Conveners: Ascanio Rosi (Università di Padova), Filippo Catani (Università di Padova), Mario Floris (Università di Padova), Sansar Raj Meena (Università di Padova)
mario.floris@unipd.it
mario.floris@unipd.it
In Italy, landslides are considered to be one of the extreme natural threats and have large implications on infrastructure, economy, and society as a whole. Availability of new measurement methods, data mining, and predictive analysis create a new avenue of researching and improving the control of such phenomena. The goal of this session is to discuss recent developments in technologies and methodologies for landslide detection and forecasting within the Italian geological context, with a focus on the following aspects.
- Recent advancement in the use of machine learning technologies for landslide prediction.
- In situ and remote monitoring of landslide phenomena.
- Risk assessment with the use of computational models.
- Early warning system for risk management strategies.
- Case studies and lessons learned from recent events in Italy.
Difficulties in engaging the community and effective risk communication. We invite contributions including, but not limited to, demonstrations of emerging technologies and software tools, analyses of significant case studies, critical reviews of the state-of-the-art, proposals for interdisciplinary approaches, and discussions on risk management policies and strategies.