Search Results (290)

Precise classification of landslide types is critical for targeted hazard mitigation, although the absence of type-specific classifications in many existing inventories limits their utility for effective risk management. This study develops a transferable machine learning approach to identify cliff-type landslides from unclassified records, with a focus on earthquake-prone regions. Using the Forest-based and Boosted Classification and Regression (FBCR) tools in ArcGIS Pro, a model was trained on 167 landslide points and 167 non-landslide points from Tokushima Prefecture, Japan. The model achieved high predictive performance, with 84% accuracy and sensitivity, an F1 score of 84%, and a Matthews correlation coefficient (MCC) of 0.68. The trained model was applied to the Kegalle District, Sri Lanka, and validated against a recently updated inventory specifying landslide types, resulting in an accuracy of 80.1%. It also enabled retrospective identification of cliff-type landslides in older inventories, providing valuable insights for early hazard assessment. Spatial analysis showed strong correspondence between predicted cliff-type zones and key conditioning factors, including specific elevation ranges, steep slopes, high soil thickness, and proximity to roads and buildings. This study integrates FBCR-based modelling with a cross-regional application framework for cliff-type landslide classification, offering a practical, transferable tool for refining inventories, guiding countermeasures, and improving preparedness in regions with similar geomorphological and seismic settings. Full article

Earthquake hazards, such as strong ground motion, liquefaction, and landslides, pose significant threats to structures built on seismically vulnerable, loose, and saturated sandy soils. Therefore, a structural failure evaluation method that accounts for site-specific seismic responses is essential for developing effective and appropriate earthquake hazard mitigation strategies. In this study, a real-time assessment framework for structural seismic susceptibility is developed. To evaluate structural susceptibility to earthquakes, seismic fragility functions are employed as thresholds for structural failure and are linked to a geotechnical spatial grid that incorporates correlation equations for seismic load determination. The real-time assessment consists of the following procedures. First, the geotechnical spatial grid is constructed based on the geostatistical method to estimate the site-specific site response to be correlated with the earthquake hazard potential. Second, the peak ground accelerations are determined from seismic load correlation and assigned to the geotechnical spatial grid. Third, the damage grade of structure is determined by calculating the failure probabilities of defined damage levels and integrating the geotechnical spatial grids for the target structure in real time. The proposed assessment was simulated at Incheon Port, South Korea, using both an actual earthquake event (the 2017 Pohang Earthquake) and a hypothetical earthquake scenario. Full article

Oil and gas pipelines represent critical infrastructure for energy transportation and are essential for ensurin g energy security. The seismic disaster risk assessment of these pipelines is of paramount importance for safeguarding energy supplies. Traditional assessment methodologies primarily focus on the structural integrity of the pipeline body, often neglecting the impact of auxiliary structures and site-specific disaster effects. This study proposes an enhanced risk assessment methodology to address these gaps. This research systematically compiles seismic damage case studies of pipelines from major seismic zones in China. By considering the interactions between auxiliary structure types, site conditions, and forms of disasters, 15 typical operating conditions are identified, and a seismic damage case database is constructed. We develop a failure probability model that integrates geotechnical parameters, structural responses, and ground motion characteristics to assess the impact of liquefaction, site amplification, fault activity, and collapse/landslide phenomena. Utilizing Particle Swarm Optimization (PSO) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) algorithms, this model quantifies the influence weights and coefficients of these disasters on pipeline auxiliary structures, forming a vulnerability matrix centered around Peak Ground Acceleration (PGA). Additionally, a dual-vulnerability assessment framework is established, and a failure probability formula accounting for the superposition effects of multiple disasters is proposed. This study marks a significant advancement, transitioning from traditional single-pipeline evaluations to “structure-disaster-site” coupling analysis, and provides a scientific basis for pipeline seismic design, operation, and maintenance under specific environmental conditions. This work contributes to the development of quantitative and refined seismic risk assessments for oil and gas pipelines. Full article

Understanding the dynamic response and failure mechanisms of rock slopes during earthquakes is crucial in sustainable geohazard prevention and mitigation engineering. The initiation of landslides involves complex interactions between seismic wave propagation, dynamic rock mass behavior, and crack network evolution, and these interactions are heavily influenced by the slope geometry, lithology, and structural parameters of the slope. However, systematic studies remain limited due to experimental challenges and the inherent variability of landslide scenarios. This study employs Discrete Element Method (DEM) modeling to comprehensively investigate how geological structure parameters control the dynamic amplification and deformation characteristic of typical bedding/anti-dip layered slopes consist of parallel distributed rock masses and joint faces, with calibrated mechanical properties. A soft-bond model (SBM) is utilized to accurately simulate the quasi-brittle rock behavior. Numerical results reveal distinct dynamic responses between bedding and anti-dip slopes, where local amplification zones (LAZs) act as seismic energy concentrators, while potential sliding zones (PSZs) exhibit hindering effects. Parametric analyses of strata dip angles and thicknesses identify a critical dip range where slope stability drastically decreases, highlighting high-risk configurations for earthquake-induced landslides. By linking the slope failure mechanism to seismic risk reduction strategies, this work provides practical guidelines for sustainable slope design and landslide mitigation in tectonically active regions. Full article

Coseismic landslides are geological events in which slopes, either on the verge of instability or already in a fragile state, experience premature failure due to seismic shaking. On 5 September 2022, an Ms 6.8 earthquake struck Luding County, Sichuan Province, China, triggering numerous landslides that caused severe casualties and property damage. This study systematically interprets 13,717 coseismic landslides in the Luding earthquake’s epicentral area, analyzing their spatial distribution concerning various factors, including elevation, slope gradient, slope aspect, plan curvature, profile curvature, surface cutting degree, topographic relief, elevation coefficient variation, lithology, distance to faults, epicentral distance, peak ground acceleration (PGA), distance to rivers, fractional vegetation cover (FVC), and distance to roads. The analytic hierarchy process (AHP) was improved by incorporating frequency ratio (FR) to address the subjectivity inherent in expert scoring for factor weighting. The improved AHP, combined with the Pearson correlation analysis, was used to identify the dominant controlling factor and assess the landslide susceptibility. The accuracy of the model was verified using the area under the receiver operating characteristic (ROC) curve (AUC). The results reveal that 34% of the study area falls into very-high- and high-susceptibility zones, primarily along the Moxi segment of the Xianshuihe fault and both sides of the Dadu river valley. Tianwan, Caoke, Detuo, and Moxi are at particularly high risk of coseismic landslides. The elevation coefficient variation, slope aspect, and slope gradient are identified as the dominant controlling factors for landslide development. The reliability of the proposed model was evaluated by calculating the AUC, yielding a value of 0.8445, demonstrating high reliability. This study advances coseismic landslide susceptibility assessment and provides scientific support for post-earthquake reconstruction in Luding. Beyond academic insight, the findings offer practical guidance for delineating priority zones for risk mitigation, planning targeted engineering interventions, and establishing early warning and monitoring strategies to reduce the potential impacts of future seismic events. Full article

As a globally renowned alpine gorge region and seismically active zone, the eastern margin of the Qinghai–Tibet Plateau (QTP) is highly prone to landslide dam formation. Considering unstable landslide dams often pose catastrophic risks to downstream areas, current research on landslide dams along QTP primarily focuses on the breach mechanisms of unstable dams, while studies on the formation mechanisms of stable landslide dams—which can provide multiple benefits to downstream regions—remain limited. This paper selected the Conaxue Co landslide dam on the eastern margin of the QTP as one case example. Field investigation, sampling, numerical simulation, and comprehensive analysis were carried out to disclose its formation mechanisms. Field investigation shows that the Conaxue Co landslide dam was formed by a high-speed long-runout landslide blocking the river, with its structure exhibiting a typical inverse grading pattern characterized by coarse-grained rock overlying fine-grained layers. The inverse grading structure plays a critical role in the stability of the Conaxue Co landslide dam. On one hand, the coarse, hard rock boulders in the upper dam mitigate fluvial erosion of the lower fine-grained sediments. On the other hand, the fine-grained layer in the lower dam acts as a relatively impermeable aquitard, preventing seepage of dammed lake water. Additionally, the step-pool system formed in the spillway of the Conaxue Co landslide dam contributes to the protection of the dam structure by dissipating 68% of the river’s energy (energy dissipation rate η = 0.68). Understanding the formation mechanisms of the Conaxue Co landslide dam can provide critical insights into managing future landslide dams that may form in the QTP, both in emergency response and long-term strategies. Full article

Most public seismic recordings, sampled at hundreds of Hz, tend to be unlabelled, i.e., not catalogued, mainly because of the sheer volume of samples and the amount of time needed by experts to confidently label detected events. This is especially challenging for very low signal-to-noise ratio microseismic events that characterise landslides during rock and soil mass displacement. Whilst numerous supervised machine learning models have been proposed to classify landslide events, they rely on a large amount of labelled datasets. Therefore, there is an urgent need to develop tools to effectively automate the data-labelling process from a small set of labelled samples. In this paper, we propose a semi-supervised method for labelling of signals recorded by seismometers that can reduce the time and expertise needed to create fully annotated datasets. The proposed Siamese network approach learns best class-exemplar anchors, leveraging learned similarity between these anchor embeddings and unlabelled signals. Classification is performed via soft-labelling and thresholding instead of hard class boundaries. Furthermore, network output explainability is used to explain misclassifications and we demonstrate the effect of anchors on performance, via ablation studies. The proposed approach classifies four landslide classes, namely earthquakes, micro-quakes, rockfall and anthropogenic noise, demonstrating good agreement with manually detected events while requiring few training data to be effective, hence reducing the time needed for labelling and updating models. Full article

Earthquake-triggered landslides pose significant hazards to lives and infrastructure. While existing seismic landslide models primarily focus on seismic and terrain variables, they often overlook the dynamic nature of hydrologic conditions, such as seasonal soil moisture variability. This study addresses this gap by incorporating satellite-based soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission into the assessment of seismic landslide occurrence. Using landslide inventories from five major earthquakes (Nepal 2015, New Zealand 2016, Papua New Guinea 2018, Indonesia 2018, and Haiti 2021), a balanced global dataset of landslide and non-landslide cases was compiled. Exploratory analysis revealed a strong association between elevated pre-event soil moisture and increased landslide occurrence, supporting its relevance in seismic slope failure. Moreover, a Random Forest model was trained and tested on the dataset and demonstrated excellent predictive performance. To assess the generalizability of the model, a leave-one-earthquake-out cross-validation approach was also implemented, in which the model trained on four events was tested on the fifth. This approach outperformed comparable models that did not consider soil moisture, such as the United States Geological Survey (USGS) seismic landslide model, confirming the added value of satellite-based soil moisture data in improving seismic landslide susceptibility assessments. Full article

The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article

The present paper deals with an inhabited, creeping mountainous landmass with profound surface deformation that affects the local community. The scope of the paper is to gather surficial and subsurface information in order to understand the parameters of this creeping mass, which is usually affected by several parameters, such as its geometry, subsurface water, and shear zone. Therefore, a combined aerial and surface investigation has been conducted. The aerial investigation involves UAV’s LiDAR acquisition for the terrain model and a comparison of historical aerial photographs for land use changes. The multi-technique surface investigation included resistivity (ERT) and seismic (SRT, MASW) measurements and density determination of geological formations. This combination of methods proved to be fruitful since several aspects of the landslide were clarified, such as water flow paths, the internal geological structure of the creeping mass, and its geometrical extent. The depth of the shear zone of the creeping mass is delineated at the first five to ten meters from the surface, especially from the difference in diachronic resistivity change. Full article

As is already known, some currently stable landslides may have been activated in the past along a pre-existing sliding surface and reached the residual strength there, as a consequence of high-cumulative displacements. After a fairly long period of quiescence, these landslides can reactivate due to a temporary increase in destabilising forces capable of mobilising the residual strength along the same sliding surface again. Some recent studies have suggested that, under certain conditions, the strength mobilised upon reactivation may slightly exceed the residual value and then decay towards the latter as the displacement progresses. Regarding this matter, many previous studies have hypothesised that some geotechnical variables could affect the recovered strength more significantly: the length of the ageing time, the vertical stress, the stress history, and the speed with which the reactivation occurs. The aim of this research is to confirm whether such recovery of strength upon reactivation is possible and which geotechnical parameters have the greatest influence on the process. To this end, laboratory tests were carried out with the Bromhead ring shear apparatus on normally consolidated saturated samples of both natural soils and clays provided by industry (bentonite and kaolin). The coupling effect of the ageing time, the vertical stress, and the reactivation speed on the mobilised strength upon reactivation were investigated, starting from a pre-existing residual state of these samples. Within the limits of this research, the results seem to confirm that all three geotechnical variables are influential, with a greater impact on the reactivation speed and, subordinately, on the ageing time for long quiescence periods. Therefore, it is concluded that a quiescent landslide could show a reactivated strength slightly higher than the residual value if the destabilising action could arise with a certain rapidity. Conversely, if the destabilising action occurs very slowly, the mobilised strength could correspond to the residual value. The experimental results of this research may find some application in the design of strengthening works for a stable quiescent landslide that could experience a fairly rapid increase in destabilising actions, such as in the case of seismic stress, morphological modification of the slope, or a rising water table. Full article

We inspected a sector of the Apennines (central–southern Italy) in geographic and structural continuity with the Quaternary-active extensional belt but where clear geomorphic and seismological signatures of normal faulting are unexpectedly missing. The evidence of active tectonics in this area, between Abruzzo and Molise, does not align with geodetic deformation data and the seismotectonic setting of the central Apennines. To investigate the apparent disconnection between active deformation and the absence of surface faulting in a sector where high lithologic erodibility and landslide susceptibility may hide its structural evidence, we combined multi-scale and multi-source data analyses encompassing morphometric analysis and remote sensing techniques. We utilised high-resolution topographic data to analyse the topographic pattern and investigate potential imbalances between tectonics and erosion. Additionally, we employed aerial-photo interpretation to examine the spatial distribution of morphological features and slope instabilities which are often linked to active faulting. To discern potential biases arising from non-tectonic (slope-related) signals, we analysed InSAR data in key sectors across the study area, including carbonate ridges and foredeep-derived Molise Units for comparison. The topographic analysis highlighted topographic disequilibrium conditions across the study area, and aerial-image interpretation revealed morphologic features offset by structural lineaments. The interferometric analysis confirmed a significant role of gravitational movements in denudating some fault planes while highlighting a clustered spatial pattern of hillslope instabilities. In this context, these instabilities can be considered a proxy for the control exerted by tectonic structures. All findings converge on the identification of an ~20 km long corridor, the Castel di Sangro–Rionero Sannitico alignment (CaS-RS), which exhibits varied evidence of deformation attributable to active normal faulting. The latter manifests through subtle and diffuse deformation controlled by a thick tectonic nappe made up of poorly cohesive lithologies. Overall, our findings suggest that the CaS-RS bridges the structural gap between the Mt Porrara–Mt Pizzalto–Mt Rotella and North Matese fault systems, potentially accounting for some of the deformation recorded in the sector. Our approach contributes to bridging the information gap in this complex sector of the Apennines, offering original insights for future investigations and seismic hazard assessment in the region. Full article

This research paper presents an assessment of geohazards on Lefkas Island, Greece, using Geographic Information System (GIS) technology to map risk and enhance public awareness through an interactive web application. Natural hazards such as landslides, floods, wildfires, and desertification threaten both the safety of residents and the island’s tourism-dependent economy, particularly due to its seismic activity and Mediterranean climate. By combining the Sendai Framework for Disaster Risk Reduction with GIS capabilities, we created detailed hazard maps that visually represent areas of susceptibility and provide critical insights for local authorities and the public. The web application developed serves as a user-friendly platform for disseminating hazard information and educational resources, thus promoting community preparedness and resilience. The findings highlight the necessity for proactive land management strategies and community engagement in disaster risk reduction efforts. This study underscores GIS’s pivotal role in fostering informed decision making and enhancing the safety of Lefkas Island’s inhabitants and visitors in the face of environmental challenges. Full article

Urban expansion in coastal areas involves infrastructure development, industrial growth, and mining activities. These coastal environments face various environmental and geological hazards that require geo-engineers to devise solutions. An integrated geophysical approach aims to address such complex challenges as sea level rise, sea water intrusion, shoreline erosion, landslides and previous anthropogenic activity in coastal settings. In this study, the proposed methodology involves the systematic application of geophysical methods (FDEM, 3D GPR, 3D ERT, seismic), starting with a broad-scale survey and then proceeding to a localized exploration, in order to identify lithostratigraphy, bedrock depth, sea water intrusion and detect anthropogenic buried features. The critical aspect is to leverage the unique strengths and limitations of each method within the coastal environment, so as to derive valuable insights for survey design (extension and orientation of measurements) and data interpretation. The coastal zone of Throrikos valley, Attica, Greece, serves as the test site of our geophysical investigation methodology. The planning of the geophysical survey included three phases: The application of frequency-domain electromagnetic (FDEM) and 3D ground penetrating radar (GPR) methods followed by a 3D electrical resistivity tomography (ERT) survey and finally, using the seismic refraction tomography (SRT) and multichannel analysis of surface waves (MASW). The FDEM method confirmed the geomorphological study findings by revealing the paleo-coastline, superficial layers of coarse material deposits and sea water preferential flow due to the presence of anthropogenic buried features. Subsequently, the 3D GPR survey was able to offer greater detail in detecting the remains of an old marble pier inland and top layer relief of coarse material deposits. The 3D ERT measurements, deployed in a U-shaped grid, successfully identified the anthropogenic feature, mapped sea water intrusion, and revealed possible impermeable formation connected to the bedrock. ERT results cannot clearly discriminate between limestone or deposits, as sea water intrusion lowers resistivity values in both formations. Finally, SRT, in combination with MASW, clearly resolves this dilemma identifying the lithostratigraphy and bedrock top relief. The findings provide critical input for engineering decisions related to foundation planning, construction feasibility, and preservation of coastal infrastructure. The methodology supports risk-informed design and sustainable development in areas with both natural and cultural heritage sensitivity. The applied approach aims to provide a complete information package to the modern engineer when faced with specific challenges in coastal settings. Full article

Landslides pose significant risks to human life and infrastructure, driven by a complex interplay of geological and hydrological factors. This study investigates the ongoing slope instability affecting the village of Borrano, in Central Italy, where large-scale landslides are triggered or reactivated by extreme rainfall and seismic activity. A multidisciplinary approach was employed, integrating traditional geological surveys, direct investigations, and advanced geophysical techniques—including electrical resistivity tomography (ERT) and seismic refraction tomography (SRT)—to characterize subsurface structures. Additionally, Sentinel-1 interferometric synthetic aperture radar (InSAR) was employed to parametrize the deformation rates induced by the landslide. The results reveal a complex geological framework dominated by the Teramo Flysch, where weak clayey facies and structurally controlled dip-slopes predispose the area to gravitational instability. ERT and SRT identified resistivity and velocity contrasts associated with shallow and depth sliding surfaces. At the same time, satellite-based synthetic aperture radar (SAR) data confirmed persistent slow movements, with vertical displacement rates between −10 and −24 mm/year. These findings underscore the importance of lithological heterogeneity and structural settings in the evolution of landslides. The integrated geophysical and remote sensing approach enhances the understanding of slope dynamics. It can be used to cross-check interpretations, capture displacement trends, characterize the internal structure of unstable slopes, and resolve the limitations of each method. This synergy provides a more comprehensive assessment of complex slope instability, offering valuable insights for hazard mitigation strategies in landslide-prone areas. Full article