PSI - Issue 84

Antonio Di Pietro et al. / Procedia Structural Integrity 84 (2026) 57–64

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Fig. 3. Point-cloud processing: Pile number 5 cap detail.

4.4. Implications for Monitoring and Asset Management The Viadotto Fiacchignano dataset establishes a detailed geometric baseline suitable for periodic inspections, deformation analysis, and integration with structural health monitoring systems. Its density and internal consistency permit identification of minor geometric variations across time, including changes in pier inclination, deck deformation, settlement along the abutments, or modifications in slope geometry. Because the site includes both anthropic and natural slopes, the dataset also supports hydrological modelling, erosion-path identification, and verification of drainage conditions, all of which are relevant to the long-term stability of the viaduct. The case study confirms the suitability of the LiDAR-based workflow for infrastructures with limited accessibility, tall piers, complex morphologies, and vegetated environments, all of which are common in the Italian Apennine highway network. An overview of the viaduct and of the LiDAR-derived point cloud used in the analysis is shown in Fig. 4, summarising the spatial extent of the acquisition and the distribution of ground-control points employed for accuracy validation.

Fig. 4. Overview of the Fiacchignano viaduct from LiDAR data, showing the global point cloud, structural spans, and the location of the two ground-control points used for accuracy validation. 5. Conclusions This paper presented an integrated UAS–LiDAR workflow for the geometric documentation of bridge infrastructures, covering flight planning, airborne data acquisition, trajectory reconstruction, classification, and mesh generation. The methodology was applied to a concrete viaduct located in central Italy, featuring tall piers, under-deck visibility constraints, and heterogeneous terrain conditions. The results show that airborne LiDAR enables continuous reconstruction of structural and geotechnical components, including regions that are typically inaccessible to conventional or image-based inspection methods. The classified point cloud and the corresponding triangulated mesh provided detailed representations of the deck soffit, pier shafts, pier-deck interfaces, and adjacent slopes, with centimetric accuracy confirmed by independent RTK checkpoints. The geometric outputs derived from the survey are suitable for multiple engineering tasks, including as-built modelling, BIM/FEM integration, multi-temporal