PSI - Issue 84

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

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slope stability factor. The resulting slope angle map reveals a very high heterogeneous terrain, with extensive areas exhibiting slopes greater than 30° in the mountainous hinterlands, in contrast to gentler gradients of less than 10° in the alluvial plains and valleys floors. This variability in slope is one of the primary predisposing factors in landslide susceptibility. As highlighted in the literature, slope angle is the most frequently used predictive factor for Landslide Susceptibility Mapping (LSM) (Segoni et al. 2024). The slope analysis shows that bridges in the study area are distributed across a wide range of slope conditions, with many located in or adjacent to zones of high geomorphological susceptibility. This spatial configuration underscores the necessity for site-specific, bridge-by bridge risk assessments. In fact, the presence of a slope angle greater than 30° in proximity to a bridge does not inherently imply a risk; rather, the potential for landslides must be contextualized in relation to the bridge’s location. While bridges situated in flat areas, low slope areas generally associated with minimal landslide risk, those located in the mountainous valleys are significantly more exposed. River valleys, in particular, emerge as critical geomorphic features associated with high landslide susceptibility to infrastructure. The GIS-based slope analysis (Fig. 1) clearly demonstrates that bridge safety in Caserta is strongly influenced by terrain steepness, reinforcing the importance of integrating topographic parameters into infrastructure risk assessment. 3.2. Parameterization of landslide susceptibility The core of the study is a proposal for evaluation of the three parameters defined by the Italian Guidelines: Landslide Activity ( P a ), Landslide Velocity ( P v ), and Landslide Magnitude ( P m ). The following sections provide a detailed description of the datasets and methodologies used to derive these parameters, as well as the procedures adopted to visualize their spatial distribution across the study area. 3.3. Spatial and categorical analysis of landslide activity (P a ) The analysis of landslide activity ( P a ) was conducted using spatial data from the Italian National Landslide Inventory (IFFI), which consists of a polygon vector dataset representing documented landslide occurrences and their respective state of activity. The official inventory served as a primary data source for identifying potential landslide hazards affecting bridge infrastructure in the Caserta province.

(a)

(b)

Fig. 2. (a) Landslide activity ( P a ) assessment map; (b) Landslide activity ( P a ) assessment graph

The analysis was based on the preliminary introduction of two complementary criteria. The first criterion concerns the geomorphological context, defined through a simplified slope-based classification distinguishing between