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Geologically, La Paz City is located in an unstable area. During the history of La Paz city, many landslides have destroyed houses and valuable infrastructures. In the last decades, time series Interferometric Synthetic Aperture Radar (InSAR) technologies have demonstrated a great capacity for detecting slow ground displacement, achieving an accuracy of millimetre-level. In order to have a better landslide monitoring of La Paz city, in this study, the Sentinel-1 SAR images have been processed by Persistent Scatterer Interferometry (PSI) and the Small Baseline Subset (SBAS) techniques. The time span of the datasets is from March 2015 to August 2016. Both ascending and descending Synthetic Aperture Radar (SAR) images have been processed to obtain the line of sight (LOS) ground velocity, and then the results have been combined to estimate the up-down and east-west displacement. Several active movement areas have been identified, showing a surface velocity up to 158 mm year−1 westward and 49 mm year−1 eastward. Furthermore, two important findings have been discovered. First, the InSAR result has detected movement in Auquisamaa hill before the area collapsed (15 February 2017), where five houses are buried. Second, the InSAR result has identified that there are still some unstable sites in Callapa area, where a mega-landslide has destroyed more than a thousand of houses in February 2011. In conclusion, we have verified that the InSAR technology could be a very useful tool to help La Paz public institutions for a better management of urban planning, landslide areas delimitation and landslide risk mitigation. [ABSTRACT FROM AUTHOR]

Landslides are the most dangerous and common natural phenomena causing higher number of victims and damages in Piemonte (north-western Italy). An integrated statistical approach to identify the main predisposing and triggering factor causing shallow landslides occurrence based on a large dataset of historical rainfall-induced shallow landslides and a long-time series of rainfall data is presented. Historical shallow landslide events were compared with territorial and rainfall characteristics. Exploratory Spatial Data Analysis (ESDA) has been performed in order to explore the spatial distributions of landslides with the environmental quantitative variables (morphometry and rainfall) to identify possible patterns of spatial autocorrelation. ESDA showed strong autocorrelation of landslide locations with rainfall variables, while resulting in low values for morphometric parameters at the investigated scale. Moreover, by intersecting landslides distribution with categorical land thematic parameters (land thematic maps) allowed to identify areas with different landslide density occurrence. Resulting susceptibility-related areas were used to improve the landslides regional Early Warning System of Piemonte based on refined empirical intensity vs duration (I-D) rainfall thresholds. [ABSTRACT FROM AUTHOR]

We propose a simple method to estimate the surface displacement of earth slides. It is based on the assumptions that earth slides move by sliding along a discrete basal-slip surface and extensional structures, which commonly characterize their depletion zone, completely accommodate the occurred displacement. The proposed method is based on the reconstruction of the cross-sectional geometry of structures crossed by an arbitrary chosen longitudinal profile, aligned with the direction of the movement. Structure geometry reconstruction is completed using high-precision GPS survey and the reconstructed geometry is then used as basis to measure horizontal and vertical components of the displacement accommodated by each single extensional structure. Total horizontal and vertical earth-slide displacements are calculated as the sum of displacements accumulated at each single structure. We test the method at the Summonte earth slide in southern Italy using real-time kinematic GPS field mapping. Results from our estimation were validated considering a single displacement vector derived from the direct and indirect measurement of the position of an isolated tree located below the extensional zone of the slide. [ABSTRACT FROM AUTHOR]

The main aim of this study is the description and the analysis of the monitoring strategies implemented within local landslide early warning systems (Lo-LEWS) operational all around the world. Relevant information on 29 Lo-LEWS have been retrieved from peer-reviewed articles published in scientific journals and proceedings of technical conferences, books, reports, and institutional web pages. The first part of the paper describes the characteristics of these early warning systems considering their different components. The main characteristics of each system are summarized using tables with the aim of providing easily accessible information for technicians, experts, and stakeholders involved in the design and operation of Lo-LEWSs. The second part of the paper describes the monitoring networks adopted within the considered systems. Monitoring strategies are classified in terms of monitored activities and methods detailing the parameters and instruments adopted. The latter are classified as a function of the type of landslide being monitored. The discussion focuses on issues relevant for early warning, including appropriateness of the measurements, redundancy of monitoring methods, data analysis, and performance. Moreover, a description of the most used monitoring parameters and instruments for issuing warnings is presented. [ABSTRACT FROM AUTHOR]

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]

To assess the risk of slope failure, this study employs a rigorous method that is referred to as the random finite difference method (RFDM). The RFDM is capable of considering the spatial variability of soil properties subject to different auto-correlation structures. Comparisons with the collected data are made with respect to two idealized slopes, and a parametric analysis is presented. The results demonstrate that the spatial auto-correlation structures significantly affect the slope failure risk. Depending on the rotated angle, the rotated anisotropy auto-correlation structure shows a dual effect on the reliability of the slope compared to a transverse anisotropy case. [ABSTRACT FROM AUTHOR]

Landslide is one of the devastating natural phenomenon that threatens human life and property. Every year a number of persons lost their lives due to the landslides. Therefore, a better understanding and characterization of landslide is very essential for adopting mitigation strategies to contain the adversities of this natural hazard. Information on landslides from different climatic setup are very essential for better understanding of the influence of weathering, rainfall, or topography on landslide generation. Weathering is one of the important causative factor for landslide generation in the moderate topography or inactive mountainous terrain. The Western Ghats including the Deccan Traps, an inactive mountain range, receives torrential rainfall. Intense rainfall in these areas enhances the weathering processes and fabricates thick soil covers. Mahabaleshwar area, Maharashtra was chosen as a case study, where high elevated part is covered by lateritic layer and each lava flow unit is separated by a thin weathered bed of red bole. The area experiences series of landslides during the summer monsoon months. Mainly two types of landslides have been identified in the area confined with the red bole bed and powdery lateritic soil. The first type of landslides occur at higher elevations (≥1200m) where horizontal beds of permeable laterites underlined by impermeable thick basalt beds. The rain water infiltrates down and spread laterally within the permeable lateritic beds. It finally spouts at lower plateau elevations and triggers mainly debris flows. The other category of landslides occurs where the weathered red bole bed separates two successive lava flows. The percolating water from the secondary porosities (joints and inter connected vugs) comes out from the contact zones of basalt and red bole bed in the form of seepages. It erodes the red bole bed and as a result the overlying masses hang and consequently lead to rock fall. The Chemical Index of Alteration (CIA) of the representative samples from landslide locations indicates significant weathering. The CIA values for the fine lateritic soil are up to 98% whereas for the red bole bed it varies from 77 to 85%. This suggests a high chemical weathering and higher erodibility. The association of active landslide locations with the red bole bed and fine lateritic soil suggests a close relation between weathering and landslide occurrences in the area. [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]

Yang, J., 2018. Landslide damage from extreme rainstorm geological accumulation layers within plain river basins. In: Ashraf, M.A. and Chowdhury, A.J.K. (eds.), Coastal Ecosystem Responses to Human and Climatic Changes throughout Asia. To provide the basis of an early warning and detection for landslide disasters and to provide decision support for local governments in disaster prevention and mitigation, this research studied landslide damage assessment from the geological accumulation layer in a plain river basin under conditions of an extreme rainstorm. Based on an analysis of the relationship between landslide geology and rainfall and a damage model of landslides under conditions of extreme rainfall, the landslide damage assessment described in this article used the SINMAP model. The layer of geological accumulation in the Wenchuan–Diexi River section in the upper reaches of the Minjiang River was the study area. Spatial distribution characteristics and the main factors inducing a landslide disaster were studied, and a danger-evaluation model for landslides in that region was established for landslide assessment research and for applying that research. Based on the SINMAP model, the effects of different extreme rainstorm events on the stability of regional slopes were analyzed. The results of a stability evaluation for landslides show that the area has an unstable zone of 4339.8 km2, which accounts for 64.49% of the total area. The unstable area in this evaluation was basically consistent with the distribution of an existing landslide, which shows that the model can adequately evaluate slope stability and landslide potential from the layer of geological accumulation in this area. [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]

Many landslides were triggered by heavy rainfall from 29 June to 1 July 2017 in Ningxiang County, Hunan Province, China. A field investigation into one of the landslides, known as the Wangjiawan landslide, was undertaken on July 3, 2017, to understand the landslide mechanisms and the factors that triggered the event. The landslide is a translational and rotational slide that degraded downslope to an earth flow. It occurred on a steeply dipping mud-rich slate intercalation. Field investigation shows that the landslide had a movement rate of more than 25 m/s and had been triggered by up to 338 mm of continuous rainfall over 2 days. The landslide was fast-moving because it occurred on a steep slope and showed a rapid reduction in shear strength. The landslide resulted in nine fatalities and 19 injuries, most during initial rescue efforts. To mitigate a possible secondary landslide disaster, later emergency measures including evacuation of the survivors, setting up warning signs, and covering landslide cracks with plastic sheeting were adopted. [ABSTRACT FROM AUTHOR]

Recent investigations have sought to understand the spatial-temporal distribution of landslides in Teziutlán, Puebla, a municipality historically affected by landslides. The latest initiative, under the umbrella of the ICL-IPL Project “Landslide disaster risk communication in mountain areas,” was the publication of a book of Atlas type comprising a collection of 142 maps and their corresponding explanatory texts that included a context analysis of landslide disaster risk drivers at various scales, from regional to local. This paper aims to recognise and address the necessity to further enhance the guiding principle of the Sendai Framework for Disaster Risk Reduction to focus on the understanding of disaster risk drivers at local level, for the determination of measures to reduce disaster risk. We present an initial contribution to promote landslide disaster risk awareness in the urban area of Teziutlán by providing to the community direct access to maps of landslide disaster risk at local scale; this is a first step towards the establishment of a robust strategy to communicate landslide risk in the long term. Effective implementation calls for decreasing vulnerability and exposure. Beyond contexts of vulnerability reflected by social, economic, cultural, political, and institutional conditions, it may be difficult to picture the spatial interactions of exposure of communities, assets, and the environment because the means of analysing spatial relationships between society and nature are not commonly available in mountain areas. Therefore, for people to better understand risk, maps of landslide susceptibility and risk exposure present a good way for the inhabitants to familiarise themselves with the spatial context of the dynamics in which they are immersed. [ABSTRACT FROM AUTHOR]

Empirical rainfall thresholds are commonly used to forecast landslide occurrence in wide areas. Thresholds are affected by several uncertainties related to the rainfall and the landslide information accuracy, the reconstruction of the rainfall responsible for the failure, and the method to calculate the thresholds. This limits the use of the thresholds in landslide early warning systems. To face the problem, we developed a comprehensive tool, CTRL–T ( C alculation of T hresholds for R ainfall-induced L andslides− T ool) that automatically and objectively reconstructs rainfall events and the triggering conditions responsible for the failure, and calculates rainfall thresholds at different exceedance probabilities. CTRL−T uses a set of adjustable parameters to account for different morphological and climatic settings. We tested CTRL−T in Liguria region (Italy), which is highly prone to landslides. We expect CTRL−T has an impact on the definition of rainfall thresholds in Italy, and elsewhere, and on the reduction of the risk posed by rainfall-induced landslides. [ABSTRACT FROM AUTHOR]

The article focuses on the Taroko National Park in Taiwan where the wet slopes and earthquakes have made landslides common. Niels Hovius, a geomorphologist and his colleagues have made it a landscape dynamics observatory by installing various instruments. It is noted that monitoring landslides will help the researchers understand what triggers them and how landscapes recover. Landslide researcher Robert Emberson has found that landslides in Taiwan are sources of Carbon dioxide.

This study deals with the numerical modelling of large deep-seated instability processes affecting the Cinque Torri Group (Dolomites, Italy), which is a UNESCO World heritage site. The aim is to evaluate the role of intrinsic causal factors and to assess the failure mechanism proposed in previous investigations. The geological model is based on topographic, geological and geomechanical surveys, complemented with mineralogical, physical and geotechnical lab analyses for parameters determination. The numerical simulations have been carried out using a Distinct Element Method code on conceptual and site-specific slope models. A series of parametric analyses have been performed to characterize the role of the different predisposing factors potentially related with the ongoing rock spreading: i) load of the rocky pinnacles; ii) lithology, stratigraphy and attitude of the geological units; iii) discontinuity sets in the rock mass; iv) degradation of the mechanical properties. The results of this study suggest that the shear zone initiation is controlled by stress concentration due to the loading of the dolomitic pinnacles, whereas its shape appears to be structurally controlled by the dip-slope attitude of bedding in clay-rich mudstones. The interpretation of the modelling results has provided a better understanding of the ongoing deformation process, which can help in targeting effective and low-impact landslide risk mitigation strategies in this iconic landscape. [ABSTRACT FROM AUTHOR]

The development of unmanned aerial vehicle photogrammetry over the last decade has allowed terrain that is very difficult for humans to access to be captured at very high spatial and temporal resolutions. This paper deals with the application of this technique to the study of extreme topography in a near-vertical road cut-slope. Three photogrammetric projects were carried out: one derived from images taken with the camera oriented horizontally, one derived from images taken with the camera tilted at 45°, and one derived from both sets of images. Point clouds and orthophotos were generated for each of these projects. The best accuracies were achieved by the photogrammetric products derived from the combined images set, which had RMSE equal to 0.053 m, 0.070 m and 0.061 m in X, Y and Z direction, respectively. A software program was developed to generate contour lines and cross-sections derived from the point cloud, which was able to represent all terrain geometric characteristics, such as several Z coordinates for a given planimetric (X, Y) point. Furthermore, comparing the contour lines and cross-sections generated from the point cloud using the program developed in this project to those generated from the digital surface model showed that the former are capable of representing geometric terrain characteristics that the latter cannot. [ABSTRACT FROM AUTHOR]

Landslides that occur due to the rapid motion of a rock-mass are a primary risk in mountainous terrains and are a danger to human life and civil infrastructure. The application of geotechnical engineering methodologies for remedial purposes is to assess unpredictable behavior and the stability of the slope, and for analysis and design. The aim of the study is to quantify the global factor of safety (FOS) and describe a correlative and comparative assessment of the conventional Limit Equilibrium Model as compared with the advanced Numerical Model for the rock slopes of Amiya, Nainital, Uttarakhand in India utilizing Mohr-Coulomb failure criterion. The rock-mass characteristics were determined as a result of an estimation of the physio-mechanical properties of rock and debris from collected field samples with the help of the joint weakening coefficient for limit equilibrium (LE) and the numerical solution. Global FOS estimated by means of stability analysis procedures, such as Swedish slip circle, Ordinary method of slices, Modified Bishop, Janbu method, Finite difference static analysis, Finite element static, and Finite difference dynamic analysis, was found to be 0.65, 1.34, 1.38, 1.29, 1.57, 1.144, and 0.84, respectively. The results helped to deduce that the slope remains substantially stable and failure may only occur in the case of a down slope movement of rock debris (clastic mass of rocks) with a small local/global tremor. Combination of the LE technique and numerical approach (hybrid approach) has been found to be a better method for critical slip surface and FOS determination. [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]

Large wood (LW) plays a key role in physical, chemical, environmental, and biological processes in most natural and seminatural streams. However, it is also a source of hydraulic hazard in anthropised territories. Recruitment from fluvial processes has been the subject of many studies, whereas less attention has been given to hillslope recruitment, which is linked to episodic and spatially distributed events and requires a reliable and accurate slope stability model and a hillslope-channel transfer model. The purpose of this study is to develop an innovative LW hillslope-recruitment estimation approach that combines forest stand characteristics in a spatially distributed form, a probabilistic multidimensional slope stability model able to include the reinforcement exerted by roots, and a hillslope-channel transfer procedure. The approach was tested on a small mountain headwater catchment in the eastern Italian Alps that is prone to shallow landslide and debris flow phenomena. The slope stability model (that had not been calibrated) provided accurate performances, in terms of unstable areas identification according to the landslide inventory (AUC = 0.832) and of LW volume estimation in comparison with LW volume produced by inventoried landslides (7702 m 3 corresponding to a recurrence time of about 30 years in the susceptibility curve). The results showed that most LW potentially mobilised by landslides does not reach the channel network (only about 16%), in agreement with the few data reported by other studies, as well as the data normalized for unit length of channel and unit length of channel per year (0–116 m 3 /km and 0–4 m 3 /km y −1 ). This study represents an important contribution to LW research. A rigorous and site-specific estimation of LW hillslope recruitment should, in fact, be an integral part of more general studies on LW dynamics, for forest planning and management, and positioning in-channel wood retention structures. [ABSTRACT FROM AUTHOR]

This paper proposes an approach for landslide inventory mapping considering actual conditions in Indonesia. No satisfactory landslide database exists. What exists is inadequate, focusing, on data response, rather than on pre-disaster preparedness and planning. The humid tropical climate also leads a rapid vegetation growth so past landslides signatures are covered by vegetation or dismantled by erosion process. Generating landslide inventory using standard techniques still seems difficult. A catalog of disasters from local government (village level) was used as a basis of participatory landslide inventory mapping. Eyewitnesses or landslide disaster victims were asked to participate in the reconstruction of past landslides. Field investigation focusing on active participation from communities with the use of an innovative technology was used to verify the landslide events recorded in the disaster catalog. Statistical analysis was also used to obtain the necessary relationships between geometric measurements, including the height of the slope and length of run out, area and volume of displaced materials, the probability distributions of landslide area and volume, and mobilization rate. The result shows that run out distance is proportional to the height of the slope. The frequency distribution calculated by using non-cumulative distribution empirically exhibits a power law (fractal statistic) even though rollover can also be found in the dataset. This cannot be the result of the censoring effect or incompleteness of the data because the landslide inventory dataset can be classified as having complete data or nearly complete data. The so-called participatory landslide inventory mapping method is expected to solve the difficulties of landslide inventory mapping and can be applied to support pre-disaster planning and preparedness action to reduce the landslide disaster risk in Indonesia. It may also supplement the usually incomplete data in a typical landslide inventory. [ABSTRACT FROM AUTHOR]

Landslides triggered by rainfall are a major multiple geological hazard on Qin-ba Mountain. Debris landslides in the shallow layer make up a large proportion of all landslides. A flume experiment was conducted to successfully initiate shallow debris landslides using artificial rainfall in Zhouzhi County, Qin-ba Mountain. The results confirmed a strong correlation between the deformation of the slope and pore-water pressure and moisture content. Slope deformation and failure were observed, and a possible mechanism was interpreted based on the experimental results. The primary effects of rainfall on shallow debris landslides on Qin-ba Mountain are the generation of a seepage force and a decrease in the effective stress of the sliding surface as a result of increasing pore-water pressure. The effect of rainfall on the shear strength parameters is inconspicuous, which might be attributed to the relatively high saturation of debris soils under natural conditions. The failure type in Test 1 is considered to be a progressive failure, which is a typical failure mode for homogeneous shallow debris slopes on Qin-ba Mountain, particularly for slopes exposed to artificial excavation. The deformation in Test 2 with higher density, merely taking the form of surface erosion, usually occurs in the regions with the least artificial disturbance. The two deformation types can be primarily attributed to differences in the soil density; the higher density reflected the smaller number and size of inside pores and led to lower soil permeability, which further influenced the distribution of the pore-water pressure, direction of seepage force, and slope deformation. Therefore, higher soil density changed by compaction is beneficial for the stability of shallow debris slopes on Qin-ba Mountain, even with high pore-water pressure. In subsequent work, a series of experiments with various densities should be conducted to explore the dividing point between the two deformation modes, and in addition, tests with larger slope gradients should also be considered. [ABSTRACT FROM AUTHOR]

ABSTRACT: Resistivity monitoring surveys are used to detect temporal changes in the subsurface using repeated measurements over the same site. The positions of the electrodes are typically measured at the start of the survey program and possibly at occasional later times. In areas with unstable ground, such as landslide‐prone slopes, the positions of the electrodes can be displaced by ground movements. If this occurs at times when the positions of the electrodes are not directly measured, they have to be estimated. This can be done by interpolation or, as in recent developments, from the resistivity data using new inverse methods. The smoothness‐constrained least squares optimisation method can be modified to include the electrode positions as additional unknown parameters. The Jacobian matrices with the sensitivity of the apparent resistivity measurements to changes in the electrode positions are then required by the optimisation method. In this paper, a fast adjoint‐equation method is used to calculate the Jacobian matrices required by the least squares method to reduce the calculation time. In areas with large near‐surface resistivity contrasts, the inversion routine sometimes cannot accurately distinguish between electrode displacements and subsurface resistivity variations. To overcome this problem, the model for the initial time‐lapse dataset (with accurately known electrode positions) is used as the starting model for the inversion of the later‐time dataset. This greatly improves the accuracy of the estimated electrode positions compared to the use of a homogeneous half‐space starting model. In areas where the movement of the electrodes is expected to occur in a fixed direction, the method of transformations can be used to include this information as an additional constraint in the optimisation routine. [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]

The paper deals with the use of thermography to assess landslide risk. Landslide is a natural process which affects soil. In specific conditions, it can even become cause of death and damages to buildings and structures. Due to climate changes, landslide events have increased in the last years. Sensor networks are today widely used to monitor landslide triggering events. Main problems concern the development costs of such networks, so today attention is principally focused on the use of measurement systems which allow to monitor wide zones at distance. Recently researchers are considering the use of infrared thermography as a promising tool for monitoring landslide process. The paper aims to describe the current potentialities of thermography and its limitations. Several issues and open problems are still to be faced before considering such technique as an effective monitoring tool. For this reason, the author reports the results of a measurement campaign to prove the strengths and weakness of the methodology. Relevant aspects concerning the limits of this measurement technique are described in the following to provide suggestions to users and researchers working in this field. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to establish a data-driven approach and assess its potential for shallow landslide susceptibility mapping of the Shennongjia Forestry District, China. For the data processing, Fisher segmenting was used for the classification of topographical factors (gradient, relief amplitude, plan curvature, and normalized difference vegetation index) and the improved Otsu method was used to determine the buffer length thresholds of the locational factors (proximity to roads, rivers and faults). The computations show that these two objective methods help to avoid the uncertainty caused by the subjective judgments and the obtained thresholds are more consistent with actual conditions. Considering the different data types, the locational and topographical factors were evaluated by fuzzy comprehensive evaluation while the geological factors were evaluated by frequency index, and then the three separate evaluations were combined using radar chart analysis. The validation result shows that the susceptibility map based on a data-driven approach has a high accuracy of prediction and this approach will be salutary for risk mitigation and land-use management in mountainous regions. [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]

Landslides and other geological disasters occur frequently and often cause high financial and humanitarian cost. The real-time, early-warning monitoring of landslides has important significance in reducing casualties and property losses. In this paper, by taking the high initial precision and high sensitivity advantage of FBG, an FBG strain sensor is designed combining FBGs with inclinometer. The sensor was regarded as a cantilever beam with one end fixed. According to the anisotropic material properties of the inclinometer, a theoretical formula between the FBG wavelength and the deflection of the sensor was established using the elastic mechanics principle. Accuracy of the formula established had been verified through laboratory calibration testing and model slope monitoring experiments. The displacement of landslide could be calculated by the established theoretical formula using the changing values of FBG central wavelength obtained by the demodulation instrument remotely. Results showed that the maximum error at different heights was 9.09%; the average of the maximum error was 6.35%, and its corresponding variance was 2.12; the minimum error was 4.18%; the average of the minimum error was 5.99%, and its corresponding variance was 0.50. The maximum error of the theoretical and the measured displacement decrease gradually, and the variance of the error also decreases gradually. This indicates that the theoretical results are more and more reliable. It also shows that the sensor and the theoretical formula established in this paper can be used for remote, real-time, high precision and early warning monitoring of the slope. [ABSTRACT FROM AUTHOR]

Seismically-induced landslides can be detrimental to urban communities, often resulting in significant damage and repair costs, blockage of lifeline connection routes and utilities, environmental impacts, and potential for loss of life. Consistent, reliable hazard maps can assist agencies to efficiently allocate limited resources to prepare for these events. This paper presents methodology for evaluating and mapping seismically-induced landslide hazards across a large area utilizing performance-based design strategies. This approach scales site-specific seismic hazard curve analysis techniques to a regional scale evaluation by combining generally available data, including: previous landslide inventories, lidar and photogrammetric topographic data, geologic mapping, NEHRP site classifications based on shear wave velocity (VS30) measurements, and seismic hazard curves for the analysis. These maps can be combined with maps generated for other hazards (e.g., liquefaction) for a fully probabilistic, multi-hazard evaluation and risk assessment. To demonstrate the methodology, a series of landslide hazard maps showing the probabilities of exceeding different thresholds of movement (e.g., 0.1, 0.3, and 1.0 m) were generated for western Oregon. The study area contains weak, wet soils that experience land sliding regularly even without significant seismic activity. The maps show reasonable agreement with landslide inventory and susceptibility maps. [ABSTRACT FROM AUTHOR]

Despite the support of technological improvements in hazard monitoring and management, the aspect of dissemination of scientific data is still underestimated. Hazard monitoring systems are usually organized in complex networks, composed of automatized procedures in order to capture, pre-process, elaborate, transfer the monitoring result data and to generate warnings. However, a well-organized communication strategy leads to success in hazard management, especially concerning emergency conditions. In this paper, we present an approach for monitoring results dissemination in the form of single-page informative bulletin, composed of synthetic information dedicated to non-expert receivers. We developed an automatic methodology for fast and efficient data analysis and proper elaboration and dissemination, and we integrated all these elements into an algorithm for automatic bulletin generation. Our purpose was to construct a configurable tool that could be easily adapted to the hazard conditions under study. Afterwards, we applied the developed algorithm to landslide monitoring data-set. We validated the proposed approach by verifying the consistency of the model. Our methodology shows how to integrate a variety of information relative to landslide evolution, and it can be a convenient support for the management of natural hazards especially during critical situations. [ABSTRACT FROM AUTHOR]

This study attempts to compare popular statistical methods (linear, logarithmic, quadratic, power and exponential functions) with machine learning methods (multi-layer perceptron (MLP), radial base function (RBF), adaptive neural-based fuzzy inference system (ANFIS) and support vector machine (SVM)) for simulating the volume of landslides based on their surface area (VL ~ AL) in the Kurdistan province, Iran. Performances of the models were validated using some commonly error functions including the Adjusted R 2 , F-test and AIC (Akaike Information Criteria). The results showed that the power model demonstrates the best performance compared to other statistical methods whereas the ANFIS model outperforms other machine learning approaches. Furthermore, the comparative results showed that machine learning methods indicate better performances than simple statistical methods for simulating the volume of landslides in the study area. In practice, the outputs of this research can help managers and investigators decrease the cost of field surveys and measurements of volumes of landslides in landslide hazard management projects. [ABSTRACT FROM AUTHOR]

Complete landslide inventories are rarely available. The objectives of this study were to (i) elaborate the influence of incomplete landslide inventories on statistical landslide susceptibility models and to (ii) propose suitable modelling strategies that can reduce the effects of inventory-based incompleteness. In this context, we examined whether the application of a novel statistical approach, namely mixed-effects models, enables predictions that are less influenced by such inventory-based errors. The study was conducted for (i) an area located in eastern Austria and (ii) a synthetically generated data set. The applied methodology consisted of a simulation of two different inventory-based biases and an in-depth evaluation of subsequent modelling results. Inventory-based errors were simulated by gradually removing landslide data within forests and selected municipalities. The resulting differently biased inventories were introduced into logistic regression models while we considered the effects of including or excluding predictors that are directly related to the respective inventory-based bias. Mixed-effects logistic regression was used to account for variation that was due to an inventory-based incompleteness. The results show that most erroneous predictions, but highest predictive performances, were obtained from models generated with highly incomplete inventories and predictors that were able to directly describe the respective incompleteness. An exclusion of such bias-describing predictors led to systematically confounded relationships. The application of mixed-effects models proved valuable to produce predictions that were least affected by inventory-based errors. This paper highlights that the degree of inventory-based incompleteness is only one of several aspects that determine how an inventory-based bias may propagate into the final results. We propose a four-step procedure to deal with incomplete inventories in the context of statistical landslide susceptibility modelling. [ABSTRACT FROM AUTHOR]

The ANNEX to the 2017 Ljubljana Declaration on Landslide Risk Reduction described in the 'Preface' section of this issue is the list of participants (by organizations) in the Fourth World Landslide Forum. In this article, emphasis is put on this list of organizations as they are expected to be the key components for the Fifth World Landslide Forum 2020 in Kyoto, Japan. The participants in the Fourth World Landslide Forum 2017 adopted the 2017 Ljubljana Declaration on Landslide Risk Reduction. They further endorsed the concept of the Kyoto 2020 Commitment for Global Promotion of Understanding and Reducing Landslide Disaster Risk. The commitment aims to establish a long-term, wider, and stronger network after WLF5 2020 among three membership categories, namely, the International Consortium on Landslides (ICL) full members/supporters/associates, ICL-supporting organizations (UN and international global organizations) and ICL-supporting governments, and ISDR-ICL Sendai Partnerships 2015-2025. This article introduces three categories of ICL memberships and calls for participation. [ABSTRACT FROM AUTHOR]

Scientific literature is becoming daily more and more abundant. Scientific and professional journals as primary information sources are competing to each other to attract readership. Their position (ranking, visibility, attractiveness, prestige) in scientific community can be measured by using different journal bibliometric and scientometric parameters, journal impact factor being only one of them. Springer Nature publishes the journal Landslides: Journal of the International Consortium on Landslides since 2004. Being examined in the past by different authors from bibliometric and editorial point of view, this review on the journal's achievements confirmed the high ranking of this journal in the fields of geological and geotechnical engineering and engineering geology. Strong and weak points are discussed from the bibliometric point of view, stressing the need for higher internationality of co-authorship of published articles in order to be true international journal. Continuous publishing and the move to a monthly journal in 2018 will eventually increase journal's h-index and cited half-life of citations, but further editorial efforts should be directed to attract excellent review papers and focused technical notes to increase cites per paper. Until now, the journal Landslides is the foremost journal in the field of landslide disaster risk reduction, and the top young international journal in the field of geological engineering and engineering geology. [ABSTRACT FROM AUTHOR]

The Fourth World Landslide Forum (WLF4) was held in Cankarjev dom-Cultural and Congress Centre in Ljubljana, Slovenia, from 30 May to 2 June 2017, with over 600 participants from 49 countries, 5 international organizations, and 4 United Nations organizations-scientists, engineers, researchers, students, experts, politicians, and other decision makers working in the area of landslide risk reduction. Well, over 100 of them were (post)graduate students. The WLF4 as a triennial event was a contribution of the International Consortium on Landslides (ICL) to the implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030. This article reports on the main WLF4 events and outcomes of the forum. Altogether, close to 400 peer-reviewed full papers, including keynote, invited, and other submitted papers, were published by Springer Nature in five volumes with a total of over 3600 pages. During the WLF4, 20 new World Centres of Excellence on Landslide Risk Reduction for 2017-2020, IPL Awards for Success, Varnes Medals, Best Paper Awards, and other means of recognitions were handed out to the recipients. The WLF4 participants have adopted the '2017 Ljubljana Declaration,' and drafted the 'Kyoto 2020 Commitment,' in order to stress their strong and joint commitment for the ISDR-ICL Sendai Partnerships 2015-2025 on its way towards the Fifth World Landslide Forum to be held in November 2020 in Kyoto, Japan. [ABSTRACT FROM AUTHOR]

This paper analyzes the typical landslides caused by pipeline construction and the characteristics of landslides during the construction period, and assesses the risk to the long gas and oil pipeline project in China caused by landslides during its construction. Using the semiquantitative risk assessment method and introducing the concept of risk degree, according to the assessment of risk and vulnerability, a landslide disaster risk assessing index system was established after summarizing the causative disaster factors of the landslide disasters induced by the construction of the China-Myanmar pipeline project. Three typical disaster points induced by pipeline construction were chosen to make a risk grade evaluation. The results of site reviews show the evaluation results coincide with the actual situation. Thus, semiquantitative evaluation methods can be used as a reference to guide the landslide disasters developed portion of pipeline construction risk control. [ABSTRACT FROM AUTHOR]

Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km 2 , is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area. [ABSTRACT FROM AUTHOR]

Aiming at a landslide appeared during the creep deformation in the south slope of an open-pit mine， the surface morphology of the west boundary of the landslide was determined by using the on-site measurement and the INSAR technique when the east and south boundary shape were already known. Meanwhile， the underground sliding surface was determined by micro-seismic monitoring technique and the west boundary shape was determined according to the surface morphology and the underground sliding surface. Both the geological horizons in the main researching area and the bottom sliding surface of the landslide body were established by the 3D modeling technique. The west boundary shape provides a theoretical basis for the following determination of the landslide shape in the south slope. This collaborative monitoring programme can be a reference for mine slope monitoring under the similar condition. [ABSTRACT FROM AUTHOR]

In this study, in order to map storm event-induced landslide susceptibility for central Taiwan, remote-sensing data were used to interpret landslides using a geographical information system (GIS). Discriminant analysis was used to establish rules that can successfully classify landslide and nonlandslide slopes. GIS-based slope units were used as the terrain subdivision to determine landslide susceptibility. A set of causative factors and a triggering factor were used to build a landslide prediction model. Data for shallow landslides triggered by three crucial rainfall events in July 2001, July 2004, and June 2006 were selected for developing the model. Among the factors used, the total accumulated rainfall is found to be a key factor in the interpretation of landslides. The landslide susceptibility maps were built for the Guoshin region and validated using predicting samples and data from a subsequent storm event, the 2008 Sinlaku typhoon. Results show that the developed model is capable of predicting the shallow landslide distribution induced by heavy rainfall in the study area. [ABSTRACT FROM AUTHOR]

The increase of rainfall and rise of groundwater level can cause frequent failures of unsaturated soil slopes that result in catastrophic landslides. This paper proposes a stochastic method for predicting the risk of failure of an infinite soil slope subjected to unsaturated infiltration flow. Stochastic models for shear stress and strength at an arbitrary plane of an infinite slope are developed. The accuracy of the proposed method is verified with the Monte Carlo simulation method. The merit of the proposed method lies in its analytical form, which can easily facilitate practical applications. Furthermore, a risk-based sensitivity analysis is undertaken in this study to identify the factors that are the most random and that affect the slope failure most significantly. It is found in this study that the developed stochastic models can capture the randomness of all factors that contribute to slope failure. It is also found that the slope inclination angle (θ) soil air entry value (ψb) water table rise from matric suction (yb) dry soil unit weight (γd) and soil-specific constant (aϕ) are important random variables in the accurate prediction of slope failure. The paper concludes that the proposed stochastic method can serve as a tool for geotechnical engineers to predict the risk of slope failure with accuracy and ease. [ABSTRACT FROM AUTHOR]

Landslides are recurrent phenomena in Italy, but little is known regarding the public perception of related risk. In order to investigate landslide risk perception of recent phenomena, we decided to perform a qualitative investigation in Frosinone (Lazio, Central Italy) where, during 2013, a relevant landslide ('Viaduct Biondi') occurred. Survey results highlighted that Frosinone population have been experiencing landslides but do not consider themselves threatened and prepared in occurrence of this type of emergency. This study pointed out that Frosinone municipality and surrounding town populations behave as an inactive actor in land conservation and management, addressing major responsibility to institutions. For this reason, realization of a purposed designed dissemination campaign would be useful in order to improve citizen knowledge and to enhance their participation in landslide risk reduction activities. [ABSTRACT FROM AUTHOR]

Seismic shaking can cause slope instability in otherwise relatively stable permafrost terrains. In addition, rapid ice melting in low-permeability fine-grained soils can lead to excess pore-water pressure build-up and cause instability in slopes even at small angles. This study addresses the active-layer detachment (ALD) slope instability hazard and develops a systematic risk assessment framework for existing and future linear infrastructures, such as energy pipelines, bridges, and roads traversing permafrost regions. Mild slopes, with average gradient of 7°, are considered in this study as the most representative of actual field conditions. The potential for earthquake-triggered ALD is analytically quantified. State-of-the-art ALD morphological statistics for northern Canada are combined with seismic slope stability analyses to determine ( i) the probability of linear infrastructure exposure to permanent ground deformations (PGDs) caused by ALD and ( ii) the extent of the potential PGD that the linear infrastructure may be subjected to. The Monte Carlo technique is applied to simulate and assess the sensitivity of the model to parameters such as earthquake magnitude and source-to-site distance. Findings from this study can be used to evaluate the vulnerability of linear infrastructures exposed to the ALD hazard. [ABSTRACT FROM AUTHOR]

Rockfalls represent significant risks to safe and efficient use of transportation corridors. In this paper, we address the management of rockfall risk through baseline remote monitoring of susceptible slopes (every 2-4 months) along a transportation corridor along the Fraser River valley in western Canada using a terrestrial laser scanner and supporting remote sensing technologies. This includes identifying potential rockfall source zones based on incipient signs of failure, tracking kinematics in three dimensions to better understand the mechanism of failure, estimating potential failure volumes based on bounding joint structure, and transmitting this information to the railway operator for an assessment of risk. We demonstrate our approach for one case along the line where we identified several potential failures ranging in volume from 48 to 4200 m3. Our projections of the location of failures were successful, in that volume projections were within 10%-55%, and the anticipated kinematics and failure mechanism were consistent with the assessment of post-failure rockfall scar geometries. Accurate volume and kinematics estimates are important for the assessment of hazard and risk as well as the planning of risk mitigation options. In general, this approach can be used to better manage risk from rockfall hazard in communities, transportation corridors, or other infrastructure. [ABSTRACT FROM AUTHOR]