Towards Sustainable Heritage Conservation: A Hybrid Landslide Susceptibility Mapping Framework in Japan’s UNESCO Mountain Villages

Abstract

Sustainable management of cultural heritage in mountainous regions requires effective strategies to mitigate natural hazards such as landslides. Landslide susceptibility mapping (LSM) provides a critical tool to support these conservation efforts. This study presents a hybrid framework that integrates probabilistic slope stability modeling with ensemble learning for LSM in the UNESCO World Heritage sites of Shirakawa-gō and Gokayama, Japan. The framework uses probabilities of failure from Bishop’s simplified method combined with Monte Carlo simulations to guide non-landslide sample selection. An enhanced tri-parametric optimization was applied to refine the slope unit segmentation process. SHAP analysis revealed that the hybrid framework emphasizes physically meaningful features such as rainfall. The proposed method results in AUC gains of 0.072 for XGBoost, 0.066 CatBoost for, and 0.063 for LightGBM compared to their buffer-based counterparts. Future landslide susceptibility was mapped based on the 2035 precipitation projections from ARIMA time-series modeling. By enhancing accuracy, interpretability, and geotechnical consistency, the proposed approach delivers a robust tool for sustainable risk management. The study further evaluates the exposure of Gasshō-style houses and other historic buildings to varying levels of landslide susceptibility, offering actionable insights for local planning and heritage conservation.