Coastal zones are dynamic and vulnerable geomorphological systems where erosion and sedimentation interact with climatic variability and anthropogenic pressures. Monitoring shoreline dynamics is crucial for managing coastal risks, preserving ecosystems, and protecting communities, as nearly half of the global population lives near the coast. Although long-term satellite archives are available, few studies have effectively integrated multi-sensor imagery to investigate the combined role of human and natural drivers on decadal shoreline evolution. This study addresses this gap by reconstructing 40 years (1984–2024) of shoreline changes along a 20 km stretch between Torvaianica and the Tor Caldara Natural Reserve (Lazio, Italy), an area historically affected by intense anthropogenic impacts. Shorelines were extracted from Landsat 5, Landsat 8, and Sentinel 2 imagery using the Normalized Difference Water Index (NDWI), which enhances the land–water boundary and allows for consistent shoreline detection across sensors. Extracted shorelines were analyzed using the Digital Shoreline Analysis System (DSAS) to calculate End Point Rate (EPR), Net Shoreline Movement (NSM), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR). Results show a maximum LRR of −1.07 m\yr and a mean erosion rate of 0.44–0.55 m\yr, with 86.9 % of the coastline undergoing erosion. Storm events between 2012 and 2024 were identified using hydrometric levels and wind speed above the 95th percentile, revealing links between storm clusters and short-term shoreline change. Accuracy assessment highlights Sentinel 2 as the most reliable dataset. This research demonstrates the value of combining NDWI-based shoreline extraction with long-term datasets to support sustainable coastal management.
Tracking coastal changes in the central-eastern margin of Tyrrhenian Sea through integrated NDWI-derived shorelines from multi-sensor satellite time series / Iacobucci, G.; Piacentini, D.; Troiani, F.. - In: REMOTE SENSING APPLICATIONS. - ISSN 2352-9385. - 39:(2025). [10.1016/j.rsase.2025.101636]
Tracking coastal changes in the central-eastern margin of Tyrrhenian Sea through integrated NDWI-derived shorelines from multi-sensor satellite time series
Iacobucci, G.
;Piacentini, D.;Troiani, F.
2025
Abstract
Coastal zones are dynamic and vulnerable geomorphological systems where erosion and sedimentation interact with climatic variability and anthropogenic pressures. Monitoring shoreline dynamics is crucial for managing coastal risks, preserving ecosystems, and protecting communities, as nearly half of the global population lives near the coast. Although long-term satellite archives are available, few studies have effectively integrated multi-sensor imagery to investigate the combined role of human and natural drivers on decadal shoreline evolution. This study addresses this gap by reconstructing 40 years (1984–2024) of shoreline changes along a 20 km stretch between Torvaianica and the Tor Caldara Natural Reserve (Lazio, Italy), an area historically affected by intense anthropogenic impacts. Shorelines were extracted from Landsat 5, Landsat 8, and Sentinel 2 imagery using the Normalized Difference Water Index (NDWI), which enhances the land–water boundary and allows for consistent shoreline detection across sensors. Extracted shorelines were analyzed using the Digital Shoreline Analysis System (DSAS) to calculate End Point Rate (EPR), Net Shoreline Movement (NSM), Linear Regression Rate (LRR), and Weighted Linear Regression (WLR). Results show a maximum LRR of −1.07 m\yr and a mean erosion rate of 0.44–0.55 m\yr, with 86.9 % of the coastline undergoing erosion. Storm events between 2012 and 2024 were identified using hydrometric levels and wind speed above the 95th percentile, revealing links between storm clusters and short-term shoreline change. Accuracy assessment highlights Sentinel 2 as the most reliable dataset. This research demonstrates the value of combining NDWI-based shoreline extraction with long-term datasets to support sustainable coastal management.| File | Dimensione | Formato | |
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