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This document describes technical concepts and terms related to landslide risk on slopes and hillsides, from a comprehensive approach. A general methodology is presented for the risk analysis and assessment according to the threat, given by the interrelation susceptibility - probability of landslide occurrence; and the vulnerability of the exposed elements, obtained from a multifactorial analysis that considers physical and social aspects. Susceptibility is obtained considering various conditioning and triggering factors of instability and the probability of event occurrence is estimated from deterministic methods. The vulnerability analysis is done considering the spatial and temporal components of the potential events, as well as the impact that these could have on the exposed elements, in terms of social and material losses. This methodology is applied to the study of an urban slope in the city of Tijuana, Mexico. [ABSTRACT FROM AUTHOR]

Abstract Landslides are a type of mass wasting and denote any downslope movement of soil and rock under the influence of gravity; as such they can represent a dangerous natural hazard process, especially in case that they affect inhabited areas or transport infrastructure. Because the occurrence of landslides is typically favoured by terrain and lithological conditions, the process is frequently concentrated in relatively small, isolated regions exhibiting suitable initial conditions of terrain instability. Extensive regional assessments of landslide activity have been used in the past to uncover common triggers and process patterns, mostly in the aftermath of large, regional disasters. By contrast, however, regional reconstructions of past landslide activity have not been realized with dendrogeomorphic techniques, and with the aim to date past landslide histories over extended time periods and with annual dating precision. This study therefore aims at disentangling landslide dynamics at the regional scale (covering ca. 600 km2) by using growth-ring records of trees that grow on active landslides. The studied area of the Hostýnsko-vsetínská hornatina Mts. (Central Europe) is well known for its high landslide activity, but has so far been lacking a detailed chronology of past events. To this end, we dated past activity on 26 landslide bodies using tree-ring series from 1322 disturbed trees to reconstruct 327 landslide reactivations during the last century. The reconstructed landslide database allowed correlations between landslide types and their frequencies or occurrence, as well as inferences between selected morphometric parameters with landslide frequency and magnitude. We also observe periods of increased landslide activity (1940s, 1960s, 1980s, and 1990s) and events of regional importance (e.g., 1961, 1985, and 1997), as well as a significant decrease in landsliding during the last two decades. Highlights • Regional reconstruction of landslides activity for Outer Western Carpathians • Tree-ring based analysis of 26 landslides • Chronologies of various landslide types • Comparison of activity with the morphometry of landslides [ABSTRACT FROM AUTHOR]

Most regional landslide warning systems utilize empirically derived rainfall thresholds that are difficult to improve without recalibration to additional landslide events. To address this limitation, we explored the use of synthetic rainfall to generate thousands of possible storm patterns and coupled them with a physics‐based hydrology and slope stability model for various antecedent soil saturation scenarios to analyze pore water pressure and factor of safety metrics. We used these metrics to generate two‐tiered alert thresholds that can be employed to assess shallow landslide potential for any given combination of storm and antecedent wetness. When applied to the San Francisco Bay region (CA, USA), the results are consistent with events that caused widespread landsliding. Our deterministic modeling approach, which accounts for plausible ranges in soil hydraulic and mechanical properties, can inform the development of the next generation of warning systems for rainfall‐induced landsliding. Plain Language Summary: Providing accurate warning in advance of rainfall‐induced landsliding can help reduce loss of life and property but requires knowledge of hillslope wetness and future rainfall conditions to forecast when widespread landsliding is likely. However, typical landslide warning systems consider only the rainfall characteristics (e.g., rainfall amount, duration, and/or intensity) that were measured during past landslide events. These are used to define a set of rainfall conditions, or a threshold, for which landsliding should be expected within a given area. When a rainfall threshold does not perform well for subsequent landsliding events, it can be difficult to diagnose the problem because hillslope wetness is not considered. We present an approach to develop landslide thresholds that accounts for both rainfall and hillslope wetness. The results are consistent with historical and recent widespread landsliding events in our study region and, more importantly, can be related to measurable properties of hillslopes. This more direct approach could revolutionize the development of the next generation of landslide warning systems. Key Points: Thresholds for rainfall‐induced landsliding of soil‐mantled hillslopes identified with physics‐based hydrologic and slope stability modelingLibrary of modeled infiltration events based on variations in rainfall and antecedent soil saturation facilitates timely hazard assessmentDeterministic modeling approaches that account for parameter variability can inform the next generation of landslide warning systems [ABSTRACT FROM AUTHOR]

In this work residents' social vulnerability and buildings' physical vulnerability of the Loures municipality (Portugal) were combined to locate the areas where the vulnerability is the highest, and to analyse the landslide risk. The social vulnerability of Loures was assessed using the Geographic Basis for Information Reference (BGRI) terrain units by combining sensitivity and lack of resilience based on the population and housing Census 2011 data. The physical vulnerability was assessed in a previous study based on an inquiry of a pool of European landslide experts and a sub-pool of landslide experts who know the study area. A matrix approach was used to cross the classes of the social and physical vulnerabilities. Finally, the landslide risk was analysed for each terrain unit considering the combined vulnerability, the buildings' economic value and the landslide susceptibility for a specific landslide magnitude (3-metre-deep rotational slide). Results show that 0.9% of the population reside in the area of the municipality where 75% of the future landslide should occur, and 0.8% of the buildings of the municipality--which represent a value of EUR 146,170,000--are also located in this dangerous area. This approach is reproducible: the risk analysis can be applied for another magnitude scenario in Loures, and the combined vulnerability can be assessed in any Portuguese municipality thanks to the availability of the data. [ABSTRACT FROM AUTHOR]

A massive landslide was triggered on 19 May 2017 at Vishnuprayag near Joshimath, Uttarakhand, India. The landslide blocked the Rishikesh-Badrinath highway and halted traffic for about 24 h till the debris was removed and the road reopened. The Hathi Pahar hill in Vishnuprayag has been a landslide-prone zone because of the presence of loose boulders and large rock blocks on very steep slopes. The site was visited immediately after the landslide and a rapid field assessment of slope stability was carried out. The stability analysis was performed with limited geological and geotechnical data collected from field and laboratory. Based on the two-dimensional finite element analysis, it was inferred that the slope is marginally stable under static load, but fails under seismic loading. The slope could fail in future due to triggering factors such as heavy rainfall, earthquake and anthropogenic activities. This communication presents field observations and the subsequent stability analysis along with possible suggestive control measures. [ABSTRACT FROM AUTHOR]

This study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data-scarce environments. In total, 418 landslide inventories and 18 landslide conditioning factors were analyzed. Multicollinearity and factor optimization were investigated before data modeling, and two experiments were then conducted. In each experiment, five susceptibility maps were produced based on support vector machine (SVM), random forest (RF), weight-of-evidence (WoE), ridge regression (Rid_R), and robust regression (RR) models. The highest accuracy ( AUC = 0.85) was achieved with the SVM model when either the full or limited landslide inventories were used. Furthermore, the RF and WoE models were severely affected when less landslide samples were used for training. The other models were affected slightly when the training samples were limited. [ABSTRACT FROM AUTHOR]

Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selection effects on the LSM. Thus, this study assesses the training landslides random selection effects on support vector machine (SVM) accuracy, logistic regression (LR) and artificial neural networks (ANN) models for LSM in a catchment at the Dodangeh watershed, Mazandaran province, Iran. A 160 landslide locations inventory was collected by Geological Survey of Iran for this investigation. Different methods were implemented to define the landslide locations, such as inventory reports, satellite images and field survey. Moreover, 14 landslide conditioning factors were considered in the analysis of landslide susceptibility. These factors include curvature, plan curvature, profile curvature, altitude, slope angle, slope aspect, distance to faults, distance to stream, topographic wetness index, stream power index, terrain roughness index, sediment transport index, lithology and land use. The results show that the random landslide training data selection affected the parameter estimations of the SVM, LR and ANN algorithms. The results also show that the training samples selection had an effect on the accuracy of the susceptibility model because landslide conditioning factors vary according to the geographic locations in the study area. The LR model was found to be less sensitive than the SVM and ANN models to the training samples selection. Validation results showed that SVM and LR models outperformed the ANN model for all scenarios. The average overall accuracy of LR, SVM and ANN models are 81.42%, 79.82% and 70.2%, respectively. [ABSTRACT FROM AUTHOR]

Customary methods for landslide detection are labor demanding, time consuming and costly. Moreover, it becomes a real challenge to map event triggered landslides using customary techniques. Various automatic and semi-automatic techniques have been proposed for landslide detection. These techniques require extensive technical knowledge and familiarity of the selected study area for visual interpretation, suitable sampling selection, manual parameterization and the trial and error approach for selection of thresholds which makes the process irreproducible. In this context, the purpose of this study is to introduce and investigate the applicability of an automatic technique of Cosi-Corr (Co-registration of Optically Sensed Images and Correlation) for landslide identification on regional scale using high resolution orthorectified worldwies 2 images. Unlike, conventional pixel based semi-automatic methods which depends on spectral properties of pixels, this method is based on pixels shift. The correlation process was performed by using the Cosi-Corr software. The ground displacement field measured from the correlation indicates high displacement values for landslides triggered by 2010 Haiti earthquake. The method automatically identified more than 73% of co-seismic landslides at the threshold value of 3.75. The adopted procedure proposes a quick and economic way for automatic detection of coseismic landslides on regional scale if suitable pre- and post-event satellite data is available. One limitation of this method is that it does not show any unique behavioral characteristics for different types of landslides so that they could be easily distinguished or classified. [ABSTRACT FROM AUTHOR]

This paper deals with a quantitative risk analysis, performed using the rockfall risk management (RO.MA.) method, for a road affected by rockfalls. This approach allows evaluating the rockfall risk, also considering existing protection devices. Rockfall hazard and risk were assessed for an important and very busy road stretch linking Positano to Amalfi in the Campania region of southern Italy. An estimate of the rockfall return periods for assigned volume classes was obtained using the magnitude-frequency curves (MFCs) computed through the analysis of a rockfall inventory covering a time span from 1996 to 2008. For rockfall volumes of 0.1, 1.0, and 10 m, using a 2D trajectory simulating code, the involved kinetic energies and run-out distances of boulders that may hit the road were calculated. The risk, expressed as the annual probability of a fatal accident for the three rockfall hazard scenarios has been evaluated both without and with protection devices, respectively. The total final risk is given by the sum of partial risks related to the three scenarios. The analysis showed that regardless of whether there are any rockfall protection devices, the total risk remains almost constant. This is due to the wide spread of slopes protected with inadequate restraining metallic nets characterized by decreasing catching capacities, as possible rockfall magnitude increases. The individual risk is not acceptable, and some actions are requested in order to lower it. [ABSTRACT FROM AUTHOR]

The 12 May 2008 Wenchuan earthquake in China triggered numerous landslides. Loose landslide materials can easily evolve into deadly debris flows during wet seasons. During the period from 2008 to 2011, three separate large-scale debris flows occurred in the Pubugou Ravine near the epicentre of the earthquake that were among the largest repeated debris flows ever reported. Approximately 1.76 × 106 m3 of sediment was deposited during these three events. This paper aims to ( i) analyze the movements of solid materials during the repeated debris flows, ( ii) discuss the evolution of the initiation mechanisms of these debris flows, and ( iii) evaluate the changing depositional morphology of the debris flow fans and examine the particle sizes of the debris flow materials. To achieve the above research objectives, timely field investigations were undertaken in the past 5 years after each of these debris flow events. Satellite images were used to delineate the boundaries of the initiation areas, the transportation channels, and the deposition zones of these debris flows. With the occurrence of the repeated debris flows, the hill slope deposits gradually evolved into channel deposits and the solid materials in the channels moved toward the gully mouth. Hence, channelized flows gradually became dominant. The debris fan materials of the repeated debris flows became coarser and coarser over time. The three debris flows were all characterized by coarse boulder fronts. [ABSTRACT FROM AUTHOR]

The occurrence of landslides in Moa poses a serious threat to the industry, communities, socio-economic activities and the environment. The objective of this research is to assess and map the risks generated by the occurrence of landslides in the area by applying the Geographic Information Systems (GIS). For a methodological guidance, the guideline dated 2012 prepared by the National Risk Management Group was used to conduct the landslide hazard, vulnerability, risk analysis on the ground. As a result, this work produced a map indicating the overall landslide dangerousness in Moa on a 1:100 000 scale. This map is one more risk management and mitigation tool in the territorial organization. [ABSTRACT FROM AUTHOR]

Landslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion. Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the ‘black box’ of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency. With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes. [Copyright &y& Elsevier]

The paper focuses on the assessment of landslide hazard and risk along or across the Trans Adriatic Pipeline (TAP) natural gas pipeline project in Albania. TAP is a natural gas pipeline that will transport gas from the Caspian Sea to Europe, crossing Northern Greece and Southern Albania. It has long been recognised that landsliding is a major factor for TAP's pipeline route selection in mountainous regions, especially the challenging area of central Albania. Experience from similar major pipelines has shown that hazard avoidance is generally the most cost- and time-efficient strategy to minimise the landslide risk since geohazard-related decision-making is usually risk-based. For landslides, the risk profile is expected to be dominated by the upslope expansion of existing landslides, resulting in a loss of ridge crest (where the Right of Way (RoW) is usually located), possibly leading to pipeline rupture. However, it is still possible that new landslides could develop under static and/or seismic conditions, especially on steep ridge flanks along the route. An expert determination approach was adopted to define a consensus for the estimate of the risk (i.e., chance of rupture) for the pipeline at eighty-two (82) identified landslide sites in Albania, to identify "hot spots" along the route, where risk-reduction measures could be prioritised. Ten landslides were characterised as "High Risk", fifteen as "Medium Risk" and nineteen as "Low Risk". Following this risk assessment, two large re-routings, as well as several local re-routings, were considered. Further investigation was required to identify the site-specific geotechnical conditions and probable remedial measures in cases where landslides could not be avoided by rerouting. [ABSTRACT FROM AUTHOR]