Abstract

Landslides are a significant natural hazard in regions with complex topographic, geological, and climatic conditions, where they can constrain sustainable territorial development and threaten infrastructure, land use, and environmental safety. This study aims to assess and map landslide susceptibility in Southern Primorye in order to support hazard-informed territorial planning and risk reduction. The analysis integrates vegetation, precipitation, geological, and topographic predictors with documented landslide occurrence data. A presence-only landslide susceptibility modeling approach was applied using the OneClassSVM algorithm with a radial basis function kernel. The results show that the highest susceptibility is associated with lower slope segments and coastal landforms composed of loose unconsolidated deposits and partly covered by sparse woodland. Surface runoff, subsurface flow, lithological conditions, and precipitation patterns were identified as the principal factors contributing to slope instability, while field observations confirmed that anthropogenic slope cutting related to road infrastructure may act as an additional local trigger. The model demonstrated moderate but acceptable predictive performance and allowed the delineation of areas with elevated landslide susceptibility. The resulting susceptibility map provides a regional-scale basis for more sustainable land-use planning, infrastructure placement, and landslide risk mitigation in Southern Primorye and in other regions with comparable environmental conditions.

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