NH3.8 | Landslide monitoring: recent technologies and new perspectives
EDI
Landslide monitoring: recent technologies and new perspectives
Convener: Federico Raspini | Co-conveners: Veronica Tofani, Qingkai MengECSECS, Peter Bobrowsky, Mateja Jemec Auflič

Under the influence of global climate change, urban expansion and human activities, landslides (and geo-hydrological hazards in general) occur frequently every year around the world, posing a great threat to human life and property safety. The global increase in damaging events has attracted the attention of governments, practitioners and scientists to develop functional, reliable and (when possible) low-cost monitoring and management strategies. Numerous case studies have demonstrated how a well-planned monitoring system of landslides (and ground deformation in general) is of fundamental importance for long and short-term risk reduction.
Today, the temporal evolution of a landslide is addressed in several ways, encompassing classical and more complex in situ measurements or remotely sensed data acquired from aerial platforms and satellites, with particular focus to new platforms (SAOCOM, Sentinel-1C, LuTan). All these techniques are adopted for the same final scope: measure motion over time, trying to forecast future evolution or, at least, reconstruct its recent past. Real time, near-real time and deferred time strategies can be profitably used for landslide analysis, depending on the type of phenomenon, the selected monitoring tool and the acceptable level of risk.
This session follows the general objectives of the International Consortium on Landslides, namely: (i) promote landslide research for the benefit of society, (ii) integrate geosciences and technology within the cultural and social contexts to evaluate landslide risk, and (iii) combine and coordinate international expertise.
The session is expected to present various topics of innovative applications of remote sensing techniques, as well as case studies in which multi-temporal and multi-platform data are exploited for risk management. The integration and synergic use of different techniques is welcomed, as well as newly developed tools or data analysis approaches, including big data management strategies and Artificial Intelligence-based methods.

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