A method for assessing and managing landslide residual hazard in urban areas

On February 14, 2010, a large landslide affected the urban centre of San Fratello town (Sicily Island, Southern Italy), causing severe damage to buildings, roadways, and infrastructure, as well as about 2000 evacuees. This large complex landslide, covering more than 1 km² in extension, represents one of the major phenomena that ever occurred in Sicily. In order to manage the landslide risk, the civil protection system was activated as part of the initial response to the emergency (the “emergency phase”). This involved the Civil Protection Departments both at national (DPC) and regional (DRPC) levels, as well as scientific institutions (namely “Competence centres”, CdCs), local administration personnel, and technicians. On March 8, 2010, during the post-event recovery phase, a ground-based synthetic aperture radar (GB-InSAR) system was installed in order to monitor the ground surface deformation, assess the landslide residual risk, and analyse its displacement trend. Accurate field surveys and building inspections were also performed for a validation of the GB-InSAR data, in order to map the ground deformation, plan building evacuation-demolishment, as well as check the efficiency of the landslide mitigation works. This paper describes the outcomes of the 57 month monitoring campaign (March 2010–December 2014), reporting the use of GB-InSAR data for near real-time monitoring, mapping, and post-emergency/recovery management activities. The final aim was to provide the civil protection personnel with a reliable, rapid, and easy communication system of the monitoring results, designed to an enhance understanding of the landslide phenomena, and to support the decision-making process.     

On the causes of landslides: Human activities,perception, and natural processes

Conceptual equations are presented for the net benefits, total risk, and total vulnerability associated with hazard zone occupation. It is shown that, as they are polycausal phenomena, landslides require a more sophisticated approach to this form of analysis than that employed for most other forms of hazard.Three examples of landsliding are examined. At Cuyocuyo, in the Peruvian Cordillera Oriental, slope instability is virtually inevitable, but human intervention may be disturbing some very fragile natural equilibria. At Calciano, in southern Italy, deforestation has resulted in a mudflow disaster, although man-made factors are not the only causes at work. Finally, in the Valle dell'Orco (also in southern Italy) demographic and agrarian change have aided the partial metamorphosis of the catchment into a large-scale mudflow complex (although the longer-term causes are natural, tectonic ones). These examples illustrate parts of the continuum that extends from dominant natural to dominant anthropogenic causes.Human intervention has played a key role in stimulating the natural antecedents of landslides occurring in the study areas. It is concluded that risk perception has not been wide enough to promote adequate risk mitigation, in part because of a failure properly to conceive of landslides as polycausal phenomena, in which man-made causes effectively cannot—and should not—be separated from natural ones.     

Assessing landslide exposure in areas with limited landslide information

Landslide risk assessment is often a difficult task due to the lack of temporal data on landslides and triggering events (frequency), run-out distance, landslide magnitude and vulnerability. The probability of occurrence of landslides is often very difficult to predict, as well as the expected magnitude of events, due to the limited data availability on past landslide activity. In this paper, a qualitative procedure for assessing the exposure of elements at risk is presented for an area of the Apulia region (Italy) where no temporal information on landslide occurrence is available. Given these limitations in data availability, it was not possible to produce a reliable landslide hazard map and, consequently, a risk map. The qualitative analysis was carried out using the spatial multi-criteria evaluation method in a global information system. A landslide susceptibility composite index map and four asset index maps (physical, social, economic and environmental) were generated separately through a hierarchical procedure of standardising and weighting. The four asset index maps were combined in order to obtain a qualitative weighted assets map, which, combined with the landslide susceptibility composite index map, has provided the final qualitative landslide exposure map. The resulting map represents the spatial distribution of the exposure level in the study area; this information could be used in a preliminary stage of regional planning. In order to demonstrate how such an exposure map could be used in a basic risk assessment, a quantification of the economic losses at municipal level was carried out, and the temporal probability of landslides was estimated, on the basis of the expert knowledge. Although the proposed methodology for the exposure assessment did not consider the landslide run-out and vulnerability quantification, the results obtained allow to rank the municipalities in terms of increasing exposure and risk level and, consequently, to identify the priorities for designing appropriate landslide risk mitigation plans.     

Evolutionary polynomial regression to alert rainfall-triggered landslide reactivation

The derivation of an alert model for landslide risk management is a paramount problem for those sites which are affected by complex landslides involving strategic infrastructures as well as towns. This is a quite common scenario all over the world and then it is a primary problem for the management of geomorphological risk. Along the Adriatic Coast of south Italy, Petacciato landslide is peculiar, since it showed 11 reactivations between 1924 and 2009. It is a deep-seated landslide, and the history of its reactivations shows that even if generally related to quite abundant rainfall periods, there is no clear correlation between rainfall events and reactivations. For this reason, here, an analysis based on a data-driven evolutionary modeling technique is attempted, in order to identify an alert model based on cumulative rainfall heights. Modeling results are quite interesting and encouraging, since they are able to provide landslide forecasting whereas no false positive are ever returned. This work shows the results of this attempt as well as an analysis of the input to the modeling approach, in order to identify which are those cumulative rainfall heights which are physically sound with respect to the particular landslide.     

Quantitative analysis of consequences to masonry buildings interacting with slow-moving landslide mechanisms: a case study

Quantitative analysis of consequences (in terms of expected monetary losses) induced by slow-moving landslide mechanisms to buildings or infrastructure networks is a key step in the landslide risk management framework. It can influence risk mitigation policies as well as help authorities in charge of land management in addressing/prioritizing interventions or restoration works. This kind of analysis generally requires multidisciplinary approaches, which cannot disregard a thorough knowledge of landslide mechanisms, and rich datasets that are seldom available as testified by the limited number of examples in the scientific literature. With reference to the well-documented case study of Lungro town (Calabria region, southern Italy)—severely affected by slow-moving landslides of different types—the present paper proposes and implements a multi-step procedure for monetary loss forecasting associated with different landslide kinematic/damage scenarios. Procedures to typify landslide mechanisms and physical vulnerability analysis, previously tested in the same area, are here appropriately merged to derive both kinematic and damage scenarios to the exposed buildings. Then, the outcomes are combined with economic data in order to forecast monetary loss at municipal scale. The proposed method and the obtained results, once further validated, could stand as reference case for other urban areas in similar geo-environmental contexts in order to derive useful information on expected direct consequences unless slow-moving landslide risk mitigation measures are taken.     

Area-scale landslide hazard and risk assessment

The paper deals with a methodology for quantitative landslide hazard and risk assessments over wide-scale areas. The approach was designed to fulfil the following requirements: (1) rapid investigation of large study areas; (2) use of elementary information, in order to satisfy the first requirement and to ensure validation, repetition and real time updating of the assessments every time new data are available; (3) computation of the landslide frequency of occurrence, in order to compare objectively different hazard conditions and to minimize references to qualitative hazard attributes such as activity states. The idea of multi-temporal analysis set forth by Cardinali et al. (Nat Hazards Earth Syst Sci 2:57–72, 2002), has been stressed here to compute average recurrence time for individual landslides and to forecast their behaviour within reference time periods. The method is based on the observation of the landslide activity through aerial-photo surveys carried out in several time steps. The output is given by a landslide hazard map showing the mean return period of landslides reactivation. Assessing the hazard in a quantitative way allows for estimating quantitatively the risk as well; thus, the probability of the exposed elements (such as people and real estates) to suffer damages due to the occurrence of landslides can be calculated. The methodology here presented is illustrated with reference to a sample area in Central Italy (Umbria region), for which both the landslide hazard and risk for the human life are analysed and computed. Results show the powerful quantitative approach for assessing the exposure of human activities to the landslide threat for a best choice of the countermeasures needed to mitigate the risk.An erratum to this article can be found at     

The Calatabiano landslide (southern Italy): preliminary GB-InSAR monitoring data and remote 3D mapping

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.     

A simple numerical procedure for timely prediction of precipitation-induced landslides in unsaturated pyroclastic soils

In the last 20 years, several catastrophic precipitation-induced landslides have hit villages, towns and roads in Campania (southern Italy), causing extensive damage and many fatalities. Although such phenomena have occurred since time immemorial, recent urbanisation and infrastructural development have produced a major increase in landslide risk. Due to climatic changes and further unavoidable increases in exposure, in the near future, the risk will become even greater. It is therefore high time to develop reliable criteria for landslide prediction. The paper discusses the main factors which affect the triggering of precipitation-induced landslides, highlighting the key role played by antecedent rainfalls which cannot be precisely accounted for using empirical criteria. We propose a simple 1D numerical approach able to predict the evolution of the key factors governing slope stability as a tool to predict the onset of slope failure, with potential benefits for early warning systems. The approach is calibrated through a well-documented case history.     

Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley,Italy

This article presents a multidisciplinary approach to landslide susceptibility mapping by means of logistic regression, artificial neural network, and geographic information system (GIS) techniques. The methodology applied in ranking slope instability developed through statistical models (conditional analysis and logistic regression), and neural network application, in order to better understand the relationship between the geological/geomorphological landforms and processes and landslide occurrence, and to increase the performance of landslide susceptibility models. The proposed experimental study concerns with a wide research project, promoted by the Tuscany Region Administration and APAT-Italian Geological Survey, aimed at defining the landslide hazard in the area of the Sheet 250 “Castelnuovo di Garfagnana” (1:50,000 scale). The study area is located in the middle part of the Serchio River basin and is characterized by high landslide susceptibility due to its geological, geomorphological, and climatic features, among the most severe in Italy. Terrain susceptibility to slope failure has been approached by means of indirect-quantitative statistical methods and neural network software application. Experimental results from different methods and the potentials and pitfalls of this methodological approach have been presented and discussed. Applying multivariate statistical analyses made it possible a better understanding of the phenomena and quantification of the relationship between the instability factors and landslide occurrence. In particular, the application of a multilayer neural network, equipped for supervised learning and error control, has improved the performance of the model. Finally, a first attempt to evaluate the classification efficiency of the multivariate models has been performed by means of the receiver operating characteristic (ROC) curves analysis approach.     

Monitoring, prediction, and early warning using ground-based radar interferometry

In order to define adequate prevention measures and to manage landslide emergencies, real-time monitoring is required. This paper presents two different applications of the remote sensing technique: the ground-based synthetic aperture radar interferometry, here proposed as a monitoring and early warning support for slope instability. Data acquisitions carried out through a ground-based synthetic aperture radar interferometer, operating in K_u band, installed in front of the observed slopes, are discussed. Two case studies, based on the use of the same apparatus (formerly developed by the Joint Research Center of the European Commission and by Ellegi-LiSALab srl), are reported: the first one concerns the monitoring of a large landslide, named Ruinon (Valfurva, Italy). The second one deals with the monitoring of the NW unstable slope in the Stromboli island aimed to implementing an early warning system. Acquired interferometric data are processed to provide displacements and velocity maps of the monitored area. The monitoring services ongoing on the Ruinon landslide and on Stromboli demonstrate the capability of this technique to operate in different operative settings (i.e., different phenomena and geological framework) and for different aims (monitoring for prevention, early warning, and emergency assessment). This methodology has also been proved by national and regional authorities of civil protection in order to provide a real-time monitoring for emergency management.     

Geomorphometric analysis based on discrete wavelet transform

This work presents a geomorphometric approach for outlining anomalies of the topographic surface that may be related to geological structures or to geomorphological phenomena. It is based on 2D discrete wavelet transform of digital elevation models. This transform is used to extract singularities of a series of data. This is specifically applied to a digital elevation model, in order to get its detail coefficients and to have evidence about their variations and values. In particular, this approach can be helpful for the delineation and identification of landforms singularities, like landslides and geological structures. The potential and effectiveness of this approach is shown by an application to a case study about a large deep-seated landslide, located at the central-south front of the Apennine in South Italy.     

Impact of event landslides on road networks: a statistical analysis of two Italian case studies

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.     

Geological features and landslide mechanisms of an unstable coastal slope (Petacciato, Italy)

On the basis of geological and geomorphological surveys, landslide phenomena are analysed on a slope along a stretch of the Adriatic coast, near Petacciato (Molise, Italy).

Locally, a blue clay sequence of Pleistocene outcrops, stratified with silty-sandy layers; bedding dips 3–8°NE and the slope has a similar attitude. This sequence evolves upwards to sands and conglomerates, with thickness of up to 40 m, on which the built-up area is located.

Several episodes of landslide reactivation occurred in the past century, involving the zone between the built-up area and the sea, along a coastal slope of over 2000 m long and 200 m high. Important roads and railway lines have been heavily damaged as well as the town itself.

The typology of the movement is a rotational–translational slide; the displacement reaches tens of centimetres at each reactivation episode along the entire coastal slope, extending well beyond the shore line.

Detailed studies already exists, but different mechanism failures have been proposed to explain the landslide phenomena. In this study, a new failure mechanism is proposed, (sudden spreading of Terzaghi, K., Peck, R.B., 1948. Soil Mechanics in Engineering Practice. Wiley and Sons New York) and analytical approaches have been adopted to evaluate the slope stability, based on the geotechnical and monitoring data and the geometrical and geological features of the slope.     

Landslide hazard zonation in high risk areas of Rethymno Prefecture,Crete Island,Greece

The central part of Rethymnon Prefecture, Crete Island, suffers from severe landslide phenomena because of its geological and geomorphological settings alternated by the human activities. The main landslide preparatory and triggering causal factors are considered to be the ground conditions (lithology), geomorphological processes (fluvial erosion, etc.), and the man-made actions (excavations, loading etc.). The purpose of this study is to develop a decision support and continuous monitoring system of the area by composing landslide hazard and risk maps. For that reason, several approaches of the weighted linear combination (WLC), a semi-quantitative hazard analysis method, were adopted in a Geographic Information Systems (GIS) environment. The results were validated using a pre-existing landslide database enriched with new landslide locations mapped through image interpretation of a processed IKONOS satellite image. The validation results showed that the WLC method coupled with remote sensing (RS) and GIS techniques can support engineering geological studies concerning landslide vulnerability of hazardous areas.     

Quantitative hazard and risk assessment for slow-moving landslides from Persistent Scatterer Interferometry

Preparation of reliable landslide hazard and risk maps is crucial for hazard mitigation and risk management. In recent years, various approaches have been developed for quantitative assessment of landslide hazard and risk. However, possibly due to the lack of new data, very few of these hazard and risk maps were updated after their first generation. In this study, aiming at an ongoing assessment, a novel approach for updating landslide hazard and risk maps based on Persistent Scatterer Interferometry (PSI) is introduced. The study was performed in the Arno River basin (central Italy) where most mass movements are slow-moving landslides which are properly within the detection precision of PSI point targets. In the Arno River basin, the preliminary hazard and risk assessment was performed by Catani et al. (Landslides 2:329–342, 2005) using datasets prior to 2002. In this study, the previous hazard and risk maps were updated using PSI point targets processed from 4 years (2003–2006) of RADARSAT images. Landslide hazard and risk maps for five temporal predictions of 2, 5, 10, 20 and 30 years were updated with the exposure of losses estimated in Euro (€). In particular, the result shows that in 30 years a potential loss of approximate €3.22 billion is expected due to these slow-moving landslides detected by PSI point targets.     

Individual and societal risk owing to landslides in the Campania region (southern Italy)

This paper deals with the estimation of both individual and societal risks owing to landslides in the Campania region (southern Italy) thanks to the availability of an extensive catalogue of historical incident data spanning from the 5^th century up to now. Individual risk is estimated by computing the landslide mortality rate. Societal risk is measured by plotting the annual frequency F of events causing N or more fatalities against the number N of fatalities (i.e. an F–N curve). The results obtained show that in Campania both individual and societal risks owing to landslides are very high when compared to similar risks of the Italian territory. Moreover, the analysis of the incident data clearly highlights the most prone areas to catastrophic events, essentially related to the occurrence of flow-like fast-moving phenomena, where the societal risk is proved to be one of the highest in Europe.     

Morphological methods and dynamic modelling in landslide hazard assessment of the Campania Apennine carbonate slope

Landslide risk of the Campanian carbonate slopes covered by pyroclastic deposits is mainly connected with the occurrence of high-velocity debris avalanches and debris flows. Analyses show that flows initiate as small translational slides in the pyroclastics. The failure process is controlled by the interaction of both natural and human-induced factors. Geomorphological settings play a decisive role in locating the source failures. Therefore, the crucial aspects in landslide hazard and risk assessment are: (a) recognise the geomorphological control factors, (b) determine parameters defining landslide intensity (velocity, volume, depth of deposit) and (c) predict landslide runout distance. An approach combining geomorphology and numerical analysis has been adopted in the work reported here. Potential future landslide intensity scenarios are simulated predicting the runout behaviour of potential instabilities by using a dynamic model previously calibrated by back-analysing observed events of similar scale and type. The selected area is a sector of the Avella Mountains having the same geomorphological environment as the 1998 Sarno landslides (Campania, Southern Italy).     

Remote sensed data for automatic detection of land-use changes due to human activity in support to landslide studies

Slope instability studies appear to recognize a number of potential superficial slide-producing agents, which may be directly detected and monitored with Earth Observation (EO) data. The main objective of this work is to use conventional EO data and automatic techniques for providing land-use change maps useful in landslide prevention. The idea is to use the detection of changes in areas already involved in landslide events as a precursory sign of variations in the equilibrium status of the slope, independently from other natural triggering events, such as rain and seismic events. Attention is focused on man-induced surface changes, such as deforestation, urban expansion and construction of artificial structures. A historical set of 20 multi-temporal Landsat TM images, covering the period 1987–2000, was analyzed using a supervised change detection technique on a test site affected by slope instability phenomena located in the Abruzzo region in Southern Italy. A change image is obtained by comparing year-specific thematic map pairs. It contains useful information not only on the place where a transition occurred, but also on the specific classes involved in the transitions between two different years. The full set of change images is used to extract class-conditional transition probabilities, to evaluate variations in specific class distribution and the total number of changed pixels in time. Four classes and their transitions were considered in the analysis: (1) arboreous land, (2) agricultural land, (3) barren land, and (4) artificial structures. The quantitative analysis of the class-joint transition probability values of some specific class-transitions that may worsen slope stability showed that in an area prone to landslides the probability of landslide re-activation or first activation is higher where changes have occurred. Although based on a limited number of known events, such a result encourages extensive experimentation of the proposed technique on better documented landslide test sites.     

FLaIR and SUSHI: two mathematical models for early warning of landslides induced by rainfall

The development of Early Warning Systems in recent years has assumed an increasingly important role in landslide risk mitigation. In this context, the main topic is the relationship between rainfall and the incidence of landslides. In this paper, we focus our attention on the analysis of mathematical models capable of simulating triggering conditions. These fall into two broad categories: hydrological models and complete models. Generally, hydrological models comprise simple empirical relationships linking antecedent precipitation to the time that the landslide occurs; the latter consist of more complex expressions that take several components into account, including specific site conditions, mechanical, hydraulic and physical soil properties, local seepage conditions, and the contribution of these to soil strength. In a review of the most important models proposed in the technical and international literature, we have outlined their most meaningful and salient aspects. In particular, the Forecasting of Landslides Induced by Rainfall (FLaIR) and the Saturated Unsaturated Simulation for Hillslope Instability (SUSHI) models, developed by the authors, are discussed. FLaIR is a hydrological model based on the identification of a mobility function dependent on landslide characteristics and antecedent rainfall, correlated to the probability of a slide occurring. SUSHI is a complete model for describing hydraulic phenomena at slope scale, incorporating Darcian saturated flow, with particular emphasis on spatial–temporal changes in subsoil pore pressure. It comprises a hydraulic module for analysing the circulation of water from rainfall infiltration in saturated and nonsaturated layers in non-stationary conditions and a geotechnical slope stability module based on Limit Equilibrium Methods. The paper also includes some examples of these models’ applications in the framework of early warning systems in Italy.