Study on landslide hazard risk in Wenzhou based on slope units and machine learning approaches.

ABSTRACT: Landslides are a prevalent and devastating form of geological disaster. These events occur when gravity causes rock and soil masses to slide along specific surfaces or zones, often triggered by intense rainfall, seismic activity, or human engineering activities. Assessing landslide hazard risk is crucial for effective disaster management, yet traditional approaches often rely on administrative or grid units, which lack the granularity needed for site-specific hazard management. This results in uniformly high-risk classifications for hilly areas, complicating practical engagement and increasing management costs. The study further combines historical landslide data and applies machine learning models such as Random Forest, XGBoost, and LightGBM to analyze landslide susceptibility in Wenzhou

SUBMITTER: Kang D 

PROVIDER: S-EPMC11876616 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature