With increasing storminess and incessant sea-level rise, coastal erosion is becoming a primary issue along many litto-rals in the world. To cope with present and future climate change scenarios, it is important to map the shoreline posi-tion over years and assess the coastal erosion trends to select the best risk management solutions and guarantee a sustainable management of communities, structures, and ecosystems. However, this objective is particularly challeng-ing on gentle-sloping sandy coasts, where also small sea-level changes trigger significant morphological evolutions. This study presents a multidisciplinary study combining satellite images with Machine Learning and GIS-based spatial tools to analyze short-term shoreline evolution trends and detect erosion hot-spots on the Venice coast over the period 2015-2019. Firstly, advanced image preprocessing, which is not frequently adopted in coastal erosion studies, was performed on satellite images downloaded within the same tidal range. Secondly, different Machine Learning classifi-cation methods were tested to accurately define shoreline position by recognizing the land-sea interface in each image. Finally, the application of the Digital Shoreline Analysis System tool was performed to evaluate and visualize coastal changes over the years.Overall, the case study littoral reveals to be stable or mainly subjected to accretion. This is probably due to the high presence of coastal protection structures that stabilize the beaches, enhancing deposition processes. In detail, with re-spect to the total length of the considered shoreline (about 83 km), 5 % of the coast is eroding, 36 % is stable, 52 % is accreting and 7 % is not evaluable. Despite a significant coastal erosion risk was not recognized within this region, well-delimited erosion hot-spots were mapped in correspondence of Caorle, Jesolo and Cavallino-Treporti municipal-ities. These areas deserve higher attention for territorial planning and prioritization of adaptation measures, facing climate change scenarios and sea-level rise emergencies in the context of Integrated Coastal Zone Management.

Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice

Fogarin, S;Zanetti, M;Dal Barco, M K;Zennaro, F;Furlan, E;Torresan, S;Pham, H V;Critto, A
2023-01-01

Abstract

With increasing storminess and incessant sea-level rise, coastal erosion is becoming a primary issue along many litto-rals in the world. To cope with present and future climate change scenarios, it is important to map the shoreline posi-tion over years and assess the coastal erosion trends to select the best risk management solutions and guarantee a sustainable management of communities, structures, and ecosystems. However, this objective is particularly challeng-ing on gentle-sloping sandy coasts, where also small sea-level changes trigger significant morphological evolutions. This study presents a multidisciplinary study combining satellite images with Machine Learning and GIS-based spatial tools to analyze short-term shoreline evolution trends and detect erosion hot-spots on the Venice coast over the period 2015-2019. Firstly, advanced image preprocessing, which is not frequently adopted in coastal erosion studies, was performed on satellite images downloaded within the same tidal range. Secondly, different Machine Learning classifi-cation methods were tested to accurately define shoreline position by recognizing the land-sea interface in each image. Finally, the application of the Digital Shoreline Analysis System tool was performed to evaluate and visualize coastal changes over the years.Overall, the case study littoral reveals to be stable or mainly subjected to accretion. This is probably due to the high presence of coastal protection structures that stabilize the beaches, enhancing deposition processes. In detail, with re-spect to the total length of the considered shoreline (about 83 km), 5 % of the coast is eroding, 36 % is stable, 52 % is accreting and 7 % is not evaluable. Despite a significant coastal erosion risk was not recognized within this region, well-delimited erosion hot-spots were mapped in correspondence of Caorle, Jesolo and Cavallino-Treporti municipal-ities. These areas deserve higher attention for territorial planning and prioritization of adaptation measures, facing climate change scenarios and sea-level rise emergencies in the context of Integrated Coastal Zone Management.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5035594
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