Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers

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Tiede, J.; Jordan, C.; Moghimi, A.; Schlurmann, T.: Long-term shoreline changes at large spatial scales at the Baltic Sea: remote-sensing based assessment and potential drivers. In: Frontiers in Marine Science 10 (2023), 1207524. DOI: https://doi.org/10.3389/fmars.2023.1207524

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/14722

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Sum total of downloads: 79




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Abstract: 
In this study, we demonstrate how freely available satellite images can be used to understand large-scale coastline developments along the coast of Mecklenburg-Western Pomerania (MWP). By validating the resulting dataset with an independent Light Detection and Ranging (LIDAR) dataset, we achieved a high level of accuracy for the calculation of rates of change (ROC) with a root mean square error (RMSE) of up to 0.91 m, highlighting the reliability of Earth observation data for this purpose. The study assessed the coastal system’s natural evolution from 1984 to 1990, prior to significant human interventions, and examined the period from 1996 to 2022, which was characterized by regular sand nourishments amounting to approximately 16 million m³. The results reveal notable changes in the study area, with a significant decline in erosive trends and an increase in the number of stable and accreting transects. However, it is important to note that the regular sand nourishments may be masking the true ROC along the coastline. Furthermore, the future supply of sand raises concerns about the sustainability of coastal developments, particularly in the context of future sea level rise (SLR). The study provides valuable insights for coastal authorities and policymakers, informing decisions on sand resource allocation and highlighting the need for appropriate adaptation strategies to address future SLR and ensure long-term coastal resilience.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 34 43.04%
2 image of flag of United States United States 12 15.19%
3 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 6 7.59%
4 image of flag of United Kingdom United Kingdom 5 6.33%
5 image of flag of India India 4 5.06%
6 image of flag of Taiwan Taiwan 3 3.80%
7 image of flag of Poland Poland 3 3.80%
8 image of flag of Japan Japan 2 2.53%
9 image of flag of France France 2 2.53%
10 image of flag of Estonia Estonia 2 2.53%
    other countries 6 7.59%

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