Landslide susceptibility on the Qinghai-Tibet Plateau: Key driving factors identified through machine learning

Key Points

• Landslide susceptibility is significantly influenced by identified driving factors, and predictive modeling enables better risk assessment.
• The analysis reveals that factors such as vegetation cover and rainfall patterns impact susceptibility, with an emphasis on machine learning's role.
• Approach through machine learning-based predictive modeling on the Qinghai-Tibet Plateau reveals complex interactions between environmental variables.
• These findings may enable targeted strategies for managing landslide risks in vulnerable areas, calling for further investigation into regional impacts.