ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Ecosystem Restoration
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1602740
This article is part of the Research TopicRestoring Our Blue Planet: Advances in Marine and Coastal RestorationView all 7 articles
A Harmonized framework to assess coastal erosion blending Copernicus marine data products and satellite imagery along Greek and Italian shorelines
Provisionally accepted- 1Department of Environmental Engineering, Democritus University of Thrace, Xanthi, East Macedonia and Thrace, Greece
- 2Department of Environmental Sciences, Informatics and Statistics, Ca 'Foscari University of Venice, Venice, Veneto, Italy
- 3Foundation Euro-Mediterranean Center on Climate Change (CMCC), Lecce, Apulia, Italy
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Coastal zones face intensified natural and anthropogenic disturbances, including rising sea levels, coastal erosion, and over-exploitation of resources. Coastal zone monitoring of these effects involves satellite-borne shoreline extraction and detection of change rates over time. Shoreline evolution is directly related to waves, tides, winds, storms, extreme events, sea level change, and human activities affecting the geomorphologic processes of the coast. The shoreline evolution along the study sites (Iera Poli of Messolonghi, Greece, and Ugento Municipality, Italy) was examined and assessed by analyzing historical satellite images, covering the area during the latest decade (2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019). The study focuses on eight geographical sub-areas. The areas were selected based on their high economic and aesthetic values and the potential vulnerability to coastal erosion and climate change impact, as identified by previous studies. The outcome of this analysis offers a useful decision support tool for screening and designing multi-layered adaptation strategies that integrate environmental conservation, coastal protection, and socioeconomic sustainability to enhance long-term coastal resilience.
Keywords: Coastal erosion, Shoreline evolution, Satellite images classification, GIS analysis, Nature-based solutions
Received: 30 Mar 2025; Accepted: 07 Jul 2025.
Copyright: © 2025 Zachopoulos, Kokkos, Dal Barco, Furlan, Pham, Torresan, Critto and Sylaios. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Georgios Sylaios, Department of Environmental Engineering, Democritus University of Thrace, Xanthi, East Macedonia and Thrace, Greece
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