PSI - Issue 84

Alice Vitaletti et al. / Procedia Structural Integrity 84 (2026) 191–198

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acquisitions, processed in both ascending and descending orbital geometries and updated with a revisit time of six days. These products include mean annual deformation velocities (mm/year) and displacement time series for each measurement point along the line of sight (LOS). In this study, four datasets covering the period from January 2018 to December 2022 were used. To investigate the distribution of measurement points (i.e., PS) with respect to unstable areas interacting with critical infrastructures, the analysis focused on large landslides (area > 10,000 m²) that totally or partially interact with bridges along the highway section. For most of the bridge-landslide interaction cases, a density of radar targets lower than 0.001 PS/m 2 was observed within the unstable areas, together with a highly uneven spatial distribution. PS were often scattered, clustered in limited sectors of the landslide or located predominantly on the infrastructure. This behaviour is mainly related to the dense vegetation cover typical of such slopes, which induces temporal variation of the radar signal due to wind effects and seasonal changes, thus limiting the capability of InSAR to fully capture landslide kinematics. In contrast, the selected case study exhibited a comparatively higher radar target density (about 0.010 PS/m2) and a more homogeneous spatial distribution across the unstable area. The average LOS velocity remained generally within ±1.5 mm/year along the bridge and parts of the landslide-affected slope, while local peak values exceeding +3 mm/year were detected in specific regions (Fig. 1). Although these magnitudes may appear moderate, they are consistent with the behaviour of very slow-moving landslides, where progressive displacements may develop over time. As documented in recent literature (e.g. Gabrieli et al. 2024; Salciarini et al. 2024), such slow large-volume phenomena can pose significant threat to infrastructures despite their low kinematic rates. As a result, the selected bridge-landslide interaction case was considered particularly suitable for applying the combined InSAR and FEM numerical modelling approach, as it offered both sufficient satellite data coverage and a realistic interaction between a slow-moving landslide and a highway bridge.

Fig. 1. Orthophoto of the case study showing the landslide (red), the bridge (black), and the average annual LOS velocity of PS.

3. Methodology The adopted methodology is based on the combination of satellite-based monitoring and numerical modelling to investigate the interaction between a slow-moving landslide and bridge foundations. FEM simulations were carried out using Plaxis 3D to assess the structural response under hydro-mechanical loading conditions. The numerical model enabled the full-scale simulation of landslide evolution and provided insights on the actual displacement direction, which supported the definition of the reference system adopted for satellite data interpretation. In parallel, InSAR data were post-processed to estimate the actual transverse and vertical components of the displacement field within a local reference system fixed to the landslide phenomenon, providing further insight into slope kinematics and supporting the reliability of the numerical model. The combination of InSAR observations and FEM modelling allowed the interpretation of satellite-derived deformation patterns and supported the identification of potentially unstable areas, offering an operative tool for the assessment of landslide-induced effects on highway infrastructures.