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The results of the continuous monitoring of ground deformation throughout the Tuscany region using radar images acquired by the Sentinel-1 satellite constellation of the European Space Agency (ESA) are presented here. This new monitoring approach, based on systematic imagery processing and analysis of deformation time series, is discussed at regional (for the entire Tuscany) and at local scale in the context of a case study of the Carpineta landslide, which is a large, active earth slide in the Northern Apennines (Pistoia province). The landslide registered an acceleration during the winter and spring of 2018 as a direct consequence of rainfall and snow melt. The increase in the deformation rate of the landslide, which led to the damage of several buildings, was promptly detected and monitored due to the enhanced temporal repetitiveness offered by the Sentinel-1 constellation. The results demonstrate that advances in satellite sensors, increases in computing capacity and the refinement of processing approaches and data screening tools can contribute to the development of new paradigms in satellite-based monitoring systems. Sentinel-1 data, which are systematically acquired with short revisiting times and then promptly processed, can now be used as a tool for the systematic tracking of ground deformation at the regional scale and for the continuous monitoring of slow and very slow landslides. [ABSTRACT FROM AUTHOR]

Rockfalls are a recurrent cause of disruption for transportation corridors running along the bottom of U-shaped alpine valleys. In some scenarios, risk may effectively be reduced only by implementing an early-warning system able to give notice of incipient failures on the slope. This paper describes a successful example of rockfall forecasting and risk management in proximity of the Gallivaggio sanctuary (San Giacomo Valley, Central Italian Alps). Since 2016, a Ground-Based Synthetic Aperture Radar continuously monitored a roughly 500-m high, sub-vertical granitic slope. Monitoring data evidenced the presence and continued movement of a ~ 5000 m3 highly unstable mass, having a projected fall trajectory directly threatening the sanctuary and the adjacent segment of a national road. Traffic and access to the sanctuary were regulated by a sequence of alert thresholds, and restrictive orders were issued according to the activity of the instability. The rock mass eventually fell, and the failure-time was accurately predicted several hours in advance. Despite damage to both the road and buildings, the timely evacuation of the area prevented any loss of life. The case study provides a reference framework to better manage rockfall risk in areas where the installation of adequate protective barriers is not technically feasible. [ABSTRACT FROM AUTHOR]

In this manuscript, an integrated strategy that exploits both phase and amplitude features of satellite SAR (synthetic aperture radar) images and ground data is proposed for deriving the deformation field induced by a complex landslide that affected part of the village of Ponzano (Abruzzi Region, Central Italy). The February 12, 2017, landslide was triggered by the combined effects of intense rainfalls and snowmelt that saturated the slope. The SqueeSAR algorithm was applied to two C-band SAR datasets, composed by Radarsat-2 and Sentinel-1 images, spanning a nine-year time interval before the landslide occurrence. Moreover, the amplitude information carried by two TerraSAR-X images, acquired immediately before and after the event, was exploited to derive the total displacement generated by the landslide movement by means of the RMT (rapid motion tracking) algorithm. The obtained results allow describing the landslide behavior before and after its failure. In particular, the back-monitoring analysis shows that the landslide was already slowly moving, with deformation rates increasing from the Radarsat-2 to the Sentinel-1 monitored periods, 10 years before its complete mobilization. The landslide failure of February 2017 produced maximum displacements of about 10 m in some sectors of the affected area. The registered deformation rates and the localization of the maximum displacements areas were confirmed by field data, collected during a field campaign and a helicopter recognizance of the damaged areas, both performed after the event. [ABSTRACT FROM AUTHOR]

On 24 October 2015, following a period of heavy rainfall, a landslide occurred in the Calatabiano Municipality (Sicily Island, Southern Italy), causing the rupture of a water pipeline supplying water to the city of Messina. Following this event, approximately 250,000 inhabitants of the city suffered critical water shortages for several days. Consequently, on 6 November 2015, a state of emergency was declared (O.C.D.P. 295/2015) by the National Italian Department of Civil Protection (DPC). During the emergency management phase, a provisional by-pass, consisting of three 350-m long pipes passing through the landslide area, was constructed to restore water to the city. Furthermore, on 11 November 2015, a landslide remote-sensing monitoring system was installed with the following purposes: (i) analyse the landslide geomorphological and kinematic features in order to assess the residual landslide risk and (ii) support the early warning procedures needed to ensure the safety of the personnel involved in the by-pass construction and the landslide stabilization works. The monitoring system was based on the combined use of Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) and terrestrial laser scanning (TLS). In this work, the preliminary results of the monitoring activities and a remote 3D map of the landslide area are presented. [ABSTRACT FROM AUTHOR]

Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern in many countries, including Italy. Over the last 15 years, an increasing number of applications have aimed to demonstrate the applicability of images captured by space-borne Synthetic Aperture Radar (SAR) sensors in slope instability investigations. InSAR (SAR interferometry) is currently one of the most exploited techniques for the assessment of ground displacements, and it is becoming a consolidated tool for Civil Protection institutions in addressing landslide risk. This paper presents a subset of the results obtained in Italy within the framework of SAR-based programmes and applications intended to test the potential application of C- and X-band satellite interferometry during different Civil Protection activities (namely prevention, prevision, emergency response and post-emergency phases) performed to manage landslide risk. Analysis of satellite SAR data is demonstrated to play a major role in the investigation of landslide-related events at different stages, including detection, mapping, monitoring, characterization and prediction. In addition, this paper also discusses the limitations that still exist and must be overcome in the coming years to manage the transition of satellite SAR systems towards complete operational use in landslide risk management practices. [ABSTRACT FROM AUTHOR]

Badlands can be defined as complex and peculiar types of erosional formations that develop in clayey environments and are mainly favoured by lithological and topographic features, as well as by markedly seasonal climate. This work aims at assessing badland susceptibility in Volterra municipality located in Tuscany region (Italy) by means of bivariate statistical analysis implemented in a geographic information system. The Volterra municipality is affected by intense soil erosion processes, including rill and gully erosion usually turned out as badland forms, mostly occurring on Pliocene--Pleistocene clayey sediments. Firstly, an inventory of 234 badland areas was produced on the basis of an available pre-existing database, integrated with the interpretation of aerial photographs and supported by a field survey. Badlands were distinguished in type A and type B, according to different evolutional stage, vegetation presence and consequently different landforms. Then, nine geoenvironmental factors supposed to be predisposing for badland occurrence were chosen and combined with the spatial frequency of badland areas derived from the inventory, through Information Value Statistic approach. The result was a badland susceptibility map that highlights a strong control of lithology, slope gradient and land use in conditioning badland development in the investigated area. The effectiveness of the performed model was demonstrated by a validation test computed through a receiver operating characteristics analysis. The outcomes of this work provide an updated badland database that is useful for soil erosion management and further land-use planning within the Volterra municipality. [ABSTRACT FROM AUTHOR]