PSI - Issue 84

Nicola Perilli et al. / Procedia Structural Integrity 84 (2026) 813–820

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characterize landslside and landslside bridge interaction

Although geomorphological, lithological, and land use/cover data do not directly inform CdA assessment under LLG 2020, they are part of the supplementary data used to support instability and susceptibility modeling. They also help refine field observations, enhancing the quality of essential data and, consequently, the reliability of primary and secondary parameter evaluations. 3.3 Geospatial Database Integration and Inspection Data Management This third component builds on the outputs of the first two components—thematic layers, landslide inventories, susceptibility models, and field data— and enables the integration, management, and structuring of all information within the WebGIS platform. The main activities include: . 1- Systematic data upload, real-time visualization, and access, improving Level 0 and Level 1 inspections and enabling reliable Level 2 CdA assessments. This allows monitoring of active or incipient landslides and landslide–bridge interactions. 2- Continuous updating of the landslide inventory, including new or incipient events, keeping susceptibility models current and actionable, and supporting iterative model refinement as periodic inspections are carried out. 3- Data collection using a validated closed glossary, supplemented by closed and an open vocabulary to allow progressive enrichment, ensuring consistency, standardization, interoperability, and seamless data exchange between inspectors and bridge owners. Chatbot-assisted tools facilitate the review and integration of field survey reports and allow updating of information, which is hierarchically structured in the WebGIS and easily accessible for consultation and analysis. 4- Centralizing these datasets to enhance inspector performance during periodic inspections and support bridge owners in prioritizing interventions based on up-to-date CdA evaluations. 4. Discussion Landslide risk assessment remains a major challenge in infrastructure management. A2 Traditional approaches are often fragmented, preventing integrated analysis of remote sensing and field survey data (Crosta et al., 2013; Guzzetti et al., 2020), which limits the quantity, quality and therefore the reliability of the results. A3 Regional-scale susceptibility analysis typically lack a structured approach that incorporates local scale information, underscoring the need for multi-scale approaches (Saito, 2000; Pradhan & Lee, 2010). These gaps make it difficult for inspectors and bridge owners to fully comply with the requirements of the LLG 2020, including the accurate assessment of the landslide CdA and risk-informed prioritization of periodic inspections. To address these challenges, this work proposes operational procedures and tools that use nested spatial units (Tab. 3). By translating conceptual definitions into operational procedures for CdA assessment (Tab. 6), the framework aims to integrate supplementary regional scale data with essential local-scale surveys through periodic data collection and updates of susceptibility models. This enables improved mapping of unstable slopes, monitoring of incipient or active landslides, and characterization of landslide–bridge interactions (Tab. 6). Table 6. WebGIS-based workflow: activities, procedures, and benefits for multi-scale landslide CdA assessment and inspection prioritization Activity Description Outcome / Benefit 1. Centralize datasets Integrate thematic layers, inventories, field data, and models across regional to local scales, reducing fragmentation and enabling coherent multi-scale analysis. Enhances inspector performance; supports bridge owners in fulfilling LLG 2020 commitments and prioritizing inspections based on risk.

Enable real-time data upload and visualization, with WebGIS linking back-office and field activities for consistent use of multi-source data. Incorporate new/incipient events and landslide bridge interaction, while iteratively updating susceptibility models, enabling dynamic refinements of knowledge and overcoming static approaches. Apply a validated closed glossary with both closed and open vocabularies for data enrichment and translates conceptual definitions into interoperable framework. Facilitates review, integration of field reports, structures data hierarchically, making data easily accessible for consultation and analysis.

Strengthens evidence-based inspections; improve reliability of CdA assessments and monitors active/incipient landslides and landslide–bridge interactions. Keeps susceptibility models actionable; supports adaptive, data-driven inspection planning and integrates multi-scale data for ongoing refinement. Ensures consistency, standardization, and seamless data exchange, supporting operational implementation of LLG 2020. Supports inspectors and bridge owners in fulfilling commitments; improves data management and reinforces evidence-based decision-making.

2. Systematic data upload & access

3. Continuous inventory updates

4. Standardized data management Additional support: Chatbot-assisted tools