Session Description:

In recent years, an increasing number of studies have demonstrated the power of machine learning and data-driven approaches in solving challenging landslide problems, such as landslide identification, prediction, and risk assessment. This session aims to discuss the latest developments and challenges of machine learning in landslide-related studies, including, but not limited to, the following topics:

• Landslide identification based on remote sensing
• Machine learning for landslide susceptibility analysis and prediction
• Data-driven and physics-informed slope modeling
• Intelligent slope monitoring and early warning
• Slope reliability analysis and landslide risk assessment
• Applications of LLMs in landslide hazard mitigation