authorship_metadata.json

{
    "Title": "Landslide Risk Assessment Dataset for Italy: Integrating Meteorological, Geological, and Climatic Variables for National-Scale Susceptibility Analysis",
    "Authors": "Lorenzo Tedesco, Francesco Finazzi (Department of Economic Sciences, University of Bergamo, Via dei Caniana 2, 24127 BG, Bergamo, Italy)",
    "Correspondence": "Dr. Lorenzo Tedesco (Email: Lorenzo.tedesco@unibg.it)",
    "Description": "This dataset was created to analyse and predict landslide susceptibility across Italy's slope units. It integrates meteorological, geological, and climatic data to provide a comprehensive overview of factors influencing landslide occurrence. Key components include landslide events from the ITALICA database, detailed slope unit classifications, terrain types, climate zones, and atmospheric data at high spatial resolution. This data serves to enhance risk assessment and land-use planning by identifying areas most susceptible to landslides.",
    "Source of Data": [
        "Landslide Events: ITALICA (Peruccacci et al., 2023), containing records from 1996 to 2021.",
        "Slope Units: Slope units dataset refined by (Alvioli et al., 2024), which delineates terrain based on natural drainage and topographic boundaries.",
        "Climate Zones: Based on Table A of D.P.R. 412/93, updated on October 31, 2009.",
        "Climate Data: VHR-REA_IT dataset from CMCC, based on ERA5 reanalysis and COSMO-CLM downscaling for high-resolution atmospheric and soil moisture variables (Raffa et al., 2021).",
        "Terrain Classification: 18 classes as described by (Loche et al., 2022), incorporating geological and geomorphological features."
    ],
    "Geographic Coverage": "Italy, across all regional and provincial boundaries",
    "Time Period": "2000-2021",
    "Geolocation": "Latitude, Longitude, Municipality, Province, Region",
    "Topographic Attributes": "Slope, Elevation, Curvature, Distance to Stream",
    "Soil Properties": "Bulk Density, Soil Moisture at Multiple Depths, Sand/Silt/Clay Ratios",
    "Format": "CSV, with each row representing a unique landslide or non-landslide observation, containing topographic, climatic, and geographic details.",
    "Data Usage and Applications": "This dataset is suited for landslide susceptibility analysis, climate impact studies, and regional planning. Its integration of detailed meteorological and topographic data allows for machine learning applications in risk assessment, policy development, and the creation of early warning systems."
}