Integrating passive geophysics and satellite interferometry for analysis of preparatory to triggering factors in a multi-hazard perspective

The development of tools for quantitative scenarios of ground instability effects is a challenge for risk mitigation, particularly in landslide risk management. In the RETURN project framework, the case study of the San Vito Romano earth-slide has been selected for PhD research as learning example for experiencing an integrated approach of passive geophysics and satellite interferometry. Such an approach is promising in managing urban plans and protecting historical heritage. It is also an effective tool for detecting and monitoring seasonal ground instability effects, while providing a useful instrument to calibrate numerical models aimed at predicting multi-hazard scenarios. The village of San Vito Romano (RM) is a historic location representative for the rural areas surrounding the city of Rome in Italy. The village is primarily built on an active earth-slide covering nearly 1 km², characterized by a roto-translational mechanism and slow kinematics. The landslide affects silico-clastic deposits from the Frosinone Formation (Upper Tortonian), consisting of alternating layers of clayey and arenaceous marls. This geological structure predisposes the area to slope instability. Contributing factors include cumulative precipitation, which influences soil moisture, and triggering events such as seismic activity and heavy rainfall, which activate the landslide. Evidence of this ongoing movement is found in the fractures present in buildings, which have been declared unsafe for use. More in particular, this research integrates ambient seismic noise techniques, with a specific focus on seismic interferometry, and Differential Interferometry SAR (DInSAR) techniques, particularly employing the Smal Baseline Subset approach. To conduct passive seismic studies, four short-period three-component velocimeters (VelBox, model SL06 2Hz sensor) have been installed on the landslide to continuously record ambient seismic noise. Continuous monitoring of ambient seismic noise allows the calculation of landslide mobility indices (LSMI), such as natural period variation (dT/T), peak polarization variation (dP/P), variation in the velocity of Rayleigh waves (dV/V) over time. From the variation of these parameters over time, we can continuously monitor changes in rigidity, amplification, and non-linear elastic properties of the soil to understand how the slope is prepared for possible instability. Furthermore, in relation to satellite techniques, the DInSAR technique was implemented, with a focus on the SBAS approach. DInSAR creates maps of mean displacement rate map and generates time series data on the displacements of specific points within the image. The processed data, which spans from 2022 to the present, reveals an increase in displacement rates , especially in certain sectors of the landslide. The project aims to develop a quantitative tool that correlates satellite displacements with proxies from passive seismic techniques (LSMI) to highlight the role of preparatory and triggering factors in landslide activity, specifically dealing with rainfalls and earthquakes. This information will be used to train a model for forward analysis of scenarios in a multi-hazard perspective.