Conference Agenda

Since the launch of the ERS mission early in the 1990’s, Synthetic Aperture Radars (SAR) mounted on satellites provide information on spatial and temporal surface changes associated with natural and anthropic activities, day and night, and independently of weather conditions. Despite the progress achieved in terms of data quality/resolution and processing methods, this technology has been constrained in a limited number of applications until the venue of the ESA Copernicus Sentinel-1 mission. The latter opened a new era in the radar remote sensing scenario, mainly because of systematic, global, open data availability. In addition, new missions from several space agencies, as well as commercial operators worldwide, constantly increase the potential of SAR not only for back analyses and surveys at local and regional scales, but also in monitoring applications and early warning scenarios.

In this contribution, we present key results obtained with satellite SAR data in the framework of alpine mass movement detection and monitoring. The focus is not only on scientific achievements, but also on their practical applications. The study areas range from the Swiss Alps to the Himalayas, and the examples of application include: (i) identification of snow wetness conditions and mapping of snow avalanches based on change detection methods exploiting SAR backscatter; (ii) decadal analyses based on radar interferometry aimed at the interpretation of spatial and temporal slope displacements patterns; (iii) monitoring accelerated slope deformation and characterization of catastrophic slope failure events; (iv) combined use of SAR and optical/multispectral sensors to enhance the interpretation of complex alpine phenomena. Moreover, we discuss the current challenges, and the perspectives offered by new sensors with very high spatial resolution (<1m) and frequent revisit time (sub-daily).

Flash floods frequently occurred in Switzerland during summer 2024. It damaged the infrastructures, human habitats and landscapes. This research observed that the flash floods often followed by the high precipitation of several days before the day of the flash flood occurred in Switzerland and mountainous regions such as Hindu Kush Himalaya. The objective of this research is an attempt to detect the potential flash floods based on the satellite based daily precipitation signals in the human habitat zone of the mountainous regions and adjacent areas in Switzerland. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) is a unified satellite precipitation product produced by National Aeronautics and Space Administration (NASA) to estimate surface precipitation over most of the globe. The daily observed precipitation data is downloaded and calculate the daily mean and daily maximum precipitation of each district over Switzerland. Number of days that received above the threshold daily mean and maximum precipitations were categorized in the attribute tables of each district, as the preliminary flash flood risk maps. Furthermore, the time series observed daily precipitation signals or graphs were plotted for selected district which have received high mean precipitation and maximum precipitation. Statistically significant clusters and outliers of districts were identified using the space and time data mining of daily satellite observed precipitation data cube. The time series signals, and preliminary risk maps, clusters and outliers of districts jointly indicated that the flash floods do not occur suddenly. It requires certain days to set the stage for happening flood event soon. Therefore, it could provide enough time to inform the forewarning to the people and infrastructure operators to endure that the flash floods occurred with the minimal damage, to save lives and infrastructures. Python programming language and ArcGIS Pro software are applied in this research. This research attempts to contribute saving lives and infrastructures from the flash floods using remotely sensed estimated daily precipitation data from the IMERG satellites.

Natural hazards in mountainous regions present significant risks to communities, infrastructure, and ecosystems, demanding advanced systems for forecasting, preparedness, warning, and response. This oral presentation presents *GUARDAVAL*, an innovative hazard monitoring platform implemented in the Canton of Valais, Switzerland. Developed in 2003, and continually upgraded, GUARDAVAL integrates real-time data from over 200 monitoring sites, including extensometers, GNSS stations, hydrometric sensors, and satellite-based InSAR measurements, to track and forecast geophysical hazards such as landslides, rockfalls, and floods.

The system employs a modular web-GIS portal that consolidates data from both local and national networks (e.g., SwissMetNet, SLF) into a centralized, real-time monitoring platform. Additionally, GUARDAVAL supports multi-hazard forecasting by incorporating meteorological and hydrological models, such as MINERVE, enabling accurate flood predictions. Through automated alert systems and comprehensive risk visualization tools, the platform enhances decision-making for public authorities and private agencies responsible for hazard mitigation.

This presentation will demonstrate GUARDAVAL's technological innovations, operational framework, and its role in improving disaster preparedness and response in challenging alpine environments. The discussion will also explore lessons learned from nearly two decades of deployment, highlighting the potential of such systems in improving resilience against climate-induced hazards globally.