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Background: The world population is still growing. The growing population caused a changes in the trend of selecting settlements location. Due to the limited flat land, people were starting to form settlements in a hilly or mountainous area which is prone to landslide. The community used to move from place to place to avoid landslides, however, it is no longer possible to implement those actions. While a lot of research has been conducted to assess the vulnerability and risk of settlements to disasters, there needs to be more research on developing settlements in landslide-prone area and their impact on disaster management. Results: High social influences can be found in the development of landslide-prone settlements of Giripurno Village. The community shows a high consideration on relatives in deciding their settlement location. Moreover, high consideration of kinship and social activity affects the arrangement of spaces in the house and directly affects the amount of space occupancy. Layout of houses in Giripurno Village were found to have large living room to accommodate family and community gatherings. Although high social dependences of one community can be beneficial in the disaster emergency response and recovery, it can also hinder the disaster mitigation effors by allowing development in an unsafe area, thus increase the risk of disasters. Conclusion: This paper discuss about how the social factors can relate to the disaster management with an emphasis on the development of settlements. This paper also highlight the aspects of space occupancy which is rarely being discussed in the disaster management related research. The result obtained by this study could provide important insight into the future disaster management in the landslide-prone settlements area. [ABSTRACT FROM AUTHOR]

Small-scale landslides that occur at unexpected locations and seasons can cause severe losses of life and property. Unusually, the Shidang landslide occurred prior to the rainy season in Jinkouhe County, Sichuan Province, China, resulting in 19 deaths and missing persons. In this paper, landslide characteristics and causes are revealed through a field investigation, laboratory experiments, and numerical calculations. The results show that the Shidang landslide was a small-scale landslide with a total volume of approximately 19500 m3, originating from hollow colluvial deposits. The geomorphological hollow above the landslide provided topographic conditions for the collection of subsurface runoff. Groundwater flow was transported downward along dolomite and accumulated in the area above shale, with a low conductivity. Groundwater table rise combined with the decrease in the soil strength led to landslide occurrence. Improper siting of residential areas and insufficient vigilance against post-rainfall landslides caused this tragedy. Considering the post-disaster lessons, it is strongly recommended that in the future, more attention should be given to the investigation of landslides triggered by groundwater, especially in determining landslide hydrological system boundaries. In mountainous areas where the developable space is limited, areas with hollow landforms are potentially at risk of geohazards. This paper could provide a reference for the prevention and management of similar landslides and new insights for updating landslide investigation systems and residential housing plans. [ABSTRACT FROM AUTHOR]

Background: Earthquakes and landslides pose significant threats to human safety and property, necessitating early warning systems. However, the high construction costs of earthquake early warning systems present a challenge. Purpose: Landslide warnings are more prevalent, so linking them to earthquake warnings could address cost concerns. Hence, it is crucial to validate the feasibility of utilizing GNSS landslide monitoring as assistance for earthquake early warning systems. Methods: This paper analyzes acceleration anomaly data from 31 GNSS landslide monitoring points near the epicenter of the May 2, 2023, MW = 5.2 Baoshan earthquake in Yunnan. The response time was determined as the time difference between an earthquake's occurrence and GNSS's acceleration anomalies. This calculation helps measure the time delay and sensitivity between these two events. Data were obtained from the geological disaster monitoring and early warning management system. Results: GNSS landslide monitoring showed high sensitivity to nearby earthquakes. The fastest response time among the 31 data points was 8 seconds, while the slowest was 56 seconds, all falling within the one-minute mark. A linear correlation was found between acceleration anomaly response time and distance from the epicenter, indicating the feasibility of GNSS landslide monitoring-assisted earthquake monitoring. Conclusion: A proposal is made for a GNSS landslide monitoring cluster to establish a multi-dimensional landslideearthquake disaster warning system. This approach offers new methods for combining earthquake and landslide early warning systems, leveraging existing infrastructure for cost-effectiveness and enhancing disaster preparedness. [ABSTRACT FROM AUTHOR]

Based on construction of landslide displacement field detection system in Heifangtai (Lanzhou, China), landslide geological hazard prediction method based on probability migration is proposed and verified in this paper. In the hardware of landslide displacement field detection system, there are five diction points which contain 15 fiber Bragg grating (FBG) displacement sensors, and the data of detection point 1 m1 m2 and m3 are chosen as sample to complete data analyses. After data analyses, the future trend state of m1 is 'S' due to that state transition probability Pm111 > Pm113 > Pm112, m2 is 'S' due to that Pm211 > Pm212 > Pm213, and m3 is 'S' due to that Pm311 > Pm312 = Pm313. The future trend state prediction is highly consistent with the actual measured data and field observation results. These results of data analyses show that the proposed prediction method in this paper can realize effective prediction of landslide state and has important practical value for landslide prediction. [ABSTRACT FROM AUTHOR]

Landslides are a major cause of losses and damages in railways and roadways which cross hilly regions. Some landslides may cause traffic interruption for several days, leading to severe prejudice to cargo flow in busy transportation systems. Landslide studies are essential to identify potentially unstable areas, and their consequent impact on infrastructure, and prioritize critical areas to implement failure prevention measures. This paper presents the results of a Landslide Hazard Analysis Program (LHAP) developed to evaluate failure-prone slopes along a 41-km rail that crosses the “Serra do Mar” mountain range, located in the southeastern region of Brazil. This railway was built in the late 1920s and is still vital to transport commodities from the Brazilian countryside to the major port in Brazil, located in the city of Santos. The paper shows how local geological-geotechnical conditions, associated with construction peculiarities, resulted in a very fragile infrastructure. Recent failures caused severe losses and damages to the railway system, leading to traffic interruption for several days and prejudice to cargo flow. The Landslide Hazard Analysis Program was developed to identify and understand the main causes of slope failures and prioritize intervention with basis on failure susceptibility and consequences to the railway. A failure prevention program was developed with basis on the results and consisted in stabilizing slopes with both temporary and permanent retaining structures as well as restoring and implementing a new drainage system. The methodology presented in this paper could be validated with basis on data from five slope failures that occurred in cut slopes after the ranking had been defined, demonstrating the suitability of the analysis. With some adaptations, the methodology may be used in similar linear structures such as roadways, pipelines, and others. [ABSTRACT FROM AUTHOR]

Over the past years, the growing number of natural hazards all over the world has led to an increasing focus on activities aimed at studying and controlling the occurrence of these phenomena. In this context, monitoring systems have become a fundamental component for Landslide Early Warning Systems, allowing to understand the evolution of these processes and assess the need for dedicated mitigation measures. This result is achieved thanks to several technological advancements that led to the introduction of more accurate and reliable sensors, as well as automatic procedures for data acquisition and elaboration. However, despite these improvements, the data interpretation process is still a challenging task, in particular when it comes to the identification of critical events and failure forecasting operations. This paper presents a methodology developed to assess if a potentially critical event is displaying a significant deviation from previously sampled data, or if it could be classified as a false alarm. The process relies on the definition of a threshold value based on the landslide behavior preceding the event of interest. In particular, the reference value derives from the evaluation of equivalent displacements, defined as the displacements previously observed in a time interval equal to the one showed by the potentially critical event. This paper reports a series of examples referring to different case studies, involving both false alarms and real collapses, underlining the effectiveness of the proposed model as a useful tool to evaluate the landslide behavior with a near-real-time approach. [ABSTRACT FROM AUTHOR]

Length (L), width (W), and aspect ratio (ε, L/W) are elementary parameters widely adopted to characterize landslide geometry. Aspect ratio (ε) had been associated with the propagation of landslide along its movement path. However, current automatic measurement algorithms have not effectively considered the path of landslide movement, therefore only measure "path-independent" instead of "path-dependent" geometric parameters. This paper proposes a new approach for measuring path-dependent landslide L, W, and ε, in which path-dependent landslide L (Lpdep) is measured as the path distance from the landslide crown to its tip along the central line of landslide movement, and path-dependent landslide W (Wpdep) is measured as the weighted average lateral extent, across the central line of landslide movement. Specifically, Wpdep is calculated indirectly through dividing the landslide area by its length (A/Lpdep), and path-dependent landslide ε (εpdep) can be calculated by Lpdep2/A. The central line of landslide movement, i.e., landslide profile, is a three-dimensional (3D) polyline generated by the freely available software ALPA (Automatic Landslide Profile Analysis), and all these path-dependent geometric parameters can be measured either in 3D space or in two-dimensional (2D) space (in the horizontal plane). A case study is presented showing that path-dependent parameters can be effectively measured by the proposed profile-based approach, and could be significantly different from path-independent parameters especially for long-narrow and tortuous landslides. This paper also practically introduces new path-dependent definitions of landslide L, W, and ε, which inspires a worthwhile revisit of nomenclature. An overview shows that significant divergencies exist between current definitions of landslide L, W, and ε. In order to moderate the raised ambiguities and confusions, this paper accordingly suggests a "physically indicative" inclusive nomenclature somehow embracing all current representative definitions, and then appeals for constituting "type-specific" nomenclatures for each landslide type. However, some open questions still exist. We therefore suggest relevant academic organizations to work further on type-specific nomenclatures and effective measurement approaches for landslide L, W, and ε. [ABSTRACT FROM AUTHOR]

This paper presents the first example of how to systematically identify the submarine landslide source of a tsunami using an innovative hybrid approach. This ground-breaking method is developed to resolve the puzzle around the source mechanism of the mysterious tsunami observed on 6th February 2023 in the Eastern Mediterranean Sea. The tsunami followed the two inland Mw 7.8 and Mw 7.5 Türkiye–Syria earthquakes, which occurred consequently with a 9 h interval on this day. The first earthquake (Mw 7.8) had an epicentral distance of 90 km from the nearest coast, which is closer than the second one (Mw 7.5) to the coast and yet its crustal deformation was almost entirely limited to inland. Therefore, the co-seismic surface displacement generated by the earthquake was ruled out as the source of the tsunami, confirmed by numerical modelling. Here, we hypothesized that the tsunami was most likely generated by a submarine landslide triggered by the earthquake. Analysis of tide gauge observations revealed that the waves arrived from 27 min to 48 min after the first earthquake (Mw 7.8) at different coastal locations, implying that the potential submarine landslide was triggered by the first earthquake (Mw 7.8). Backward tsunami travel time mapping using tide gauge observations guided us to constrain the area of the potential landslide. We approximated the dimensions of the landslide using spectral analysis of the tsunami observations. Consequently, an iterative trial-and-error approach was employed to confirm the landslide source of the tsunami by defining various informed alternative landslide scenarios and applying numerical modeling. Modelling showed that a submarine landslide can reproduce the tsunami observations reasonably well. It is located on a steep slope of the seafloor approximately 50 km from Arsuz. The submarine landslide is estimated to have caused a seafloor deformation measuring approximately 16 km in length and 4.0 km in width. [ABSTRACT FROM AUTHOR]

The reservoir impoundment can lead to accelerated deformation or reactivation of landslides, posing great threats to human lives and dam stability. The primary objective of this paper is to report the movement process of the Tuandigou (TDG) ancient landslide in the Baihetan dam area during reservoir impounding. Field investigation, borehole work, and site monitoring data are used to analyze the deformation behavior and triggering mechanism of the TDG landslide. It is found that the landslide deformation is closely related to the reservoir water level. After the reservoir water level reached the elevation of 810 m on October 12, 2022, the ground cracks continued to expand and gradually linked up, resulting in an accelerated deformation of the TDG landslide. Furthermore, the lithology in the study area also positively contributes to the slide movement. Based on these results, it is anticipated that the present research will provide guidelines for the early warning and control of the TDG landslide during and after the reservoir impounding. [ABSTRACT FROM AUTHOR]

In the past few decades, digital technologies have played a more and more important role in landslide disaster risk management. To identify the progress and future directions with regard to the use of digital technologies in landslide disaster risk management, a systematic review of journal papers in the ISI Web of Science is conducted in this study. Findings indicate that in the early phase, landslide risk management research mainly focused on hazard evaluation and zonation. Then, studies about the spatial predictions of landslides and landslide susceptibility appeared. The research scale of landslides is developing from large scale to fine scale. The use of digital technologies in landslides has been widely discussed since 2009. The use of digital technologies has been developing in the directions of deep learning and artificial intelligence. The monitoring means has been gradually developing from high altitude to low altitude and to ground sensors. Processing technologies are the most widely used in landslide disaster risk research, followed by sensing technologies. Different types of digital technologies play different roles in landslide disaster management. Digital technologies account for a low proportion in the mitigation phase, but contribute the most in the disaster preparation phase. In the future, digital technologies can further strengthen mitigation for and responses to landslide disasters. The application of digital technologies in landslide disaster management should gradually adapt to the needs of the vulnerable group. The government should implement differentiated landslide disaster management according to the regional level of economic development and digital technology development. This study not only reviews the state of the latest technology, but also addresses the future trend of research and provides support for scientists and decision-makers involved in landslide disaster management. [ABSTRACT FROM AUTHOR]

The aim of this paper is to report on fatal landslides resulting from two extraordinary storm events in January and February 2023, in Auckland, New Zealand, including the characteristics of the terrain, the site geology, and the storms. The January 27 Auckland Anniversary storm was from an "atmospheric river," dumping Summer's worth of rain (265 mm) in one day. This was the highest 24-h total on record, estimated a 1 in 200-year event, with a peak 2-min rainfall of 4.2 mm, coinciding with Friday's evening "rush hour." This led to widespread landsliding throughout Auckland, including a fatal landslide in Parnell, central Auckland. Notably, this occurred only meters from a similarly destructive landslide in 1997. With January 2023 Auckland's wettest January on record, and with the region still in a state of emergency, Tropical Cyclone Gabrielle crossed the region on February 13–14. This also caused widespread landsliding, including a fatal landslide at Muriwai on the west Auckland coast. Fatal landslides from the same escarpment had occurred in 1965, close to the February 13, 2023, fatal landslide. Taken together, both storm events caused > 140,000 landslides across the North Island, and flooding, making hundreds of people homeless, with damage estimates of > US$8.6 billion (3.4% of NZ's GDP). For future disaster risk reduction, attention should be paid to revising legislation and local planning, which currently allows people to legally build (and re-build) houses in landslide-prone areas of New Zealand. [ABSTRACT FROM AUTHOR]

The use of Global Navigation Satellite System (GNSS) in combination with real-time kinematic technique, known as differential GNSS (dGNSS), has increased in recent years for monitoring landslide displacements and detecting early signs of potential failure, enabling an earlier response for risk mitigation than traditional monitoring techniques. GNSS offers several advantages, including high accuracy and high-frequency data collection. Although more cost-effective, their affordability may still present challenges for public organizations managing multiple landslides in their territory. The SparkFun is a suite of components for GNSS assembly designed for topographic surveying, that integrates u-blox ZED-F9P or ZED-F9R modules. The system offers the benefits of dGNSS technology while being more affordable than other market options. It also avoids relying on phone signals for data storage on a cloud server. This paper presents the SparkFun system, its components, and how it can be assembled to create a dGNSS system for landslide monitoring. The deployment and testing at the Chin Coulee landslide in Alberta are discussed. Over the 6-month testing period, the system achieved millimeter accuracy (up to 14 mm), aligning with the manufacturer's specifications. Estimated system errors were found to be comparable to a commercially available dGNSS system (Ophelia Geocube). Additionally, the system exhibits displacement trends similar to the 2018 Geocube monitoring campaign; however, for future deployments, the robustness of the power supply system and the insulation of the equipment need to be enhanced. Overall, the SparkFun system appears to be a promising and cost-effective alternative for monitoring landslide displacements. [ABSTRACT FROM AUTHOR]

The purpose of this study is to propose an impact analysis model to explore the effect of the post-earthquake landslide surge on local damage to ultra-high arch dams. Based on the existing pressure model of landslide-generated waves impacting the dam, nonlinear dynamic analysis is conducted on a high arch dam subjected to the landslide surge of different surge heights after the earthquake, through numerical simulation. According to the theory of nonlinear least squares, the relationship between the surge height and the damage value of all dam elements is fitted with a Sigmoid function, and the results show good fitting performance. This result proves that the proposed impact analysis model can well reflect the influence of the surge height on the local damage to arch dams. In addition, three parameters are defined based on this model. The influence of the post-earthquake landslide surge on the local damage of arch dams at different positions is analyzed based on these three parameters, and the vulnerable positions of the dam body under the impact of the post-earthquake landslide surge are determined. The model has important significance for the safety evaluation of dams affected by landslide-generated waves after an earthquake. [ABSTRACT FROM AUTHOR]

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

Selecting appropriate mapping units is vital for landslide susceptibility mapping as well as pattern investigation, given that various units-based analyses extensively control the prediction performances. This paper investigated the landslide development through the interpretation and field surveys along the Yunling–Yanjing segment of the Lancang River in southeastern Tibet, and fulfil LSM with the consideration of 15 conditioning factors. Two grid unit methods (single-point and multi-point patterns) and two slope unit methods were comparatively analyzed for model training and mapping of landslide susceptibility via machine learning algorithms. The results suggest that the landslides are preferentially distributed in an elevation range of 2000–4000 m, in a slope range of 20–40°, a local relief range of 1000–2500 m, and southwest-oriented slopes. The data extracted by the multi-point method denotes a higher representation of landslide development features. All models possessed positive prediction ability for landslide susceptibility, and the multi-point method based on grid unit performed the best with the AUC exceeding 0.9. The best-performing models indicated that zones of high and very high susceptibility mainly distributed adjacent to the mainstem and some tributaries of the Lancang River. Furthermore, the distribution of "safety islands" (the slopes less prone to landslides) along National Highway G214 was reasonably illustrated as well, which provides a hazard predictability for such an important transportation corridor along the deeply-incised valley in the Lancang River. This study demonstrates a theoretical basis for the regional disaster prevention and mitigation for human activity, and provides methodological references for landslide susceptibility evaluation in similar mountainous areas over the world. [ABSTRACT FROM AUTHOR]

Among natural hazards occurring offshore, submarine landslides pose a significant risk to offshore infrastructure installations attached to the seafloor. With the offshore being important for current and future energy production, there is a need to anticipate where future landslide events are likely to occur to support planning and development projects. Using the northern Gulf of Mexico (GoM) as a case study, this paper performs Landslide Susceptibility Mapping (LSM) using a gradient-boosted decision tree (GBDT) model to characterize the spatial patterns of submarine landslide probability over the United States Exclusive Economic Zone (EEZ) where water depths are greater than 120 m. With known spatial extents of historic submarine landslides and a Geographic Information System (GIS) database of known topographical, geomorphological, geological, and geochemical factors, the resulting model was capable of accurately forecasting potential locations of sediment instability. Results of a permutation modelling approach indicated that LSM accuracy is sensitive to the number of unique training locations with model accuracy becoming more stable as the number of training regions was increased. The influence that each input feature had on predicting landslide susceptibility was evaluated using the SHapely Additive exPlanations (SHAP) feature attribution method. Areas of high and very high susceptibility were associated with steep terrain including salt basins and escarpments. This case study serves as an initial assessment of the machine learning (ML) capabilities for producing accurate submarine landslide susceptibility maps given the current state of available natural hazard-related datasets and conveys both successes and limitations. [ABSTRACT FROM AUTHOR]

A paper recently published by Bartelt and Buser (hereafter identified as 'the authors') aims to clarify relationships between granular dilatancy and dispersive pressure and to question the effective stress principle and its application to shallow granular avalanches (Bartelt and Buser in Act Geotech 11:549-557, 2). The paper also criticizes our own recent work, which utilizes the concepts of evolving dilatancy and effective stress to model the initiation and dynamics of water-saturated landslides and debris flows. Here we first explain why we largely agree with the authors' views of dilatancy and dispersive pressure as they apply to depth-integrated granular avalanche models, and why we disagree with their views of effective stress and pore-fluid pressure. We conclude by explaining why the authors' characterization of our recently developed D-Claw model is inaccurate. [ABSTRACT FROM AUTHOR]

Context: Since the nineteenth century, rural areas have experienced progressive abandonment mostly due to socioeconomic changes, with direct and indirect effects on forest disturbance regimes occurring in these human-dominated landscapes. The role of land abandonment in modifying disturbance regimes has been highlighted for some types of disturbances, albeit being still somewhat overlooked compared to climate change. Objectives: This literature review is aimed at highlighting the most relevant effects of land abandonment and land-use legacy on the regime of different types of forest disturbances, providing insight into land-use change/disturbances interactions. Methods: We searched in the Scopus and Web of Science databases for relevant studies at the global scale dealing with eight major natural disturbances: avalanche, flooding, herbivory, insect outbreak, landslide, rockfall, wildfire and windthrow. We classified papers into five relevance classes, with the highest score (4) assigned to studies quantitatively measuring the interactions between abandonment dynamics and disturbance regimes. Results: Most papers focused on wildfires in Mediterranean Europe in the twentieth century, where landscape homogenisation and fuel build-up contributed to worsening their frequency, size and severity. Dense forests developed following land abandonment instead exert inhibiting effects toward mass movements such as avalanches, rockfalls and landslides. Regarding the other investigated disturbances, we found only a few studies presenting site-specific and partly contrasting effects. Conclusions: Land abandonment triggers ecological processes at the landscape scale, altering land cover patterns and vegetation communities, which in turn affect disturbance regimes. Implications for land and resource management mostly depend on the stage at which post-abandonment secondary succession has developed. [ABSTRACT FROM AUTHOR]

Accurately evaluating the failure process of soil slope can mitigate its negative influence on both human lives and economic loss. However, it is still a very difficult and important task. In this paper, a novel nonlinear rheological model with nonstationary parameter creep (NPCNRM) was proposed to represent the tertiary creep characteristics of slope soil. One-dimensional constitutive equations and three-dimensional (3D) model of NPCNRM were derived, and its 3D finite element program was developed in Fortran. The feasibility of the proposed model was partially verified by the uniaxial creep test of argillaceous slate. Through the application of Liangyeshan landslide located in Wuping county, Fujian province, China, the results show that using the proposed model can scientifically evaluate the creep failure mechanism of saturated granite residual soil slope; the accelerated creep of soil near the top of the slope is more significant than that at slope toe, which will aggravate the disintegration and loosening of soil and the continuous infiltration of rainfall, and then leads to further deterioration of soil strength. [ABSTRACT FROM AUTHOR]

As one of the most destructive geological disasters, a myriad of landslides has revived and developed in the Three Gorges Reservoir area under the combined action of various detrimental factors. Therefore, the pertinently regional landslide susceptibility mapping (LSM) is of great significance for disaster prevention and mitigation. In this study, LSM is prepared by using a boosting-C5.0 decision tree model. Under the landslide verification of on-site investigations, the study area is divided into accumulation and rock areas, and a total of 12 impact factors are selected. TOL and VIF are employed to determine the multicollinearity among the impact factors. The independent training (80%) and validation (20%) datasets are constructed by random sampling for LSM. ANN, C5.0, and SVM are selected for comparative analysis. The results show that there is no rigorous multicollinearity among the impact factors proposed in this paper. The landslide susceptibility in the study area is divided into low, moderate, high, and very high. The highest susceptibility area distributes along the riverside where the landslide ratio is 37.05% in boosting-C5.0 model. Then the ROCs are expropriated to infer the accuracy of each model. The boosting-C5.0 performs the best with the largest area under the curve in both accumulation and rock areas, reaching at 0.991 and 0.990 in the validation sets, respectively. Finally, the composite modification of the 5 validation sets shows that the uncertainty of boosting-C5.0 is concentrated in the intermediate probability areas of susceptibility. This study reveals the feasibility of machine learning in landslide susceptibility assessment, which could provide a basis for the risk management and control of geological disasters. [ABSTRACT FROM AUTHOR]

The premise of ecological protection and sustainable development in coal mining areas is to find the law of surface damage, damage speed and damage mechanism, and then put forward preventive measures in a targeted manner. Taking the landslide in the coal mining mountain area of Shanxi Province as an example, this paper comprehensively integrates the disaster-pregnant environment and disaster information of the landslide, and constructs a multi-level model of the scene through the analysis of the landslide geology scene. The object features characterize the evolution process of landslides in terms of stratigraphic structure changes, surface changes, texture changes, shape characteristics, spectral characteristics, color characteristics, etc., the typical landslide types in Shanxi coal mining areas are verified by examples. The comprehensive consideration of geology, geographical environment, ecological environment, disaster environment and the damage of landslides to other important ground features, with the advent of the era of big data, various data obtained from air, space and ground monitoring can be applied to research. Through the cognition of landslide spatial scenes, it is helpful to understand the influence mechanism of external events on landslide activities, so as to better predict the spatial and temporal characteristics of landslide activities. [ABSTRACT FROM AUTHOR]

Landslide instability occurs frequently all over the world. The specific factors affecting the loess slope instability include collapse, landslide, debris flow, etc., among which rainfall is one of the most important factors. In this paper, through field model tests, the displacement changes of soil mass at different depths inside the slope and on the slope surface under different rainfall intensity and rainfall time are studied by means of artificial rainfall and artificial water injection. The results show that under the circumstance of rainfall, the displacement of the shallow soil changes obviously, while the deep soil shows obvious hysteresis; as the rainfall process continues, the displacement of the deep soil increases gradually, but the growth rate is significantly lower than that of the shallow soil. After the rain stopped, the soil displacement continues to increase within 3 to 4 days, the deformation of the shallow soil is relatively stable, and the deformation of the deep soil converge slowly. With the increase of rainfall intensity, the closer the soil mass is to the slope toe within 2.2 m, the greater the horizontal displacement is, but the displacement change of shallow soil mass within 0.8 m is smaller, and the displacement at the slope toe is the most obvious. The closer the soil below 2.2 m to the slope toe, the smaller the horizontal displacement of the slope. The closer to the toe of the slope, the more likely the loess slope to be damaged. The slope shows different effects under the influence of rainfall, water injection, rainfall duration, and influencing region. The research results can provide guidance for loess slope reinforcement and slope restoration. [ABSTRACT FROM AUTHOR]

In the present paper, an active landslide located to the southeast of the urban area of Alcoy (Alicante, Spain) is analysed. This landslide affects the N-340 road, as well as an area in which some industrial buildings dated from the fifteenth century and catalogued as Places of Cultural Interest are placed. This region is characterised by the existence of a steep relief composed of materials from the Miocene to the present, on which many gravitational movements are developed. The displacements have been analysed using high-resolution spotlight mode SAR images captured by the Spanish SAR satellite PAZ (which operates at X-band), which were processed by advanced differential SAR Interferometry (A-DInSAR). The behaviour of the instability has been determined using InSAR-derived time series displacement maps. Additionally, the study has been completed with a detailed geomorphological mapping at 1:2000 scale and an analysis of structural damage carried out in situ. The landslide was modelled in 3D, from a deterministic and probabilistic point of view, confirming the global instability of the area and the relationship of the landslide with rainfall and the construction of a new road. The integration of all this information obtained and its subsequent analysis has made possible to precisely define the extension of the instability, its kinematics, and to identify the main triggering factors. This information will be crucial for the proper management of this landslide by the local authorities. [ABSTRACT FROM AUTHOR]

Landslide monitoring is a mandatory step in landslide risk assessment. It requires collecting data on landslide conditions (e.g., areal extent, landslide kinematics, surface topography, hydrogeometeorological parameters, and failure surfaces) from different time periods and at different scales, from site-specific to local, regional, and national, to assess landslide activity. In this analysis, we collected information on landslide monitoring techniques from 17 members of the Earth Observation and Geohazards Expert Group (from EuroGeoSurveys) deployed between 2005 and 2021. We examined the types of the 75 recorded landslides, the landslide techniques, spatial resolution, temporal resolution, status of the technique (operational, non-operational), time of using (before the event, during the event, after the event), and the applicability of the technique in early warning systems. The research does not indicate the accuracy of each technique but, rather, the extent to which Geological Surveys conduct landslide monitoring and the predominant techniques used. Among the types of landslides, earth slides predominate and are mostly monitored by geological and engineering geological mapping. The results showed that Geological Surveys mostly utilized more traditional monitoring techniques since they have a broad mandate to collect geological data. In addition, this paper provides new insights into the role of the Geological Surveys on landslide monitoring in Europe and contributes to landslide risk reduction initiatives and commitments (e.g., the Kyoto Landslide Commitment 2020). [ABSTRACT FROM AUTHOR]

The preferred plane often exists in a layered slope, which has a main influence on the slope stability. Such a plane can evolve into the failure surface, due to the internal and external triggers of landslides. This paper proposes a case study of the failure of a highway slope in Sichuan, China. The site investigations were conducted using a number of methods, such as geological survey, unmanned aerial vehicle survey, slope monitoring, in-situ and laboratory tests. Through the case study, the failure mechanism of the layered slope was discussed, where the slope stability analysis was conducted using the limit equilibrium method (slip-wedge method) and strength reduction method (SRM). According to the circumstance of the landslide area and the requirement for the highway, this paper also proposes the stabilization measures, which was subsequently validated by SRM. Finally, the sliding mechanism of the landslide was discussed. [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]

A destructive landslide occurred in spring 2019, in Hosein Abad Kalpush Village, Northeast of Iran, after an unusually rainy period. Significant damages were observed in buildings and roads located on the slope failure zone. This paper represents a preliminary reconnaissance report prepared through the site visit done by the authors, a few days following the landslide occurrence. Then, the geotechnical and geophysical properties of the sliding area are reported using the site investigation tests. Subsequently, the rainfall data are incorporated for numerical slope stability analyses. This study shows the variation of the failure mechanism of the slope before and after rainfall. The results confirm that the factor of safety decreases 1.78 times after a 3-month period of rain with rainfall intensity about 6 times the long-term average. Finally, the performance of two slope stability improvement strategies is evaluated to mitigate the landslide hazard. The results of the study can provide a perspective on the climate change impacts in Iran for future geosystem designs, geohazard prediction, and the selection of rainfall-induced landslide mitigation strategies. [ABSTRACT FROM AUTHOR]

Landslides are one of the main geological disasters in the riparian zone of the Three Gorges Reservoir Area (TGRA) in China, causing massive losses in terms of industrial and agricultural production and people's lives and property. Due to the difficulty of data collection and lack of facade information, the remote sensing methods currently used for landslide mapping and detection are insufficient. The current landslide information acquisition method is mainly based on visual interpretation and automatic computer classification from aerial orthophotographs, which is subjective and time-consuming and yields low accuracy. New shipborne photogrammetry has unique advantages in small and steep slope landslide detection. In recent years, the deep learning technology represented by convolutional neural networks (CNNs) exhibits more powerful feature learning ability in image recognition than traditional machine learning technology. Meanwhile, transfer learning can make the network suitable for small datasets through fine-tuning, which could transfer the parameters of the pretrained model to the new model in a certain way, thereby increasing the learning efficiency of the model. In this paper, the training of multiple deep learning models is realized through transfer learning, and automatic identification of landslides based on shipborne images is achieved through decision-level fusion. The experimental results show that through the integration of decision-level fusion and transfer learning, it performs well in the classification of landslides based on shipborne images. [ABSTRACT FROM AUTHOR]

Landslides which occur at unexpected locations and times, and which have unrecognizable risk areas, often cause mass casualties. Despite there being few preceding landslides in the same season, the catastrophic Qijiaba landslide occurred in the new government-selected settlement of Wufu village, Sichuan Province, China, on September 5, 2021, killing three people and destroying 13 houses. In this paper, the landslide features and causes are discussed based on field investigations, remote sensing interpretations, and laboratory-based soil experiments. The results showed that it was a typical soil landslide within a geomorphic hollow of the slope with a volume of 20,230 m3, recurrence interval of at least 69 years, and runout distance of 137.5 m. This type of landslide is difficult to predict. The soil strength in the sliding surface decreased suddenly as the water content increased, and the soil's rich clay mineral and high clay particle contents determined its high mobility (Heim's ratio of 0.44). The occurrence time of the Qijiaba landslide lagged 1.3 days behind the peak rainfall, and the 2-day cumulative rainfall was a crucial factor in the landslide occurrence. Finally, the large water confluence area behind the main scarp was determined to be 3.9 times the area of the landslide itself, thereby providing abundant water conditions to induce failure. The factors underlying the casualties included inappropriate site selection, insufficient awareness of potential landslides, and failure to evacuate in time. The results of this study provide a basis for future prevention, mitigation, and early warning of similar landslides. [ABSTRACT FROM AUTHOR]

Geological hazards, especially landslides, occurred frequently in Zigui County, which significantly caused a great threat to the safety of people's lives and property. At present, the investigation of landslides in Zigui County mainly focuses on the cause analysis of a certain characteristic landslide, while the regional landslide susceptibility analysis is absent in Zigui County. To effectively control the landslides in Zigui County, this paper utilized analytic hierarchy process (AHP) and variable weight theory (VW) to evaluate the landslide susceptibility in Zigui County based on five evaluation indicators (lithology, slope, distance from the fault, distance from the river, and landform). The results in the AHP model showed that the susceptibility areas of very low, low, medium, and high account for 14.16%, 38.11%, 36.31%, and 11.42%, respectively, while the results in the AHP-VW model are 12.41%, 29.67%, 32.19%, and 25.73%, respectively. Based on the area under curve (AUC) results, the accuracy of the AHP-VW model has been greatly improved by introducing the VW in the landslide susceptibility evaluation. Additionally, this paper also verified that rainfall and human activities are two important factors to induce landslides. The adaptive prevention and control methods are also proposed and recommended in Zigui County according to the composition factors and precipitating factors. [ABSTRACT FROM AUTHOR]

Nowadays, the 3D modelling of surfaces is widely used to provide point clouds in geosciences. To study the evolution of landslides, many point clouds are available but post-processing can be very computationally demanding, especially to analyze their dynamics. This paper proposes automatic tools to identify areas with continuous motion and those with non-continuous motion using a new continuous motion indicator. Displacements of continuously moving areas are computed by two "displacements" methods (the image correlation method and the Gefolki differential optical flow method), which are compared. The evolution of non-continuous motion areas is quantified by a distance metric. The developed method is applied on two sites with different deformation mechanisms and evolution speeds to test the ability to show the 3D spatial evolution of landslides. The comparison with instrumental data shows a good concordance between the calculated data and the reference data. The Gefolki differential optical flow method is considered as a relevant option for the image correlation method with the new continuous motion indicator. [ABSTRACT FROM AUTHOR]

The Jianshanying landslide in Guizhou province, China, is a typical mining-induced landslide with its complex formation in karst mountainous area. However, the spatiotemporal deformation characteristics and failure mechanism are still unknown. In this paper, the surface deformation time series from 2017 to 2020 is firstly estimated by combining multi-temporal synthetic aperture radar (SAR) interferometry and improved offset-tracking methods to overcome the difficulties caused by the large gradient surface deformation and surface material changes. Then, the spatiotemporal characteristics of Jianshanying landslide is analyzed in terms of line-of-sight (LOS) deformation with stacking InSAR method and two-dimensional (2D) deformation with improved SAR offset-tracking method. And the different deformation features between sliding body and surrounding areas are uncovered. Accordingly, we point out the "three-section" surface deformation model. We further analyze the deformation time series by considering the joint effects of rainfall and underground mining. Finally, we conceptualize the landslide failure mode for the Jianshanying landslide, which can be extended to the similar landslide in karst mountainous areas of southwestern China. [ABSTRACT FROM AUTHOR]

This paper reports the results of satellite image and seismological data analysis obtained when considering the causes of a landslide on the Yelbashinskii dump at the Kolyvan anthracite deposit. The potential for determining the natural vibrations of large objects from low-frequency seismological records and monitoring thereof has been demonstrated. [ABSTRACT FROM AUTHOR]

A framework for a IoT-based local landslide early warning system (Lo-LEWS) has been proposed. Monitoring, modelling, forecasting and warning represent the main phases of the proposed framework. In this study, the first two phases have been applied to capture the hydrological behaviour of a natural unsaturated slope located adjacent to a railway track in Eastern Norway. The slope is monitored and the stability is kept under frequent observation, due to its steepness and the presence of the railway lines at the toe. The commercial software GeoStudio SEEP was used to create and calibrate a model able to replicate the in situ monitored volumetric water content (VWC) and pore water pressure (PWP) regime. The simulations conducted were divided into two main series: one with an initial calibration of the VWC profile (C) and another with no calibration (NC). The simulations have been validated using Taylor diagrams, which graphically summarize how closely a pattern (or a set of patterns) matches observations. The results show that a preliminary calibration for matching the in situ VWC, as well as considering climate conditions and vegetation, are crucial aspects to model the response of the studied unsaturated slope. A sensitivity analysis on the hydraulic conductivity and the permeability anisotropy ratio contributed to better define the input data and to improve the best-fit model result. The effectiveness of the best simulation, in back-calculating VWC, was tested for 3 different time periods: 6-month, 1-year, 1.25-year. The results show that the hydrological model can adequately represent the real monitored conditions up to a 1-year period, a recalibration is needed afterward. In addition, a slope stability analysis with GeoStudio SLOPE for the 1-year period was coupled to the hydrological model. Finally, the calculated safety factor (FS), the temperature, the precipitation, the VWC and PWP monitored were used as input dataset for a supervised machine learning algorithm. A random forest model highlighted the importance of the monitored VWC for forecasting the FS. The findings presented in this paper can be seen as a first step towards an Internet of Things (IoT)-based real-time slope stability analysis that can be employed as Lo-LEWS. [ABSTRACT FROM AUTHOR]

The great M ~ 8 1920 Haiyuan earthquake (HYEQ) was one of the largest and most deadly earthquakes in China in the last century, with ~ 234,000 deaths. The earthquake occurred within the Loess Plateau of northern China, where Quaternary loess deposits form a distinctive blanket across the landscape. Large regions of this loess cover experienced co-seismic landslides. Based on an analysis of the original disaster reports, field surveys, and satellite image interpretation, we have compiled the shaking effects of the earthquake, including the distribution of landslides, fatalities, and structural damage. Landslides triggered by the HYEQ (n > 7,000) are concentrated south of the Haiyuan fault, in a region that has both thick loess cover and long-term relief generated by the drainage network. This distribution is spatially separated from landslides triggered by other earthquakes. We find that in contrast to previous studies, the most important factor in the severe death toll of the HYEQ was the collapse of housing by ground shaking, including collapse of loess house-caves. Landslides were a secondary factor; although up to 32,000 deaths occurred in areas with intense landsliding. Based on the revised distribution pattern of landslides and damage (e.g., house collapses), we suggest that the isoseismal intensity IX line extends south of previous locations. We have also identified 126 dammed lakes created by co-seismic landslides, which form major modifications of this semi-arid landscape. The research methods in this paper, combining historical review, satellite image interpretation, and field validation of landslides, can be used as a reference for studies of other areas affected by historical earthquakes and co-seismic landslides, elsewhere in the Loess Plateau and beyond. [ABSTRACT FROM AUTHOR]

Underground mining under the slope can induce strata movement, which in turn can induce landslides and surface subsidence. Previous studies have focused on the damage behavior of the surrounding rock mass caused by underground mining, ignoring the combined effect on the rock mass from open-pit mining to underground mining. In this paper, unmanned aerial photogrammetry (UAV) and interferometric synthetic aperture radar (InSAR) investigations were used to obtain the failure characteristics and displacement evolution of rock masses caused by underground mining. Then, based on Yanqianshan mine measurement results and combined with 3D numerical modeling, the sliding surface evolution inside the slope and the failure mechanism were analyzed. In addition, a double-sliding surface deflection (DSD) failure model for analyzing the landslide area was proposed and validated by base friction tests. The results showed that underground mining was the factor that directly led to landslide development. The failure characteristics are summarized into three phases: bottom collapse, traction landslide, and ground subsidence. The maximum deformation value reaches 193.1 cm, and vertical displacement is dominant with a maximum rate of − 115.73 cm/a. The internal movement boundary was deflected near the slope surface, and the deflection direction depended on the synthesis vector of two mining influences. These results are significant for disaster risk reduction caused by underground mining. [ABSTRACT FROM AUTHOR]

A new anchor-siphon drainage combined method used for slope stabilization is proposed in this paper. It includes an anchoring section and a siphon drainage section. The novelty of the anchor-siphon drainage combined method is the realization of the drainage and anchoring in the one inclined borehole. The engineering cost of drilling and the resulting disturbance to the slope is reduced. To validate the feasibility of the proposed method, a numerical method that combines the pore water pressure distribution after siphon drainage and the anchoring force of the anchoring section is used to evaluate the safety of the slope with the anchor-siphon drainage method. The proposed method was illustrated and validated with the Hongpu Village landslide, in Tonglu County, Zhejiang Province, in China. Compared with the common anchor bar with the same length in the anchoring section, the factor of safety (FOS) for Hongpu Village slope with anchor-siphon drainage is increased by 0.085. The calculation method of the optimal length ratio between the drainage section and the anchoring section and its influencing factors were studied. For the different design parameters, there is always an optimal length ratio of the drainage section. Compared with the siphon drainage and full-length anchor bar with the same borehole length, the anchor-siphon drainage combined method shows better landslide prevention ability. Moreover, when the optimized parameters with a bond strength of 560 kPa, a borehole inclination of 35°, and no reduction in length are used, the calculated safety factor is 1.316, which is significantly higher than the FOS of 1.131 for the slope with siphon drainage. [ABSTRACT FROM AUTHOR]

Most previous studies on the quantitative risk assessment (QRA) of landslides focused on the probability of slope failure at the pre-failure stage and adopted empirical models for consequence analysis. The conventional approaches simplify the relationship between the pre-failure state and the post-failure behavior and cannot reasonably account for the effects of uncertainty on the entire landslide process. In this paper, an efficient QRA method that involves the direct simulation of the entire landslide process is proposed. A QRA formula that considers the probability of only those landslides that can impact the element at risk is used. The coupled Eulerian–Lagrangian method is used to simulate the entire landslide process and to identify slopes that can impact the element at risk and determine the failure consequences. The subset simulation method is adopted to efficiently estimate the probability of landslide impact, and parameter uncertainty is considered. Two case histories of landslides are investigated. First, the 2011 Baqiao loess landslide in Xi'an, China, is investigated, and the results of the proposed method are compared with those of the conventional approaches. Second, the proposed method is applied to assess the risk of the 2015 Ganjingzi landslide in the Three Gorges Reservoir. The effects of the risk mitigation works are also discussed. [ABSTRACT FROM AUTHOR]

The impoundment of reservoirs in canyons can aggravate the destruction of bank slopes. The Xingguang village landslide is located on the Xiluodu Reservoir in the lower reaches of the Jinsha River. It has deformed continuously since impoundment of the reservoir in 2012, and it seriously threatens the operational safety of the Xiluodu hydropower station. Its temporal and spatial deformation characteristics and its deformation mechanism have not been systematically monitored and explained. In this paper, the movement directions were identified based on the time-series cumulative displacement maps and the landslide is further partitioned into different sections by combining geomorphological data, stratigraphic occurrence, and lithological characteristics. The horizontal and vertical displacement characteristics of the two sections of the Xingguang village landslide were obtained by ascending and descending track interferometric synthetic aperture radar (InSAR) observation results and two-dimensional decomposition functions, and the results were further verified by a field survey and unmanned aerial vehicle (UAV) photography. The results show that the lithologic combination of alternating soft and hard anticline strata and the high steep bank slope cut by the Jinsha River are the internal factors responsible for the development of the Xingguang village landslide. The softening of the strata caused by water storage and the pressure difference caused by water level fluctuations reduce the slope stability. This study provides a new technical path to obtain the direction of landslide movement through time-series cumulative displacement maps and stratigraphic information and then identifies rock toppling in a remote way, which is of great significance for the prevention and control of rocky slope failures in canyon reservoir areas. [ABSTRACT FROM AUTHOR]

This paper proposes a multidimensional landslide warning method based on statistical and physical models. Firstly, the least square linear fitting (LSF), quantile regression (QR), and logistic regression (LR) methods are used to establish the cumulative rainfall-duration-mean intensity (E-D-I) threshold models based on the rainfall landslide events in Sangzhi County, Hunan Province, from 1987 to 2007, which improve the threshold precision compared with traditional I-D analysis. Then, the thresholds are quantitatively compared using list skill scores and receiver operating characteristic (ROC) curves. The results show that the skill score of TLR for E-D performed the best, indicating that the corresponding threshold equation is the most suitable for Sangzhi County. Further, the improved SINMAP model is used to analyze the slope stability for Liyuan, Sangzhi County, under four rainfall return periods of 5, 10, 20, and 50 years. By the relationship between rainfall and landslide instability probability, the rainfall threshold inducing the landslide in Liyuan Town is determined to be 120 mm/day. Finally, the landslide events from 2008 to 2017 in the SINMAP model are extracted to verify the appropriateness of the threshold equation. At least 75% (in fact, 100% of TLR for E-D) of the landslide events are above all thresholds of 0.5 percentile. The converted I-D thresholds share similar trends compared with similar working areas globally. The multidimensional threshold proposed can provide a theoretical basis for preventing and managing landslide disasters in Sangzhi County, which is of significant academic value and has practical implications. [ABSTRACT FROM AUTHOR]

Toppling is a kind of failure mode that commonly exists in anti-dip rock slopes. Toppling deformation has a great influence on the stability of rock slopes, which often leads to geological disasters such as sliding and collapse of anti-dip slopes. However, a large number of faults and other structural planes will be produced in many rock slopes due to the action of geological structure movement. In the investigation, it is found that there are not only toppling deformation, but also faults and other geological structures in the toppling deformation rock slope. Previous studies have calculated the depth of toppling deformation, which is considered from the development characteristics of toppling deformation itself. In this paper, based on the field investigation of the anti-dip rock slope with bedding faults, the relationship between the depth of toppling deformation and the location of faults is analyzed by three-dimensional discrete element method. When the dominant structural plane and toppling fracture surface exist at the same time, the main factors affecting the failure of the reverse dip rock slope can be obtained by determining the different depths of the two planes. The final failure depth and failure mode of the toppling deformation in an anti-dip rock slope with a dominant structural plane can be preliminarily determined. [ABSTRACT FROM AUTHOR]

The decomposition of natural gas hydrate will reduce the cementation effect of hydrate and produce ultra-static pore pressure, which will change the mechanical characteristics of the reservoir. Eventually, a series of geological disasters could be triggered, of which the submarine landslide is a typical example. In order to analyze the stability of hydrate-bearing submarine slopes and to explore the internal relationship between hydrate decomposition and submarine landslides, a "two-step reduction method" was described in this paper. This method was based on a strength reduction approach, which can be used to assess the effects of the initial geostress balance and hydrate decomposition on substrate strength reduction. This method was used to reveal the essence of hydrate decomposition, and then, a joint operation mode of multi-well was proposed. The internal relationship between hydrate decomposition and submarine landslides was analyzed in detail. And the development process and mechanism of submarine landslide were deeply discussed. The results showed that hydrate decomposition is a dynamic process of stress release and displacement, where the "stress inhomogeneity" distributed along the slope is transformed into "displacement inhomogeneity." We concluded that hydrate decomposition could trigger a submarine landslide, especially along a sliding surface. The formation of submarine landslide is a gradual development process and presents the dual characteristics of time and space. [ABSTRACT FROM AUTHOR]

Multi-dimensional, long-term time series displacement monitoring is crucial for generating early warnings for active landslides and for mitigating geohazards. The synthetic aperture radar (SAR) interferometry method has been widely applied to achieve small-gradient landslide displacement monitoring; however, measuring the landslide displacement with a steep gradient has posed certain challenges. In comparison, the SAR offset tracking method is a powerful tool for mapping large-gradient landslide displacement in both the slant-range and azimuth directions. Nevertheless, there are some limitations in the existing SAR offset tracking approaches: (i) the measurement accuracy is greatly reduced by the extreme topography relief in high mountain areas, (ii) a fixed matching window from expert experience is usually adopted in the calculation of cross-correlation, (iii) estimating the long-term displacements between the SAR images from cross-platforms and with longer spatiotemporal baselines is a challenging task, and (iv) it is difficult to calculate the three-dimensional (3D) landslide displacements using a single SAR dataset. Additionally, only a few studies have focused on how to realize early warning of landslide deformation using SAR measurements. To address these issues, this paper presents an improved cross-platform SAR offset tracking method, which can not only estimate high-precision landslide displacements in two and three dimensions but also calculate long-term time series displacements over a decade using cross-platform SAR offset tracking measurements. Initially, we optimize the traditional SAR offset tracking workflow to estimate high-precision ground displacements, in which three improvements are highlighted: (i) an "ortho-rectification" operation is applied to restrain the effect of topography relief, (ii) an "adaptive matching window" is adopted in the cross-correlation computation, and (iii) a new strategy is proposed to combine all the possible offset pairs and optimally design the displacement inversion network based on the "optimization theory" of geodetic inversion. Next, robust mathematical equations are built to estimate the two-dimensional (2D) and 3D long-term time series landslide displacements using cross-platform SAR observations. The M-estimator is introduced into the 2D displacement inversion equation to restrain the outliers, and the total least squares criterion is adopted to estimate the 3D displacements considering the random errors in both the design matrix and observations. We take the Laojingbian landslide, Wudongde Reservoir Area (China), as an example to demonstrate the proposed method using ALOS/PALSAR-1 and ALOS/PALSAR-2 images. The results reveal that the proposed method significantly outperforms traditional methods. We also retrieve the movement direction of each pixel of the Laojingbian landslide using the proposed method, thus allowing us to understand the fine-scale landslide kinematics. Finally, we capture and analyze the acceleration characteristics of the landslide, perform an early warning of hazard, and forecast the future displacement evolution based on the 3D displacement time series coupled with the physical models of the rocks. [ABSTRACT FROM AUTHOR]

Frequent landslides in the flysch zones along the Adriatic coast commonly develop on the contact between the sound flysch and Quaternary sediments. The reason for this is most often the increased pore pressure and degradation of material due to inadequately regulated surface and groundwater. A case of one such landslide in the south-western part of Montenegro is presented in this paper. The disposal of construction waste materials above the location of the village Podi was followed by the occurrence of a landslide which affected 3.5 ha of slope and damaged 27 houses in the village. In the course of legal proceedings initiated against the contractor, a question arose of whether the deposited material could have triggered the landslide. Response to this complex question required a multidisciplinary approach, including also a numerical parametric analysis. The results of such analysis indicated that the improper depositing of material above the village induced the landslide activation for two reasons: an increase in shear stress and a change in the natural groundwater regime, which in turn affected elevation in the pore water pressure. Numerical analyses indicated that with a moderate water table rising, the factor of safety decreased by some 20%, which in case of an already conditionally stable slope is sufficient to initiate the terrain movement and formation of a landslide on a wider area. [ABSTRACT FROM AUTHOR]

Landslide dams pose enormous risks to the public because of the potentially catastrophic floods generated by breaching of such dams. The need to better understand the threats of landslide dams raises questions about the proper estimation of breaching parameters (breach size, breaching duration, and peak outflow rate) of landslide dams and the feasibility of applying models for estimating the breaching parameters of man-made earthen dams to landslide dams. This paper aims to answer these two questions. In this study, a database of 1,239 landslide dams, including 257 cases formed during the 12 May 2008 Wenchuan earthquake, has been compiled. Based on records of 52 landslide dam cases with breaching information in the database, empirical models for estimating the breaching parameters of landslide dams are developed. A comparison study between landslide dams and man-made earth and rockfill dams is conducted, which shows that the models for man-made earth and rockfill dams are not suitable for estimating the breaching parameters of landslide dams. Two case studies are presented to show the application of the set of empirical models developed in this paper. [ABSTRACT FROM AUTHOR]

Previous studies about probabilistic back analysis for shear strength parameters of landslides generally adopted a fixed slip surface. This setting may lead to unreliable results due to the uncertainty of slip surface location speculated by limited observations. Based on Bayes' theorem, this paper proposes a probabilistic framework for the back analysis of landslides considering slip surface uncertainty. The posterior distributions of shear strength parameters in Bayesian inference are solved by Markov chain Monte Carlo simulation method. To improve computational efficiency, a response surface function based on extreme learning machine is constructed to approximate the relationship between shear strength parameters and the corresponding factor of safety and critical slip surface. A synthetic slope, for which the actual shear strength parameters and slip surface are known, is used to compare the proposed and traditional methods. The effects of measurement error of slip surface and prior distribution of shear strength parameters on probabilistic back analysis results are also investigated. Results show that the shear strength parameters obtained from traditional probabilistic back analyses neglecting slip surface uncertainty significantly deviate from actual values, and are greatly affected by prior mean of shear strength parameters. The proposed method performs better than traditional method and is less affected by the prior distributions of shear strength parameters, and the smaller the measurement error of slip surface, the higher the Bayesian back analysis accuracy. A practical landslide is applied to further verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the artificial bee colony (ABC) algorithm is used to generate landslide susceptibility maps. To the best of our knowledge, it is the first time the ABC algorithm is applied as a classifier on landslide susceptibility mapping. Twelve features are considered as inputs for the ABC model in this research work. These features contain redundant and correlated information. Therefore, normalization and dimension reduction are applied in the pre-processing stage. Three different normalization methods are investigated, i.e. minimum and maximum (Min-Max), mean standard deviation (Mean-SD), and median and interquartile range (Med-IQR). Two dimensionality reduction techniques, i.e., principal component analysis (PCA) and canonical variate analysis (CVA), are utilized to deal with high-dimensional information and eliminate correlated information in the data. In total, six different schemes of input data based on the three normalization methods and two techniques of dimension reduction are applied to train the ABC model. There are a total of 382 landslide incidents occurred at various locations on Penang Island, out of which 255 are selected for training and remaining 127 are used for the validation purpose of the model. The model classification accuracies and receiver of characteristics (ROC) curve are applied to evaluate the model's performance. The results show that the ABC model trained using Min-Max normalization and CVA scheme generates the best results among these six schemes. The landslide susceptibility maps generated in this research offer significant information for landslide risk management. [ABSTRACT FROM AUTHOR]

This paper studies the role of vetiver grass (Vetiveria zizanoides) on the stability of hill slopes through physical and numerical modeling. Vetiver plantation in nutrient-deficient poorly graded sand with silt in a glass model, showing mean root growth of 0.42 m and increase in tillers (shoots) from 3 to 15 after six months, advocates its survival in unfavorable soil conditions. Finite element analysis shows, for the sand/silt, existing 15 m high bare natural slopes are stable up to a slope angle of 30° with a factor of safety of 1.01 and crest deformation of 37.2 mm. Covering the whole slope with vetiver yields a higher factor of safety of 1.17 and nearly 10 mm lower crest deformation as the root zone depth reaches 3.0 m. However, as this positive impact of root's mechanical reinforcement is inhibited beyond the threshold angle of 33.3° yielding factor of safety of 1.06, terraced slopes in combination with vetiver are considered. Compared to sand/silt, vetiver performs better in sandy silt in reducing chances of shallow slope failure at the same geometry of natural slope. This study recommends vetiver as a sustainable and cost-effective approach for restoration of hill slopes along with reducing the risk of shallow slope failures and eventually landslides. [ABSTRACT FROM AUTHOR]

The traditional landslide risk research mostly focuses on the spatial distribution of landslide occurrence probability, but the research on the time distribution of landslide occurrence probability is not in-depth, and there is no effective professional management advice for specific risk areas, so it has great limitations. This paper takes the landslide-prone area along the Qingjiang River in Jianshi County, Hubei Province as the research area, takes the slope as the unit, and uses the information value method to complete the landslide geological disaster risk assessment in the study area. Through the characteristics of landslide risk in time and space, the dynamic management measures of landslide risk in different periods of the study area are formulated. The map of landslide prevention and control planning measures in different periods in the study area can be obtained, which provides a basis for realizing the balance between safety and economy of landslide prevention and control planning. This has obvious guiding significance for landslide prevention and control planning in other regions. [ABSTRACT FROM AUTHOR]

Long-runout landslides can be extremely hazardous and unpredictable. The prediction of long-runout landslides is challenging because it is unclear what factors control their mobility, and it is unclear how to best measure their runout given that they traverse changing topography. In this paper, we document the development and statistical evaluation of a Landslide Runout Score (LRS) system to predict short, medium, and long runout using a new mobility measure, the unitless Runout Number L/A1/2 (where L is landslide length and A is landslide area). The Runout Number has previously been correlated to three geomorphological factors (planimetric curvature, sand content, and upslope contributing area normalized to landslide area), so the LRS uses these factors as inputs. These factors are readily calculated using geographic information systems (GIS) and publicly available data sources. The LRS system predicts runout categories (short, medium, and long) with one-vs.-all accuracies (i.e., percentage of correct predictions within a given class) of 75, 58, and 72%, respectively, for a total weighted accuracy of approximately 65%. The results of this work are summarized in a worksheet that can be used by geologists and engineers to develop preliminary predictions of landslide runout behavior, which can be incorporated into or used alongside regional-scale landslide hazard assessments. [ABSTRACT FROM AUTHOR]