Search

Landslide hazards have significant social, economic, and environmental impact. This work provides a critical review of the main existing literature using satellite data for mapping landslides. We created and examined an extensive bibliographic database from Web of Science (WoS) consisting in 291 outputs from > 1,000 authors who studied almost 700,000 landslides across all continents, for a total of 52 countries represented with China and Italy on top of the list with more authors. The outputs are equivalent to ~ 5% of the whole landslide-related production for the period 1996–2022, with a 600% increase in the number of papers after 2014 driven by the availability of Sentinel-1 and Sentinel-2 data. Analysis of the geographical location across the 66 different countries analysed shows that, within the total number of contributions, the satellite imagery was used to detect and map two main types of landslides: flows and slides. When specified in the manuscripts, the events have been triggered by rainfall (104 cases), earthquakes (32 cases), or both (17 cases). Slope instabilities in these areas were predominantly identified through manual detection (40%); but since 2020, the advent of artificial intelligence is suppressing all other techniques. Despite the undisputed progress of EO-based landslide mapping over the last 26 years, which makes it a consolidated tool for many landslide-related applications, challenges still remain for an effective and operational use of EO images for landslide detection and mapping, and we provide a perspective for future applications considering the existing and the planned SAR satellite missions. [ABSTRACT FROM AUTHOR]

Identifying the instability areas provides useful information about the recognition of the vulnerable zones and, thus, helps to potentially decrease the harm to the infrastructure and the hazard conditions in inhabited areas. In this regard, morphometric parameters and tectonic setting are widely employed in mapping, modelling and understanding of instability processes. The present study is aimed to analyse the combined effects of slope morphometry (slope gradient, slope curvature, local relief), of lithology, of drainage density and of tectonic setting on the distribution of landslides. The study area is located in the Mesima Basin that lies in the central part of the Calabria region (southern Italy). The morphometric analysis was carried out by geographic information system (GIS) techniques, whereas the geomorphic attributes were computed by a digital elevation model (DEM). The recognized landslides and faults were digitized and stored in a GIS geo-database that allowed the construction of relative density maps. A total of 1 991 landslides and 231 tectonic lineaments were recognized and mapped. The distribution of the collected data suggests that the occurrence of landslides is not random. Indeed, the research highlights as the lithology, the fault density, the slope gradient and the local relief play an important role in determining the landslide occurrence. The used approach is aimed to reinforce the knowledge about the validity of the application of morphometric analysis to the landslide susceptibility. The Mesima Basin is a poorly studied area of the Calabria from a geomorphological viewpoint. Indeed, previous researches focused mainly on geological and on tectonic aspects, as well as on instability phenomena in the Mesima surroundings. Thus, this paper takes a step forward with respect to previous studies because it augments the knowledge about the relationship between faults, morphometric features and the occurrence of landslide. [ABSTRACT FROM AUTHOR]

This paper reports a case study of the interaction between a slow-moving landslide in clay soil and a railway tunnel protected by sheet pile walls, that crosses the landslide accumulation. The earthflow, that develops in the Southern Apennines, Italy, has been long studied and monitored by different organizations, such as the national railway company and the University of Basilicata. Since the investigated landslide and construction typologies are quite diffused in mountainous areas, the case study can be considered representative of a large number of other similar cases. Differently from other approaches proposed in the literature, the role of the landslide slip surface depth, changing in the directions longitudinal and transversal to the tunnel, and of structural connections, affecting the pile–tunnel system response, are accounted for in detail. Several numerical models are used to simulate the interaction between the sliding soil and tunnel. Different 2D and 3D geotechnical and structural models are adopted to reproduce stress–strain scenarios compatible with the experimental evidence. The modeling results indicate that the interaction varies considerably along the tunnel length because of the 3D geometry of the landslide, and is conditioned by the residual shear strength available on the slip surface. The expansion joints in the tunnel lining only marginally influence the stress in the structure because of the presence of the adjacent sheet pile walls, which enable considerable collaboration between the tunnel sectors. [ABSTRACT FROM AUTHOR]

Perceptions of risk are a key issue when seeking to develop systems, practices and policies to protect local populations. This is particularly evident when risk mitigation strategies involve non-structural measures such as relocation and warning systems which presuppose the active involvement of the communities in question. This study adopts an interdisciplinary approach to studying the perceptions, knowledge and opinions on landslide risk amongst residents in Sarno, a small town in Southern Italy which was hit by disastrous landslides on 5-6 May 1998. The paper presents the results of a survey conducted in the months of March, April and May 2013 using a purpose-designed questionnaire. The survey was conducted using face-to-face interviews with 100 residents, 60 of whom live inside the so-called 'red zone', a territory declared at high residual risk soon after the events of 1998. The questionnaire included questions relating to perceived risk exposure, trust in institutions responsible for risk management, evaluations of risk mitigation measures and the early-warning strategy. The results of the study clearly emerges, amongst other issues, that the organisms which are responsible for risk management in Sarno need to develop more effective communication strategies in order to transmit knowledge about the actions implemented to reduce landslide risk in the area. [ABSTRACT FROM AUTHOR]

Background: In Italy landslides are widespread natural phenomena causing a significant number of fatalities and huge economic losses throughout the country every year. Information on the spatial and temporal distribution of landslides at national scale is critical for developing landslide susceptibility, hazard and risk maps, as well as, more generally, for decision making in landslide risk management.Description: The paper presents, after a brief review on global and national landslide databases, a new geo-referenced catalog of recent landslides affecting the Italian territory. The catalog, called Franeitalia, includes both fatal landslide events and events that did not produce physical harm to people. It has been developed consulting online news sources from 2010 onwards. The following seven steps have been performed to define and populate the catalog: i) selection of news sources; ii) identification of effective search keywords; iii) collection of relevant news articles; iv) identification of landslide categories; v) definition of catalog fields; vi) information mining from news articles; vii) geo-referencing of the events. Landslide events are classified considering two numerosity categories and three consequence categories. The numerosity categories are: single landslide events (SLE), for records only reporting one landslide; and areal landslide events (ALE), for records referring to multiple landslides triggered by the same cause in the same geographic area. Both SLEs and ALEs are divided in three consequence classes according to whether the event produced victims and/or missing people (C1, very severe), injured persons and/or evacuations (C2, severe), or did not cause any physical harm to people (C3, minor). Information on the landslide events collected in the catalog always includes: data on the location of the event, day of occurrence of the landslide (s), source (s) of information, and number of landslides in case of areal events. Additional information may include: onset and duration of the landslide event, landslide characteristics, phase of activity, details on the consequences.Conclusions: Reports and statistics on the landslides included in the catalog are presented highlighting: the main figures of the landslide inventory, currently spanning from the 2010 to 2017 and including 8931 landslides; and time-dependent national and regional trends, with a focus on the consequences induced by the events. The paper also compares and discusses the figures in relation to other catalogs reporting recent landslides that occurred in the Italian territory. [ABSTRACT FROM AUTHOR]

Nowadays, several systems to set up landslide inventories exist although they rarely rely on automated or real-time updates. Mass media can provide reliable info about natural hazard events with a relatively high temporal and spatial resolution. The news publication about a natural disaster inside newspaper or crowdsourcing platforms allows a faster observation, survey, and classification of these phenomena. Several techniques have been developed for data mining inside social media for many natural events, but they have been rarely applied to the automatic extraction of "landslide events". This source of information allows continuous feedback from real world, and news concerning landslide events can be rapidly collected. In this work, the newspaper articles about landslides in Italy are automatically collected by an existing data mining algorithm, based on a semantic engine. The news has been analysed to assess their distribution over the territory and to verify the possibility of using them for hazard mapping purpose. In 10 years, from 2010 to 2019, the algorithm identified and geolocated 184322 articles referring to 32525 generical events ("news"). At first, the collected data underwent to a manual verification, followed by a classification based on news relevance, localization accuracy and time of publication. Then, these data have been used to identify the areas and the periods most affected by landslide phenomena. The analyses show that almost 42% of Italian municipalities have been affected by landslide. According to the results, the use of data mining is helpful for the creation of landslide databases where the day and the approximative location (municipality) of the possible landslide triggers are known. This database, in turn, can be used for scientific purposes, as the definition of the meteorological condition associated with landslide initiation, the validation of risk maps. It can also be used for a proper land use or risk mitigation planning, since the most landslide-prone municipalities can be defined. [ABSTRACT FROM AUTHOR]

Slope stability is influenced by a number of factors that modify the resisting/acting force ratio control landslide initiation and movement velocity. Among these, artificial vibrations have been identified as an important degrading factor for soil strength, but it is not fully clear if they can trigger or modulate movements of clay landslides. To contribute to a better understanding of the potential effect of vibrations on landslide movement, also in terms of boundary conditions, we analyzed monitoring data acquired at the toe of the Pietrafitta landslide in southern Italy. This landslide adjoins the SS87 national road that suffered periodic closure due to landslide activity and in April 2016 operates daytime only for risk mitigation purpose. This condition promoted a better identification of a potential cause-effect relation between traffic vibration and landslide movement. Results from data analysis and landslide modeling suggest that in condition of incipient movement, artificial vibrations, also of limited amplitude, are able to directly initiate clay landslide movement that due to the viscous nature of the involved material exhibit a specific displacement pattern that is not consistent with a sliding block model. [ABSTRACT FROM AUTHOR]

Landslides often happen where they have already occurred in the past. The potential of landslides to reduce or enhance conditions for further landsliding has long been recognized and has often been reported, but the mechanisms and spatial and temporal scales of these processes have previously received little specific attention. Despite a preponderance of qualitative and anecdotal evidence, analysis has been limited. As a result, there is little consensus on the meaning of terms such as landslide repetition, recurrence, and reactivation. This source of confusion is evident when such terms are also used to describe systems where landsliding is prevalent but unrelated to landslide history. Recent findings, partly based on a rare multi-temporal landslide inventory for an area in Italy, show that the impacts of earlier landslides affect a substantial fraction of landslides, that landslides following earlier landslides differ from those that do not, and that accounting for the effect of previous landslides can improve susceptibility assessments. These findings await confirmation in other landslide-prone landscapes but show that consecutive landsliding deserves more attention, which requires consistent terminology. No such terminology is presently available, and we therefore propose it in this manuscript. We use the term "uncorrelated landsliding" to describe situations where landslides are common, but where a correlation with environmental variables such as terrain steepness is not implied. We propose "correlated landsliding" to describe situations where landslides are common and correlations with environmental variables exist, and "path-dependent landsliding" to describe situations where causal relations exist between consecutive landslides, for instance, when landslides occur at the scarp of previous landslides. These are situations where past landslides impact future landslides. Within the path-dependent category, we distinguish three subcategories based on the spatial distance between earlier and later landslides: "reactivation" or "continuation" if essentially the same material recommences or continues to slide, "local activation" if an earlier slide causes changes in a local hillslope that cause a later slide, and "remote activation" if an earlier slide causes changes elsewhere in the landscape that cause a later landslide. We use this proposed set of terms to outline some prominent knowledge gaps and potential research questions. [ABSTRACT FROM AUTHOR]

Understanding the mechanism of a landslide and its evolution is of fundamental importance in the risk management process. This work introduces an articulated approach to the problem, applying it to a specific case in the south of Italy where a gravitational movement insists on a section of an important highway. In recent years, the site has been investigated from a geomorphological and a lithological point of view, and a comprehensive geomechanical characterization has been carried out by means of on-site and laboratory tests. The area has been instrumented with a monitoring system composed of automatic inclinometers, piezometers, a rainfall station, and time domain reflectometry (TDR) cables. These sensors have monitored the deformation processes and their correlation with groundwater fluctuation. A 2D finite differences model (FDM) of the slope has been created, calibrated, and validated through back analysis, carried out using the monitoring data available. A secondary creep phenomenon, barely influenced by the water level rise due to occasional rainfall, has been identified and modeled using the Burgers viscoelastic constitutive model. Variations in the piezometric level were introduced and their effect accounted for the numerical model refinement. Once the improvements had been completed together with the reproduction of past events, a predictive analysis was carried out in order to forecast the most probable slope behavior relative to the incoming year. At the end of this phase, the infrastructure supervisor should have information about possible deformations to be compared with the near real-time monitoring outcomes and design assumptions. This procedure allows real-time monitoring of the compatibility of slope deformations with highway safety. [ABSTRACT FROM AUTHOR]

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events. [ABSTRACT FROM AUTHOR]

This study evaluates the performances of the presence-only approach, Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment (Sicily, Italy). This catchment underwent several meteorological stresses, resulting in hundreds of shallow rapid mass movements between 2007 and 2011. In particular, the area has become known for two disasters, which occurred in 2009 and 2010; the first weather system did not pass directly over the catchment; however, peak rainfall was registered over the basin during the second meteorological event. Field data were collected to associate the depth from the slope surface that material was mobilised at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes, divided into shallow failures for maximum depths of 1 m and deep ones in case of values equal or greater than 1 m. Topographic attributes from a 2-m DEM were used as predictors, together with medium resolution vegetation indexes derived from ASTER scenes and geological, land use and tectonic maps. The presence-only approach discriminated between the two depth classes at the landslide trigger zone, producing excellent prediction skills associated with relatively low variances across a set of 50 randomly generated replicates. The role of each predictor was assessed to ascertain the significance to the final model output. This work uses simple field measurements to produce triggering-thickness susceptibility, which is a novel approach and may perform better as a proxy for landslide hazard assessments with respect to more common susceptibility practises. [ABSTRACT FROM AUTHOR]

Review of the literature on the reconstruction of the rainfall responsible for slope failures reveals that criteria for the identification of rainfall events are lacking or somewhat subjective. To overcome this problem, we developed an algorithm for the objective and reproducible reconstruction of rainfall events and of rainfall conditions responsible for landslides. The algorithm consists of three distinct modules for (i) the reconstruction of distinct rainfall events, in terms of duration ( D, in h) and cumulated event rainfall ( E, in mm), (ii) the identification of multiple ED rainfall conditions responsible for the documented landslides, and (iii) the definition of critical rainfall thresholds for possible landslide occurrences. The algorithm uses pre-defined parameters to account for different seasonal and climatic settings. We applied the algorithm in Sicily, southern Italy, using rainfall measurements obtained from a network of 169 rain gauges, and information on 229 rainfall-induced landslides occurred between July 2002 and December 2012. The algorithm identified 29,270 rainfall events and reconstructed 472 ED rainfall conditions as possible triggers of the observed landslides. The algorithm exploited the multiple rainfall conditions to define objective and reproducible empirical rainfall thresholds for the possible initiation of landslide in Sicily. The calculated thresholds may be implemented in an operational early warning system for shallow landslide forecasting. [ABSTRACT FROM AUTHOR]

In Italy, rainfall-induced landslides are recurrent phenomena that cause societal and economic damage. Thus, assessing the rainfall conditions responsible for landslides is important and may contribute to reducing risk. The prediction of rainfall-induced landslides relies primarily on empirical rainfall thresholds. However, the thresholds are affected by uncertainties that limit their use in operational warning systems. A source of uncertainty lies in the characterization of the rainfall events responsible for landslides. Objective criteria for the definition of rainfall events are lacking. To overcome the problem, we propose an algorithm that reconstructs the rainfall events, identifies the rainfall conditions that have resulted in landslides, and measures the duration and the cumulated rainfall for the events. The algorithm is independent from the local settings and uses a reduced set of parameters to account for different physical settings and operational conditions. We tested the algorithm in Sicily, Italy, with rainfall and landslide information between January 2002 and December 2012. The rainfall conditions responsible for landslides identified by the algorithm were compared against results obtained manually. The algorithm was proven capable of accurately reconstructing most (87.7 %) of the rainfall events. For each landslide, the algorithm identified a variable number of rainfall conditions responsible for the failures, which are equally likely triggers of the landslide. This opens the possibility of evaluating the uncertainty introduced by different criteria to determine the rainfall events responsible for landslides. Use of the algorithm shall contribute to reducing the uncertainty in the definition of landslide-triggering rainfall events, to compiling large catalogues of rainfall events with landslides and to determining reliable rainfall thresholds for possible landslide occurrence. [ABSTRACT FROM AUTHOR]

In the last decades, building damage caused by landslides in urban areas has increased due to the rapid growth of urbanization even on landslide-prone slopes. This work presents the analysis results of landslide damage evolution by means of a macrodamage index in relation to the characteristics of landslides. The study area is located in southern Italy, and is affected by slow-moving landslides, which, over time, have caused relevant effects on the buildings. A series of geological and geomorphological studies and field surveys, supported by monitoring via conventional geotechnical techniques, allowed us to classify four categories of landslides based on the following criteria: landslide movement, type of material and estimated depth. Detailed field surveys aimed at evaluating distribution and evolution of the damage to buildings located within and near the unstable area were carried out in 2005 and 2011. The evaluation of the macrodamage index in two different years enabled us to directly correlate the features of the landslide categories and their effects on the urban fabric. [ABSTRACT FROM AUTHOR]

A landslide in a stiff clay formation, interrupting the excavation of a tunnel for a major railway in Sicily, is reported. Limit equilibrium and FEM undrained and drained analyses of the slope before tunnel excavation agree in showing that the slope was stable with a relatively high factor of safety and the critical slip surface is located well above the tunnel. The undrained stability of the tunnel checked both via FEM and via standard analytical solutions for face stability is also verified. The FEM analyses of the slope have been repeated considering the excavation of the tunnel in undrained and drained conditions. The advancement of the tunnel face is simulated in a plane strain analysis by the Panet method. In undrained conditions, the system keeps stable. In drained conditions with a stress release factor of 50 %, the slope is on the verge of failing with a very low safety factor, while with a stress release factor of 80 %, it fails following a complex mechanism that matches the observed failure surface. These findings are discussed and some conclusions attempted. [ABSTRACT FROM AUTHOR]