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• W4382982870 abstract "This paper presents a GIS-based approach to create a multilevel data system for detailed knowledge of landslide occurrences in small territorial units such as municipalities. The main aim is to collect all the available data (geological, geomorphological, and climatic data, as well as landslide inventory maps and catalogues) in a structured data management system and perform further analyses to identify the typical landslide scenarios of the study area that can be useful in landslide risk management. We demonstrated the use of the methodology analyzing landslide risk in the municipality of Catanzaro (southern Italy), having a surface of 111.7 km2, 20.5% of which was affected by landslides. The spatial and temporal distribution of landslides highlighted that in several cases, they are reactivations of pre-existing phenomena. In fact, in the municipality, approximately 17% of the buildings fall within landslides-affected areas, 7.9% of which are in areas where landslides are classified as active. Furthermore, active landslides involve 8.1% and 9.5% of the roads and railways, respectively. In the 1934–2020 study period, 53% of activations occurred between October and December and were triggered by daily rain which in the highest percentage of cases (49%) showed values between 50 and 100 mm. The proposed GIS platform can be easily updated in order to preserve the landslide history of the area and can be enriched with further thematic layers (i.e., layers concerning flood events, which often occur simultaneously with major landslide events). The case study demonstrates how the platform can support landslide risk management in terms of monitoring, planning remedial works, and the realization/updating of civil protection plans." @default.
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• W4382982870 date "2023-07-01" @default.
• W4382982870 modified "2023-09-30" @default.
• W4382982870 title "Multi-Level Data Analyses for Characterizing Rainfall-Induced Landslide Scenarios: The Example of Catanzaro Municipality (South Italy)" @default.
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• W4382982870 doi "https://doi.org/10.3390/w15132437" @default.
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