Under the influence of global climate change, urban expansion and human activities, landslide events occur frequently every year around the world, posing a great threat to human life and property safety, especially in less developed regions. The global increase in damaging landslide events has attracted the attention of governments, practitioners and scientists to develop functional, reliable and (when possible) low-cost monitoring strategies. Numerous case studies have demonstrated how a well-planned monitoring system of landslides 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 satellite and aerial platforms. All these techniques are adopted for the same final scope: measure landslide 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 monitoring, depending on the type of phenomenon, the selected monitoring tool and the acceptable level of risk.
Remote sensing methods, such as radar Interferometry, photogrammetry, LiDAR or optical imaging represent valuable approaches in understanding landslides characteristics, especially when integrated with traditional ground-based monitoring techniques and when analysed with machine learning approaches.
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. Considering these key conceptual drivers, this session aims to present successful monitoring experiences worldwide based on both in situ and/or remotely sensed data.
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 monitoring 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. Specific relevance is given to the evaluation of the impact of landslides on cultural heritage.