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Cascading landslides are specific multi-hazard events in which a primary movement triggers successive landslide processes. Areas with dynamic and quickly changing environments are more prone to this type of phenomena. Both the kind and the evolution velocity of a landslide depends on the materials involved. Indeed, rockfalls are generated when rocks fall from a very steep slope, while debris flow and/or mudslides are generated by fine materials like silt and clay after strong water imbibition. These events can amplify the damage caused by the initial trigger and propagate instability along a slope, often resulting in significant environmental and societal impacts. The Morino-Rendinara cascading landslide, situated in the Ernici Mountains along the border of the Abruzzo and Lazio regions (Italy), serves as a notable example of the complexities and devastating consequences associated with such events. In March 2021, a substantial debris flow event obstructed the Liri River, marking the latest step in a series of landslide events. Conventional techniques such as geomorphological observations and geological surveys may not provide exhaustive information to explain the landslide phenomena in progress. For this reason, UAV image acquisition, InSAR interferometry, and pixel offset analysis can be used to improve the knowledge of the mechanism and kinematics of landslide events. In this work, the interferometric data ranged from 3 January 2020 to 24 March 2023, while the pixel offset data covered the period from 2016 to 2022. The choice of such an extensive data window provided comprehensive insight into the investigated events, including the possibility of identifying other unrecorded events and aiding in the development of more effective mitigation strategies. Furthermore, to supplement the analysis, a specific finite element method for slope stability analysis was used to reconstruct the deep geometry of the system, emphasizing the effect of groundwater-level flow on slope stability. All of the findings indicate that major landslide activities were concentrated during the heavy rainfall season, with movements ranging from several centimeters per year. These results were consistent with numerical analyses, which showed that the potential slip surface became significantly more unstable when the water table was elevated. [ABSTRACT FROM AUTHOR]

Landslides represent a major problem in human activities, especially in the proximity of cities or infrastructure. In this paper, we present the peculiar case of Pietracamela, Italy. Pietracamela is a small village located in the Central Apennines, a few kilometers north of the Gran Sasso Mountain. The peculiarity of the case study is the fact that the village is simultaneously affected by two different types of slope instabilities. The southwest sector, representing the historical part of the village, has been affected by large rockfalls generated from the "Capo le Vene" cliff located in the south of the village. The northeastern sector of the village represents the most recent urbanized area and is involved in a deep-seated landslide that, in the last decades, has damaged buildings and infrastructure. In this context, we have used two different types of remote sensing techniques to study the two phenomena. The rockfall area has been surveyed through the use of an Unmanned Aerial Vehicle (UAV) that allowed the definition of main joint sets and the volume of blocks associated with the most recent (2011) rockfall event. Three main joint sets have been highlighted, which are responsible for the failure of the "Capo le Vene" cliff. The volume of blocks that failed during the last rock failure in 2011 ranged from a few to 1500 m3. The deep-seated landslide has been studied by analyzing borehole data and 20 years of InSAR data from ERS1/2, ENVISAT, COSMO-SkyMed, and SENTINEL-1. It has been highlighted by InSAR analysis that the northeast sector of the village shows a perfectly linear displacement trend that generates movements up to about 230 mm (about 1 cm/year). [ABSTRACT FROM AUTHOR]

Rocky coastlines are characterised by steep cliffs, which frequently experience a variety of natural processes that often exhibit intricate interdependencies, such as rainfall, ice and water run-off, and marine actions. The advent of high temporal and spatial resolution data, that can be acquired through remote sensing and geomatics techniques, has facilitated the safe exploration of otherwise inaccessible areas. The datasets that can be gathered from these techniques, typically combined with data from fieldwork, can subsequently undergo analyses employing/applying machine learning algorithms and/or numerical modeling, in order to identify/discern the predominant influencing factors affecting cliff top erosion. This study focuses on a specific case situated at the Conero promontory of the Adriatic Sea in the Marche region. The research methodology entails several steps. Initially, the morphological, geological and geomechanical characteristics of the areas were determined through unmanned aerial vehicle (UAV) and conventional geological/geomechanical surveys. Subsequently, cliff top retreat was determined within a GIS environment by comparing orthophotos taken in 1978 and 2022 using the DSAS tool (Digital Shoreline Analysis System), highlighting cliff top retreat up to 50 m in some sectors. Further analysis was conducted via the use of two Machine Learning (ML) algorithms, namely Random Forest (RF) and eXtreme Gradient Boosting (XGB). The Mean Decrease in Impurity (MDI) methodology was employed to assess the significance of each factor. Both algorithms yielded congruent results, emphasising that cliff top erosion rates are primarily influenced by slope height. Finally, a validation of the ML algorithm results was conducted using 2D Limit Equilibrium Method (LEM) codes. Ten sections extracted from the sector experiencing the most substantial cliff top retreat, as identified by DSAS, were utilised for 2D LEM analysis. Factor of Safety (FS) values were identified and compared with the cliff height of each section. The results from the 2D LEM analyses corroborated the outputs of the ML algorithms, showing a strong correlation between the slope instability and slope height (R2 of 0.84), with FS decreasing with slope height. [ABSTRACT FROM AUTHOR]

Cascading landslides are sequences of multiple landslides that commonly involves significant volumes of material and exhibit variable velocity up to several m/s. The impact of these processes is generally significant so that they can claim victims and be responsible of significant losses. Considering the complexity of the process, their mitigation involves the understanding of causeeffect relations between the initial triggering event and subsequent cascading processes as well as the development of methodological framework for their analysis. On this basis, this work aims to analyse the characteristics of the cascading landslide event of Morino-Rendinara, in the L’Aquila province, applying a procedure that, comprising multiple methods, is capable of providing data depicting mechanism and kinematics of the system, anatomy of landslides and prospective susceptibility scenario. [ABSTRACT FROM AUTHOR]

Rockfalls are among the most dangerous natural hazards. The study of these phenomena may be complex in relation to the geology and the rock mass characteristics. Recent advances on the use of remote sensing techniques made the survey of rock slopes easier and faster, increasing the amount and quality of data. At the same time, the improved availability of software for characterizing rock slopes and simulating rockfalls permits a more detailed and precise definition of rockfall hazard areas. In this context, this research highlights the importance of using remote sensing techniques in the study of these phenomena, especially in developing accurate and reliable geological and structural models. The Regional Park of Monte Conero (Ancona, Italy) is used as the case example. The study area has been investigated through conventional geological/structural surveys, UAV photogrammetry and iPad-based LiDAR. The data gathered from surveys have been used to perform rockfall simulations and define potential mitigation measures. Finally, innovative visualization techniques based on the use of Virtual Reality will be introduced for an improved interpretation of geological and structural data and simulation results. [ABSTRACT FROM AUTHOR]

Natural hazard is recognized to be a threat to human society that is becoming more critical under the perspective of climate change. Italy is one of the most exposed European countries to hydrogeomorphological hazard, as proven by the annual casualties and economic losses. Among the most recent events, the one happened in the Misa river catchment in 2022 is of particular interest for the great amount of rainfall poured in just one night, which led to extensive erosion. The mountainous part of the catchment was hit by several landslides, and the resulting sediments and debris, transported downstream by rivers, increased the amount of damages. This event was interpreted as directly caused by climate change, as it was linked to a tropical storm not common at this latitude. This work proposes an analysis of this exceptional event from a hydrological point of view. The 2022 event was compared with other relevant events from the past, in order to evaluate the peak discharge, the sediment erosion and transport processes in the area for different scenarios. The analysis included the modelling at catchment scale with two physically-based models: SWAT, which provides results on channel processes, and SMART-SED, working at the catchment scale. The two scales of analysis, together with field surveys, gave a better understanding of the evolution of the shallow processes during the events. Finally, this work intends to highlight the relevance of hydrological modelling for the management of hazard in different scenarios at catchment scale. [ABSTRACT FROM AUTHOR]

The characterization of landslides located in remote areas poses significant challenges due to the costs of reaching the sites and the lack of reliable subsurface data to constrain geological interpretations. In this paper, the advantages of combining field and remote sensing techniques to investigate the deformation and stability of rock slopes are demonstrated. The characterization of the Fels landslide, a large, slowly deforming rock slope in central Alaska, is described. Historical aerial imagery is used to highlight the relationship between glacier retreat and developing instability. Airborne laser scanning (ALS) and Structure-from-Motion (SfM) datasets are used to investigate the structural geological setting of the landslide, revealing a good agreement between structural discontinuities at the outcrop and slope scales. The magnitude, plunge, and direction of slope surface displacements and their changes over time are studied using a multi-temporal synthetic aperture radar speckle-tracking (SAR ST) dataset. The analyses show an increase in displacement rates (i.e., an acceleration of the movement) between 2010 and 2020. Significant spatial variations of displacement direction and plunge are noted and correlated with the morphology of the failure surface reconstructed using the vector inclination method (VIM). In particular, steeper displacement vectors were reconstructed in the upper slope, compared to the central part, thus suggesting a change in basal surface morphology, which is largely controlled by rock mass foliation. Through this analytical approach, the Fels landslide is shown to be a slow-moving, compound rockslide, the displacement of which is controlled by structural geological features and promoted by glacier retreat. [ABSTRACT FROM AUTHOR]

Italy is famous for its one-of-a-kind landscapes and the many cultural heritage sites characterizing the story of its regions. In central Italy, during the medieval age, some of them were built on the top of high and steep cliffs, often on the top of ancient ruins, to protect urban agglomerations, goods and people. The geographical locations of these centers allowed them to maintain their original conformation over time, but, at the same time, exposed them to a high risk of landslides. In this context, this research aimed to present an integrated and low-cost approach to study the potential landslide phenomena affecting two medieval towns. Field surveys and mapping were carried out through the use of innovative digital mapping tools to create a digital database directly on the field. Data gathered during field surveys were integrated with GIS analyses for an improved interpretation of the geological and geomorphological features. Due to the inaccessibility of the cliffs surrounding the two villages, a more detailed analysis of these areas was performed through the use of unmanned aerial vehicle-based photogrammetry, while advanced differential synthetic aperture radar interferometry (A-DInSAR) interpretation was undertaken to verify the stability of the buildings in proximity to the cliffs and other potential active failures. The results of the study highlighted the similar geometry and structural settings of the two areas. Kinematically, the intersection of three main joint sets tends to detach blocks (sometimes in high volumes) from the cliffs. The A-DInSAR analysis demonstrated the presence of a landslide failure along the northwest side of the Monte San Martino town. The buildings in proximity to the cliffs did not show evidence of movements. More generally, this research gives insights into the pro and cons of different survey and analysis approaches and into the benefits of their procedural integration in space and in time. Overall, the procedure developed here may be applied in similar contexts in order to understand the structural features driving slopes' instabilities and create digital databases of geological/monitoring data. [ABSTRACT FROM AUTHOR]

This work presents the case study of the San Lorenzo road tunnel, a linear infrastructure located in Friuli Venezia Giulia, northern Italy, affected by the so-called Passo della Morte landslide. This slope instability phenomenon has caused several problems since the beginning of the tunnel construction works, like water seepage and concrete lining detachments, increasing the safety risk for road users. Due to these circumstances, numerous studies have been conducted and a monitoring system has been developed since 2014 to control the ongoing situation of the most damaged portions of the road tunnel. Building on the monitoring data, studies and knowledge accumulated over the years, this paper describes the work done to trace back the sum of landslide-induced stresses directly responsible for the current damages on the tunnel. The first steps taken in this direction have included an adequate representation of the crack pattern on the tunnel vault. This has been used both as an initial goal and as a means of validation in the development of a finite element model. From the latter, it will be possible to infer the landslide-induced stress combination mentioned earlier. [ABSTRACT FROM AUTHOR]

Several orogenic belts exhibit regional-scale anticlines characterized by prominent faults in their crestal/forelimb zone. These faults are also a common feature in the Neogene fold-and-thrust belt of the Apennines, where they have been contrastingly interpreted as younger-on-older thrust faults, large-scale strike-slip faults, and pre- or syn-thrusting normal faults. In this study, we analysed a NW–SE-trending fault (Montagna dei Fiori Fault) that affects the hinge-zone/forelimb of the Montagna dei Fiori Anticline. This fold is the outermost exposed contractional structure within the Pliocene–Quaternary antiformal stack of the outer Central Apennines. The integration of stratigraphic and structural data collected during a field geological survey enabled us to reconstruct a multiphase reactivation and deformation along the Montagna dei Fiori Fault. From the novel field data, a different interpretation for the evolution of the Montagna dei Fiori Fault is proposed. The fault originated as a Late Cretaceous – middle Miocene, NE-dipping, Dinaric up-thrust and was later reactivated, displaced and rotated during Pliocene Apennine thrusting and related folding, until assuming a present-day SW-dipping attitude with an apparent normal fault character. This newly proposed Dinaric origin of the Montagna dei Fiori structure is compared with an analogous subsurface example of a Palaeogene–Quaternary structure imaged by seismic reflection profile in the Adriatic foreland. The outcome of this combined field and subsurface investigation provides new elements to unravel the complex evolution of the Apennine thrust belt that developed at the expense of a previously deformed foreland, ahead of the advancing Dinaric chain. [ABSTRACT FROM AUTHOR]