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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: 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]

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]

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]

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]

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]

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]

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]

Rapid detection of landslides using remote sensing images plays a key role in hazard assessment and mitigation. Many deep convolutional neural network-based models have been proposed for this purpose; however, for small-scale landslide detection, excessive convolution and pooling process may cause potential texture information loss, which can lead to misclassification of landslide target. In this paper, we present a novel UNet model for the automatic detection of landslides, wherein the reversed image pyramid features (RIPFs) are adapted to mitigate the information loss caused by a succession of convolution and pooling. The proposed RIPF-Unet model is trained and validated using the open-source landslides dataset of the Bijie area, Guizhou Province, China, wherein the precision of the proposed model is observed to increase by 3.5% and 4.0%, compared to the conventional UNet and UNet + + model, respectively. The proposed RIPF-Unet model is further applied to the case of the Longtoushan region after the 2014 Ms.6.5 Ludian earthquake. Results show that the proposed model achieves a 96.63% accuracy for detecting landslides using remote sensing images. And the RIPF-Unet model is also advanced in its compact parameter size; notably, it is 31% lighter compared to the UNet + + model. [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]

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]

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]

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]

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]

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 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]

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]

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]

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]

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]

Landslide warning models are important for mitigating landslide risks. The rainfall threshold model is the most widely used early warning model for predicting rainfall-triggered landslides. Recently, the rainfall threshold model has been coupled with the landslide susceptibility (LS) model to improve the accuracy of early warnings in the spatial domain. Existing coupled models, designed based on a matrix including predefined rainfall thresholds and susceptibility levels, have been used to determine the warning level. These predefined classifications inevitably have subjective rainfall thresholds and susceptibility levels, thus affecting the probability distribution information and eventually influencing the reliability of the produced early warning. In this paper, we propose a novel landslide warning model in which the temporal and spatial probabilities of landslides are coupled without predefining the classified levels. The temporal probability of landslides is obtained from the probability distribution of rainfall intensities that triggered historical landslides. The spatial probability of landslides is then obtained from the susceptibility probability distribution. A case study shows that the proposed probability-coupled model can successfully provide hourly warning results before the occurrence of a landslide. Although all three models successfully predicted the landslide, the probability-coupled model produced a warning zone comprising the fewest grid cells. Quantitatively, the probability-coupled model produced only 39 grid cells in the warning zone, while the rainfall threshold model and the matrix-coupled model produced warning zones including 81 and 49 grid cells, respectively. The proposed model is also applicable to other regions affected by rainfall-induced landslides and is thus expected to be useful for practical landslide risk management. [ABSTRACT FROM AUTHOR]

A landslide is the movement of rock, debris or earth down along the slope under the gravity. It may cause to loss of people's life and their private and public properties. Landslide is a common hazard in steep slope areas, especially during the rainy season. A study of landslide helps urban planners, engineers and local communities to reduce losses caused by existing and future landslides by means of prevention, mitigation and avoidance. Therefore, the prime aim of this paper is to produce acceptable landslide hazard map for Chenab valley, Jammu and Kashmir. Semiautomatic extraction of the landslide is a suitable method that has been used in this paper to extract the location and extent of the landslides. IRS LISS-IV and CartoDEM have been used for object-based image analysis to extract and prepare a landslide inventory map. About 84 landslide potential sites have been identified by the semiautomatic extraction approach. Landslide numerical risk factor model is derived by using thirteen thematic layers with landslide inventory to prepare the landslide hazard map. The result showed that 21% area of the Chenab valley is falling under the very high hazard zone category of the landslide. The final result of the investigation will definitely be useful in the decision-making procedure at the time of emergency and will be used to prepare a preparedness plan for high-risk areas of Chenab valley. The ROC curve method is used for accuracy assessment that signifies the acceptable result for landslide susceptibility zonation of Chenab valley with 0.956 AUC value. [ABSTRACT FROM AUTHOR]

Natural dams are formed when landslides are triggered by heavy rainfall during extreme weather events in the mountainous areas of Taiwan. During landslide debris movement, two processes occur simultaneously: the movement of landslide debris from a slope onto the riverbed and the erosion of the debris under the action of high-velocity river flow. When the rate of landslide deposition in a river channel is higher than the rate of landslide debris erosion by the river flow, the landslide forms a natural dam by blocking the river channel. In this study, the effects of the rates of river flow erosion and landslide deposition (termed the erosive capacity and depositional capacity, respectively) on the formation of natural dams are quantified using a physics-based approach and are tested using a scaled physical model. We define a dimensionless velocity index vde as the ratio between the depositional capacity of landslide debris (vd) and the erosive capacity of water flow (ve). The experimental test results show that a landslide dam forms when landslide debris moves at high velocity into a river channel where the river-flow velocity is low, that is, the dimensionless velocity index vde > 54. Landslide debris will not have sufficient depositional capacity to block stream flow when the dimensionless velocity index vde < 47. The depositional capacity of a landslide can be determined from the slope angle and the friction of the sliding surface, while the erosive capacity of a dam can be determined using river flow velocity and rainfall conditions. The methodology described in this paper was applied to seven landslide dams that formed in Taiwan on 8 August 2009 during Typhoon Morakot, the Tangjiashan landslide dam case, and the Yingxiu-Wolong highway K24 landslide case. The dimensionless velocity index presented in this paper can be used before a rainstorm event occurs to determine if the formation of a landslide dam is possible. [ABSTRACT FROM AUTHOR]

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The paper describes the recent devastating landslide of Kotrupi, Himachal Pradesh in India which had claimed many human lives and properties along its course on 13 August 2017. This event was the third reactivation of the slide as per data available. The study for this landslide involves a preliminary investigation of the site and comparison of pre- and post-event slope stability analysis. Other than rainfall, the combined effect of differential weathering rate of the debris and soil layers, low material strength, and the presence of a fault zone was found to be the primary cause of instability. The analysis was carried out with the geotechnical investigation and numerical modeling with the help of finite element model-based Phase 2 simulator. The significant findings of this paper include numerical simulation of pre- and post-event slide as stated under unsaturated and saturated condition. The study finds a low factor of safety of the present slope. The unstable condition of the slope may trigger another event of the same intensity shortly. [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]

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]

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]

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]

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]

Interferometric Synthetic Aperture Radar (InSAR) technology is capable of detecting large areas of potentially unstable slopes. However, traditional time-series InSAR methods yield fewer valid measurement points (MPs) in alpine canyon regions. Distributed Scatterer (DS) Interferometry (DSI) technology serves as a potent tool for monitoring surface deformation in complex land cover areas; nonetheless, it grapples with high computational demands and low efficiency when interpreting deformation across extended time series. This study proposes an image compression–based DSI (ICDSI) method, which, building upon the DSI method, utilizes principal component analysis (PCA) to compress multi-temporal SAR images in the time dimension. It develops a module for compressing long-time sequence SAR images, acquires the compressed image (referred to as a virtual image), and integrates the developed image compression module into the DSI data processing flow to facilitate the inversion of long-time sequence InSAR land surface deformation information. To validate and assess the credibility of the ICDSI method, we processed a total of 78 ascending and 81 descending scenes of Sentinel-1A images spanning the period 2019–2021 using Small Baseline Subset (SBAS), DSI, and the ICDSI method proposed in this paper. Subsequently, these methods were applied to detect landscape displacements on both coasts of the Jinsha River Basin. The investigation reveals that the ICDSI method outperforms SBAS and DSI significantly in monitoring landslide displacements, enabling the detection of more measurement points (MPs) while utilizing less raw data. The accomplishments of this research program carry crucial theoretical implications and practical application value for the detection of surface deformation using long-time series InSAR. [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]

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]

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]

Since 2008, the water level of the Three Gorges Reservoir has been periodically fluctuating between 175 and 145 m. The rise and fall of the reservoir water level result in changes in the seepage field in the slopes on both banks of the reservoir. Groundwater is an important factor affecting the stability and reactivation of landslides. Developing a method to accurately determine the location of the groundwater saturation line is crucial to the evaluation and prediction of landslide stability. In this paper, the phreatic line under the condition of steady seepage is used as the initial value for unsteady seepage, and the analytical solution for the phreatic line on the bank’s slope under the action of reservoir water level changes is mainly modified based on two assumptions about the rate of change in the reservoir water level and the slope of the bank. In addition, through a large number of indoor tests, the relationship between the water yield, the permeability coefficient, and the porosity of the landslide in the Three Gorges Reservoir area is studied in detail, and a formula for the water yield of a soil–rock mixture is proposed. Finally, the modified analytical solution is used to determine the phreatic line in the Shiliushubao landslide, and the results are compared with the numerical analysis and monitoring results. The results show that the modified analytical solution is closer to the actual situation of the phreatic line in the reservoir water level fluctuation zone. [ABSTRACT FROM AUTHOR]

Aspect ratio is an elementary parameter widely adopted to characterize landslide geometry. Nevertheless, it in essence reflects an overall elongation of landslide only, and cannot reflect the variation of width along the central line of movement. This paper proposes the new concept "landslide longitudinal shape" for complementing the landslide aspect ratio, and develops the methodology for interpreting it based on generation and analysis of the landslide profile. Relative width change and relative width fluctuation are defined as parameters quantitatively describing landslide longitudinal shape, and five different types of shape (rectangle, widening, narrowing, spindle, and hourglass) are predefined for qualitatively classifying it. A case study showed that landslide longitudinal shape can provide additional information and therefore is a complement to the aspect ratio. Landslides with larger aspect ratios (more elongated) are more possibly characterized by a narrowing overall varying trend and a stronger fluctuation of width. Landslides with similar longitudinal shapes of headscarp zones were found to have transition-deposition zones with diverse longitudinal shapes, which is caused by diverse topographic confinements and forces governing motion. For an unconfined and laterally confined landslide in the study area, its transition-deposition zone is most likely to have a regular and narrowing longitudinal shape, respectively. Longitudinal shape is not just a geometric parameter, but can somehow help to understand motion constraints of landslides. It must be emphasized that the new longitudinal shape concept is not applicable to landslides that show a complex geometry that prevents a clear definition of a longitudinal profile. [ABSTRACT FROM AUTHOR]

Landslide is one of the most morpho-dynamic patterns of slopes in the coastal region of Syria. The assessment of landslide susceptibility is a complex procedure because of limited data and lack of related literature in Syria. Therefore, the current paper explored the landslide susceptibility in Al-Fawar basin, based on remote sensing data in the GIS environment. Inventorization of the current landslide was carried out as points utilizing satellite images, fieldwork, and photographs. Thirteen dominant factors of landslide including slope angle, slope aspect, curvature, plan curvature, profile curvature, elevation, proximity to faults, proximity to streams, proximity to roads, NDVI, rainfall, lithology, and TWI were utilized for landslide susceptibility mapping. In this study, two bivariate statistical models, i.e., frequency ratio (FR) and statistical index (SI), were used for spatial calibration between the resulting inventory map and the geofactors. The quality of models performance in mapping the landslide susceptibility was assessed utilizing receiver operating characteristic (ROC) curves. The prediction accuracy curves showed that the landslide susceptibility map using FR model has the greatest prediction accuracy (AUC = 0.824) compared with SI model that showed 0.801 of AUC. Identically, the success rate curve graph showed that the AUC for FR and SI models was 0.799 and 0.778, respectively. Although the susceptibility assessment utilizing the FR model produced higher accurate output, the validation results indicate that the two models used in this study can be encouraging approaches for the assessment of landslide susceptibility hazard in the Syrian coastal basin, thus fruitfully creating spatial mitigation and conservation measures. [ABSTRACT FROM AUTHOR]

Rainfall-induced landslides are among the most fatal and destructive geological hazards in the mountainous regions where active faulting is a major geological process. So far, many studies have been conducted on the various factors that influence or trigger rainfall-induced landslides; however, lesser attention has been paid to the proximity of rainfall-induced landslides to major faults. First time, this paper is going to discuss the concepts of fault damage zone and fault zone processes that interact and influence the occurrence of rainfall-induced landslides. This is done by introducing the concept of fault damage zone and its architecture and then presenting several examples from high mountains of Alborz and Zagros in which fault zones interact proactively with mass movement processes. Fault zone processes control the rainfall-induced landslides by three ways: (1) increasing fracture density near major faults that produces more debris and reduces rock strength, (2) weak minerals growing in fault zones in which clay minerals grow and (3) topographic features produced by active faulting. Presented examples show how active faulting can influence localization of rainfall-induced landslides. Intensely weathered rocks in the fault zone are a major source of sediment flux combined with the water to form mudflows. Additionally, fault mechanism and movement direction of fault blocks influence on internal geometry and attitude of minor structures is fault zone that controls properties of rock materials in the fault zone and therefore influence on slope strength. The interaction and connectivity among tectonic faults, river systems and erosion is a complex feature that should be considered in modeling landslides in the mountainous regions. [ABSTRACT FROM AUTHOR]