NH3.18 | Artificial Intelligence for Landslide Risk Management Framework: From Detection to Risk Assessment
EDI
Artificial Intelligence for Landslide Risk Management Framework: From Detection to Risk Assessment
Convener: Sansar Raj Meena | Co-conveners: Xiaochuan Tang, Minu Treesa Abraham, Omid Ghorbanzadeh, Oriol Monserrat

This session aims to facilitate a collaborative and multidisciplinary dialogue that fosters the exchange of knowledge and expertise in landslide risk management. By integrating cutting-edge advancements in artificial intelligence (AI) with diverse perspectives from researchers, practitioners, and stakeholders, we seek to develop innovative solutions for landslide detection, monitoring, and risk assessment. The session will explore how AI-driven approaches can enhance traditional methodologies, offering new insights into early warning systems, hazard prediction, and mitigation strategies. Our goal is to create a visionary roadmap for AI-enabled landslide risk management, underpinned by scientific rigor and aimed at safeguarding communities worldwide from the impacts of landslides.

This session aims to facilitate a collaborative and multidisciplinary dialogue that fosters the exchange of knowledge and expertise in landslide risk management. By integrating cutting-edge advancements in artificial intelligence (AI) with diverse perspectives from researchers, practitioners, and stakeholders, we seek to develop innovative solutions for landslide detection, monitoring, and risk assessment. The session will explore how AI-driven approaches can enhance traditional methodologies, offering new insights into early warning systems, hazard prediction, and mitigation strategies. Our goal is to create a visionary roadmap for AI-enabled landslide risk management, underpinned by scientific rigor and aimed at safeguarding communities worldwide from the impacts of landslides.