ArticleScientific reports2022
Improvement of a coastal vulnerability index and its application along the Calabria Coastline, Italy.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A global assessment of coastal vulnerability and dominant contributors.Nature communications · 2026Article
- A coastal exposure index for Ireland: relative hazard exposure and the protective role of coastal habitats.Natural hazards (Dordrecht, Netherlands) · 2026Article
- Climate change and hyponatremia-related hospital admissions in people with focal epilepsy exposed to carbamazepine or its derivatives.Epilepsia · 2025Article
- Presentation and analysis of the Geotechnical Coastal Vulnerability Index and validation of its application to coastal erosion problems.Scientific reports · 2025Article
- Vulnerability assessment of English and Welsh coastal areas.Scientific reports · 2024Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present paper further develops a coastal vulnerability index formulation (CVI) previously proposed by the authors by integrating a new variable and redefining three variables to improve the suitability of the index for low-lying coasts. Eleven variables are divided into three typological groups: geological, hydro-physical process and vegetation. The geological variables are: geomorphology, shoreline erosion/accretion rates, coastal slope, emerged beach width, and dune. The hydro-physical process group includes: river discharge, sea-level change, mean significant wave height and mean tide range. The vegetation variables are: vegetation behind the back-beach and coverage of Posidonia oceanica. The index was applied to a stretch of the Ionian coast in the province of Crotone in the Calabria region (Southern Italy), and a vulnerability map was produced. A geography information system (GIS) platform was used to better process the data. For the case study area, the most influential variables are shoreline erosion/accretion rates, coastal slope, emerged beach width, dune, vegetation behind the back-beach, and coverage of Posidonia oceanica. The most vulnerable transects are those near urban areas characterized by the absence of dunes and vegetation. Statistical and sensitivity analyses were performed, and the proposed CVI was compared with the previous formulation proposed by the authors and with two other CVI methods present in the literature.
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