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This study presents an integrated approach, coupling rockfall risk assessment with a vehicle-based surveying for the large-scale management of slope assets along transportation corridors. Rockfall risk was assessed qualitatively using relative rating scales. To reduce the subjectivity inherent in expert judgment, susceptibility was estimated through probabilistic methods, while vulnerability was informed by conventional runout simulations. Despite the associated uncertainties, the occurrence of a January 2024 rockfall within an area classified as high risk provides independent qualitative support for the consistency of the first-level screening results. Terrestrial Mobile LiDAR (TML) survey conducted from a car was designed to maximise effectiveness and efficiency in capturing rockfall-prone slopes and establishing a baseline for long-term monitoring. Its actual effectiveness, efficiency, potential and limitations were evaluated through a survey conducted in April 2023. Approximately 3.5 km of the A22 motorway, representing more than one-quarter of the analysed section, were found to be potentially exposed to rockfall risk, originating from 27 of the 55 identified potential detachment zones. The TML survey successfully detected over 70% of these zones, achieving a point density potentially sufficient to identify volumes greater than approximately 10 dm 3 . The scanning was constrained by morphological conditions, such as vertical slopes adjacent to the motorway, structural obstacles, such as tunnel portals, and the instrument’s maximum range of 475 m. Despite these limitations, the quality and accuracy of the acquired data indicate that the TML can effectively support the motorway operators in large-scale rockfall risk management.
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Lelli et al. (2026) studied this question.
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