-4 |
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