Paolo Farina

Slow to extremely slow landslides in urban areas may cause severe damage to buildings and infrastructure that can lead to the evacuation of local populations in case of slope accelerations. Monitoring the spatial and temporal evolution of this type of natural hazard represents a major concern for the public authorities in charge of risk management. Pariana, a village with 400 residents located in the Apuan Alps (Massa, Tuscany, Italy), is an example of urban settlement where the population has long been forced to live with considerable slope instability. In the last 30 years, due to the slope movements associated with a slow-moving landslide that has affected a significant portion of the built-up area, several buildings have been damaged, including a school and the provincial road crossing the unstable area, leading to the need for an installation of a slope monitoring system with early warning capabilities, in parallel with the implementation of mitigation works. In this paper, we show how satellite multi-temporal interferometric synthetic aperture radar (MT-InSAR) data can be effectively used when coupled with a wireless sensor network made of several bar extensometers and a borehole inclinometer. In fact, thanks to their wide area coverage and opportunistic nature, satellite InSAR data allow one to clearly identify the spatial distribution of surface movements and their long-term temporal evolution. On the other hand, geotechnical sensors installed on specific elements at risk (e.g., private buildings, retaining walls, etc.), and collected through Wi-Fi dataloggers, provide near real-time data that can be used to identify sudden accelerations in slope movements, subsequently triggering alarms. The integration of those two-monitoring systems has been tested and assessed in Pariana. Results show how a hybrid slope monitoring program based on the two different technologies can be used to effectively monitor slow-moving landslides and to identify sudden accelerations and activate a response plan.

This paper presents results from applying semi-automatic point cloud segmentation methods in the underground tunnels within the Military Shrine’s conservative restoration project in Cima Grappa (Italy). The studied area, which has a predominant underground development distributed in a network of tunnels, is characterized by diffuse rock collapsing. In such a context, carrying out surveys and other technical operations are dangerous activities. Considering safety restrictions and unreachable impervious tunnels, having approached the study area with the scan-line survey technique resulted in only partial rock mass characterization. Hence, the geo-mechanical dataset was integrated, applying a semi-automatic segmentation method to the point clouds acquired through terrestrial laser scanning (TLS). The combined approach allowed for remote performance of detailed rock mass characterization, even remotely, in a short time and with a limited operators presence on site. Moreover, it permitted extending assessing tunnels’ stability and state of conservation to the inaccessible areas.

Slope failures are life-threatening geohazards well-known in the mining industry, where a single accident can endanger workers and cause million dollars’ -worth of activity downtime. Therefore, a detailed ground deformation map of an open-pit mine represents a vital planning tool and high-frequency monitoring is pivotal, since false or anticipated alarms may represent a higher impact than missed alarms. This article presents an application of interferometric satellite data from Sentinel-1. The scope of the study is showing the potential of the new generation of satellites for the detection of the boundary, typology, and kinematics of the on-going slope instabilities in open-pit mines. Most notably, this experience discloses how the short revisiting time (six days) permits the implementation of time of failure forecasting methods, which so far were a prerogative of ground-based monitoring systems. Only recently, a few experiences have shown the possibility of (a posteriori) predicting slope failures using displacement time series measured from satellite; the case study here described represents one of such first examples. Moreover, 11 other areas of instability have been detected and classified in terms of subsidence (sediment compaction) or slope failures, based on considerations concerning the acquisition geometry used to detect the movements. The movement vectors along the ascending and descending lines of sight have been combined to compute horizontal and vertical vectors, which have been employed to infer the geometry of the sliding surface of some selected slope instabilities. Despite the advancements of the technique, clear limitations still exist and are discussed in this article.

Ground-based Synthetic Aperture Radar (GB-SAR) interferometry is used to monitor the Tessina landslide. This is a complex mass movement in the Italian Eastern Alps. Radar data, acquired during a 10-day campaign, are interferometrically processed. Image couples taken at the same position but at different times are used to estimate terrain slope deformations on a short temporal scale of a few hours. In addition, SAR images acquired with a baseline are processed to extract information on the current topography of the landslide area. Comparison with the terrain morphology of the scene at earlier times allows to evaluate the landslide activity on a long time scale spanning a few years.