Vulnerability assessment of road networks to landslide hazards in a dry-mountainous region

Landslides are natural hazards that can cause catastrophic life losses and damage to infrastructures and communities. In Iran, landslide exposure has been predominantly increasing in the Zagros Mountains, notably along the lifelines, such as road networks. Therefore, this study aimed to investigate the landslide vulnerability of a 6682 km road network in the Chaharmahal and Bakhtiari Province, Iran, using a two-step methodology comprised of: (1) landslide susceptibility mapping using four machine learning methods—boosted regression trees (BRT), multiple discriminant analysis (MDA), multivariate adaptive regression splines (MARS), and random forest (RF); and (2) mapping road exposure to landslides using the analytic hierarchy process (AHP) that computed the weight for four buffer zones (0–50, 50–150, 150–300, and > 300 m) from the road network. The combined results of steps 1 and 2 produced a map of the road network vulnerability to landslides that demonstrated that 9.7 km (13.6%) of the road network was located in the very-high vulnerability class. Specifically, the roads of the Ardal and Kohrang counties have been found to be the most vulnerable to landslide risk. The finding of this study could be useful for decision-makers and civil engineering to better manage road networks in terms of landslide risk and community resilience in the aftermath of major landslides.