In this paper all the phases for the realization of the early warning system for the rockslide of Torgiovannetto in Central Italy are described. The landslide consists in a 182,000m3 rock wedge threatening two roads which are important for local transportation. The present work encompasses all the components of an early warning system, including the geological knowledge, the risk scenarios, the kinematic characterization of the landslide, the choice and installation of the monitoring system, the setting of appropriate alarm levels and the definition of plans of civil protection. The focus is on practical and logistical issues met in all these phases and the counter-measures adopted.At present the system consists in 13 wire extensometers, 1 thermometer, 1 rain gauge and 3 cameras. Should a velocity threshold be exceeded by two or more sensors, the attention level would be entered, causing improved monitoring and surveillance. In case the behavior of the landslide changes and, by using expert judgment and forecasting methods, an imminent failure is hinted, then an alarm is issued and the upper road is closed.This paper can provide ideas and solutions for a landslide early warning system that aims to be simple, flexible, versatile and with a low probability of giving false alarms

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2- and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present.

Regional-scale forecasting of landslides is not a straightforward task. In this work, the spatiotemporal forecasting capability of a regional-scale landslide warning system was enhanced by integrating two different approaches. The temporal forecasting (i.e. when a landslide will occur) was accomplished by means of a system of statistical rainfall thresholds, while the spatial forecasting (i.e. where a landslide should be expected) was assessed using a susceptibility map. The test site was the Emilia Romagna region (Italy): the rainfall thresholds used were based on the rainfall amount accumulated over variable time windows, while the methodology used for the susceptibility mapping was the Bayesian tree random forest in the tree-bagger implementation. The coupling of these two methodologies allowed setting up a procedure that can assist the civil protection agencies during the alert phases to better define the areas that could be affected by landslides. A similar approach could be easily adjusted to other cases of study. A validation test was performed through a back analysis of the 2004–2010 records: the proposed approach would have led to define a more accurate location for 83 % of the landslides correctly forecasted by the regional warning system based on rainfall thresholds. This outcome provides a contribution to overcome the largely known drawback of regional warning systems based on rainfall thresholds, which presently can be used only to raise generic warnings relative to the whole area of application.

The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty-clayey sedimentary cover.In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques.PS-InSARâ\u84¢ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14. min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management. © 2014