PSI - Issue 84

Mirza Adeel Zeb et al. / Procedia Structural Integrity 84 (2026) 248–255

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past decades, thousands of lives have been lost, and damages amounting to millions of euros have been reported. According to the National Landslide Inventory (IFFI), more than 635,000 landslides have been documented, affecting over 8.3% of the national territory by Trigila et al. (2025). The province of Caserta, located in southern Italy, is one of the most landslide-prone areas in the country, with approximately 60% of its territory affected. The local geology is characterized by steep slopes, unconsolidated materials, and severe weather conditions, which pose a continuous and significant threat to the built environment. In recent years, some fatal landslide events have occurred in this region such as the one in San Felice a Cancello in August 2024, highlighting the persistent geomorphological instability of the area. Bridges represent a critical component of transportation infrastructure. Most of the bridges in Italy were constructed in the mid-20th century and are increasingly vulnerable to structural degradation and natural hazards, including landslides. Recent studies have documented multiple cases of rainfall-triggered landslides affecting road and bridge networks across Italy, highlighting how both slow-moving slope instabilities and rapid mass movements have caused significant structural damage, particularly during extreme precipitation events in the last decade (Salciarini et al. 2024; Scala et al. 2025; Gabrieli et al. 2024). These findings clearly underline the limitations of reactive maintenance strategies and reinforce the need for a transition toward a proactive, multi-hazard risk management framework. In response, in 2022 the Italian Ministry of Infrastructure MIMS (2022) released specific mandatory national guidelines. These guidelines introduce a standard national system for risk classification, where inspections and resource allocation are based on a structured, multi-level assessment process. This study represents a first application of the landslide risk component (Level 2) outlined in the Italian guidelines. In this context, regulatory requirements, objective and spatially explicit tools are needed to identify and characterize landslide-prone areas affecting bridge infrastructure at a territorial scale. Landslide Susceptibility Mapping (LSM) is a widely adopted geoscientific tool used to identify areas where landslides are likely to occur. Methods range from qualitative, expert-based approaches to quantitative models developed from empirical data. The latter category includes statistical techniques, such as logistic regression, as well as machine learning algorithms like Random Forest, which are favored for their objectivity and seamless integration with Geographic Information Systems (GIS) (Cao and Wu 2021). A review of the Italian LSM studies reveals that the most used predictive factors are slope angle, lithology, land use, and slope aspect. It is important to distinguish between the concepts of susceptibility, hazard, and risk in landslide studies. Susceptibility refers to the spatial probability of a landslide occurring in a specific area. Hazard considers the temporal probability, or frequency of occurrence, often estimated through triggers such as rainfall thresholds. Risk, on the other hand, includes the potential consequences of an event, such as the loss of life or economic damage (Azhideh et al. 2024). The 2022 Italian Guidelines adopt these definitions and introduce a semi-quantitative classification called “Attention Class”, which integrates susceptibility/hazard, vulnerability, and exposure in a broad scale screening process. Recent advances in geospatial technologies have significantly enhanced geohazard assessment capabilities. GIS serves as a fundamental platform for integrating, managing, and analyzing various spatial datasets. Interferometric Synthetic Aperture Radar (InSAR) has evolved from a research tool into an operational system for ground deformation monitoring, capable of detecting millimetric movements over a wide area (Crosetto et al. 2016). The launch of the Sentinel-1 satellite constellation under the Copernicus program, which its free access and short revisit times, has further democratized radar data, enabling widespread, operational-scale monitoring (Hussain et al. 2022). This makes InSAR an ideal technology to supply objective, large scale information on landslide activity and velocity, as required by the national guidelines. This paper focuses on the assessment of landslide susceptibility affecting existing bridges by integrating landslide susceptibility mapping approaches with satellite interferometric data, in accordance with the Italian national guidelines. 2. Methodology In this work, the national guidelines for bridge risk classification and management MIMS (2022) were followed to map landslide hazards affecting bridge infrastructures. The methodological approach includes three typological characteristics of the landslides, which are representative of the key parameters to assess landslide hazard: Pa (landslide activity), Pv (landslide velocity), and Pm (landslide magnitude). These parameters were derived by integrating multiple data sources and analytical workflows.