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Machine learning models have been widely used in landslide susceptibility prediction. However, landslide multidimensional feature extraction, model generalization ability, and prediction quantification of deep learning are still challenging. This paper proposes a new approach, the landslide density-based bidirectional long short-term memory (LD-BiLSTM) model with multichannel input and an optimized sampling strategy to predict and map landslide susceptibility in active seismic mountainous areas of Sichuan Province, China. First, to ensure the generalization ability of the LD-BiLSTM model, other regions in Sichuan were selected as the model training area independent of the prediction area (Luding County). Multichannel landslide datasets were constructed to extract high-dimensional geospatial features of landslides. Subsequently, the landslide density of each grid cell was utilized as the label for the corresponding input sample. The LD-BiLSTM model was improved by using transfer learning and sampling optimization strategies, which makes our method attenuate the impact of historical landslide inventory deviation on the spatial susceptibility mode compared with the existing DL model, which usually uses landslide objects (LO) as input sample labels. Model performance evaluation results show that the LD-BiLSTM model (precision = 0.903, recall = 0.899, F1-score = 0.901, Area under receiver operating characteristic curve (AUC) = 0.940) outperformed the LO-BiLSTM model (precision = 0.812, recall = 0.815. F1-score = 0.813, AUC = 0.910) in the case areas. Meanwhile, the performance of the LD-BiLSTM model (AUC = 0.9407) significantly outperformed both the information value (IV) (AUC = 0.7207) model and the random forest (RF) (AUC = 0.8116) models in the landslide prediction area (Luding), which confirms that the proposed LD-based method is superior to traditional LO-based methods. Significantly, our approach can effectively extract the spatial distribution of landslides and predict potential landslides in complex high-mountain environments. [ABSTRACT FROM AUTHOR]

Foreseeing the failure of important unstable volumes is a major concern in the Alps, especially due to the presence of people and infrastructures in the valleys. The use of monitoring and remote sensing techniques is aimed at detecting potential instabilities and the combination of several techniques permits the cross-validation of the detected movements. Supplemented with field mapping and structural analysis, it is possible to define possible scenarios of rupture in terms of volume, mechanisms of failure and susceptibility. A combined observation strategy was applied to the study of major instability located in the Ticinese Alps (Switzerland), Cima del Simano, where the monitoring started in 2006 with the measurement of opened cracks with extensometers. Since 2021, the monitoring has been completed by LiDAR, satellite and GB-InSAR observations and structural analysis. Here, slow but constant movements of about 7 mm/yr were detected along with rockfall activities near the Simano summit. Eight failure scenarios of various sizes ranging from 2.3 × 105 m3 to 51 × 106 m3, various mechanisms (toppling, planar, wedge and circular sliding) and various occurrence probabilities were defined based on the topography and the monitoring results and by applying a Slope Local Base Level (SLBL) algorithm. Weather acquisition campaigns by means of thermologgers were also conducted to suggest possible causes that lead to the observed movements and to suggest the evolution of the instabilities with actual and future climate changes. [ABSTRACT FROM AUTHOR]

This paper presents a new method to estimate a landslide failure surface and its volume based on a digital elevation model (DEM) using spline curves by assuming values of the tangent of the failure surface along with transversal vertical profiles. The model will give the depth of the probable failure surface plotted using the 2D grid function. We can easily visualize the results by running the codes; the display will show the step-by-step processes involved. The model requires fundamental data inputs, which are readily available online throughout the world, such as a DEM of the study area and a KML file of contour limits of the landslide as input. The calculation procedure is simple; it evaluates the depth of the failure surface at each point of the grid. The cross-section for each point is estimated perpendicular to the slope line joining the highest elevation point and the lowest elevation point within the contour limits. A cubic spline curve is calculated using two endpoints and the first derivative at these points. The Z value is calculated using these parameters at each grid point (centre of a grid), and finally, a 3D failure surface is generated, enabling the volume calculation. MATLAB code has been written to execute this process automatically. This model can easily use input data with very little fieldwork, and the processing can produce a result in a few minutes. We can enrich a real scenario by imposing more constraints on the variation in the cross-section angle based on the limit of the landslide using field measurements. This model is also helpful in predicting the area affected by the mass of the failure surface, and we can determine a predefined hazard zone to avoid any casualties in the future. [ABSTRACT FROM AUTHOR]

Many examples of rockfall simulation software provide great flexibility to the user at the expense of a hardly achievable parameter unification. With sensitive site-dependent parameters that are hardly generalizable from the literature and case studies, the user must properly calibrate simulations for the desired site by performing back-calculation analyses. Thus, rockfall trajectory reconstruction methods are needed. For that purpose, a computer-assisted videogrammetric 3D trajectory reconstruction method (CAVR) built on earlier approaches is proposed. Rockfall impacts are visually identified and timed from video footage and are manually transposed on detailed high-resolution 3D terrain models that act as the spatial reference. This shift in reference removes the dependency on steady and precisely positioned cameras, ensuring that the CAVR method can be used for reconstructing trajectories from witnessed previous records with nonoptimal video footage. For validation, the method is applied to reconstruct some trajectories from a rockfall experiment performed by the WSL Institute for Snow and Avalanche Research SLF. The results are compared to previous ones from the SLF and share many similarities. Indeed, the translational energies, bounce heights, rotational energies, and impact positions against a flexible barrier compare well with those from the SLF. The comparison shows that the presented cost-effective and flexible CAVR method can reproduce proper 3D rockfall trajectories from experiments or real rockfall events. [ABSTRACT FROM AUTHOR]

A growing body of research indicates that rock slope failures, particularly from exfoliating cliffs, are promoted by rock deformations induced by daily temperature cycles. Although previous research has described how these deformations occur, full three-dimensional monitoring of both the deformations and the associated temperature changes has not yet been performed. Here we use integrated terrestrial laser scanning (TLS) and infrared thermography (IRT) techniques to monitor daily deformations of two granitic exfoliating cliffs in Yosemite National Park (CA, USA). At one cliff, we employed TLS and IRT in conjunction with in situ instrumentation to confirm previously documented behavior of an exfoliated rock sheet, which experiences daily closing and opening of the exfoliation fracture during rock cooling and heating, respectively, with a few hours delay from the minimum and maximum temperatures. The most deformed portion of the sheet coincides with the area where both the fracture aperture and the temperature variations are greatest. With the general deformation and temperature relations established, we then employed IRT at a second cliff, where we remotely detected and identified 11 exfoliation sheets that displayed those general thermal relations. TLS measurements then subsequently confirmed the deformation patterns of these sheets showing that sheets with larger apertures are more likely to display larger thermal-related deformations. Our high-frequency monitoring shows how coupled TLS and IRT allows for remote detection of thermally induced deformations and, importantly, how IRT could potentially be used on its own to identify partially detached exfoliation sheets capable of large-scale deformation. These results offer a new and efficient approach for investigating potential rockfall sources on exfoliating cliffs. [ABSTRACT FROM AUTHOR]

In this contribution, we present an efficient MATLAB-based implementation of the material point method (MPM) and its most recent variants. MPM has gained popularity over the last decade, especially for problems in solid mechanics in which large deformations are involved, i.e., cantilever beam problems, granular collapses and even large-scale snow avalanches. Although its numerical accuracy is lower than that of the widely accepted finite element method (FEM), MPM has been proven useful in overcoming some of the limitations of FEM, such as excessive mesh distortions. We demonstrate that MATLAB is an efficient high-level language for MPM implementations that solve elasto-dynamic and elasto-plastic problems, such as the cantilever beam and granular collapses, respectively. We report a computational efficiency factor of 20 for a vectorized code compared to a classical iterative version. In addition, the numerical efficiency of the solver surpassed those of previously reported MPM implementations in Julia, ad minima 2.5 times faster under a similar computational architecture. [ABSTRACT FROM AUTHOR]

Superelevation is an often observed phenomenon in landslide and debris flow down a complex three-dimensional topography. The degree of superelevation is controlled by the geometry of the channel, the material involved and also the flow dynamics. Empirical methods are usually applied to estimate superelevation. However, those models are incomplete and lack important aspects of the channel geometry, material properties and flow dynamics, instigating serious errors in estimating flow velocities that could only be controlled empirically by introducing ad hoc correction factors. Here, we present new and complete analytical models for superelevation and superelevation velocities down a general topography providing a fully dynamical method. New models formally include essential forces that play an important role in the flow dynamics, namely gravitational forces, topographic- and hydraulic-pressure gradients and Coulomb friction. We discuss the importance of geometry in inducing superelevation and that one directional channel without twist cannot produce superelevation. With the new models we can, in principle, exactly obtain the flow velocities of deformable landslide, dynamic impact pressures and the explicit description of deposition. We have formally provided two alternative analytical representations for superelevation: geometrical and dynamical definitions of superelevation, which is a new concept. We proved that for superelevation to take place, the transversal velocity must have a gradient across the channel. We have analytically constructed a new non-dimensional superelevation number. Superelevation velocity appears to be a non-linear function of the superelevation number. We can now explicitly quantify the superelevation intensity in landslide motion. It has several implications. We proved that superelevation is higher for fluid-saturated debris flows than for dry granular flows. New superelevation models have been validated against a laboratory granular flow down a multi-dimensionally curved channel, and a natural debris flow event in Chamoson, Valais, Switzerland. Our theoretical superelevation velocities appear to be very close to the velocity measured in laboratory and in the field, which however, are largely overestimated by the empirical models. We further validated the model by constructing an exact analytical solution and by applying it to describe superelevation-induced propagation and deposition of the natural debris flow event. New simulations produced observed propagating fronts. [ABSTRACT FROM AUTHOR]

A new inventory of 66 small and shallow landslides within six pilot areas was created based on a high-resolution digital elevation model in the canton of Vaud in Switzerland. The geometrical characteristics of the landslides were recorded (i.e. surface area, maximum thickness and length), and the volumes were estimated. These data permitted the development of a model that provides the probability for a landslide to possess a maximum thickness or volume smaller than a given value based on the landslide horizontal surface area. The results are compared with three existing power-law relationships of surface area–volumes. This new approach constitutes a way to improve the quantification of the uncertainty of volume and maximum depth estimations for small and shallow landslides. [ABSTRACT FROM AUTHOR]

Reconstructions of failure surfaces (prior to potential landslides or after their release), landslide deposits, or other palaeotopographic features are important for hazard and erosion assessment. The volumes involved in landslide and failure surfaces constrain the propagation of a landslide, and knowledge of the past topography helps us to understand these hazards. Some methods exist to characterise landslide geometry, but these methods usually require monitoring information. This study tries to assess the validity of the sloping local base level (SLBL) method for this purpose. Two sets of airborne lidar digital elevation models (DEMs) of the Kii Peninsula (Japan) are used: the first one was acquired before Typhoon Talas, and the second one was acquired after. A total of 70 deep-seated landslides occurred during this event between 2 and 5 September 2011. This study shows that the SLBL method is efficient using either the slope deformations identifiable on the DEM before the release of the landslide or a reliable 2.5-D failure surface created by using both DEMs (the 2.5-D corresponds to a surface which has only one z value for each x – y coordinate; in other words, no true vertical topography or overhang can be represented perfectly). In addition, this method allows for the reconstruction of eroded deposits and buried valleys. Most of the volumes estimated are within ±35 % of the estimation made by Chigira et al. (2013), and the coefficients of expansion range from 10 % to 25 %. These results show considerable sensitivity to the parameters used for the reconstruction of the landslide volume estimations and demonstrate the need for an efficient and fast tool to reconstruct potential landslide geometries or histories. [ABSTRACT FROM AUTHOR]

Defining the relationship between volume and return period is critical when estimating the risk of rockfalls and/or rock avalanche, especially during continued global warming at high altitudes that threatens rock wall stability. Characterizing the volume-frequency relationship based on historical datasets is, however, limited by observation and quantification biases, which have not received enough attention. Here, to monitor recent activities for the Brenva Spur (Mont-Blanc massif, Italy) that is also a rock avalanche scar and estimate the return period of future rock failures based on the volume-frequency relationship (and the corresponding uncertainty), a structure-from-motion photogrammetric survey was conducted from 2017 to 2021. 39 rockfall sources with volumes ranging from 11 to 13,250 m3 were identified within the scar. The total failure volume is 22,438 m3, with an associated erosion rate of 15.5 mm/year, indicating very active morphodynamics possibly linked to the permafrost evolution in the spur. The volumes were characterized by a negative power-law that fits significant two events in 2016 (3.4 × 104 m3) and one in 1997 (2.0 × 106 m3) remarkably well, and the randomness of the fit was evaluated by a Monte Carlo approach. 7 potential failure scenarios ranging from 3.1 × 104 m3 (S 1) to 4.8 × 106 m3 (S 7) were defined according to a structural analysis and the sloping local base level concept. Their extrapolated return periods derived by the power-law fit indicate a longer return period for the maximum failure scenario than for the smaller scenarios. S 1 has a 50% chance of occurring every 3 years, while S 7 has a 50% chance of occurring every 31 years. Though the median return period of S 7 is 31 years, the 95% and 68.2% confidence intervals range from 8 to 399 years and 14 to 93 years, respectively, which reflects a high level of uncertainty but is realistic when considering global warming, progressive rock failure, etc. In addition to characterizing recent rock failure activities in high mountains, this study offers a preliminary examination of the return periods of some extreme scenarios and provides primary data for risk management in mountainous areas that are very sensitive to global warming. • Updated rock failure database by helicopter based SfM photogrammetry survey for Brenva Spur. • Detailed rockfall sources analysis linking geo-structures on the Brenva avalanche scar. • Extreme failure scenarios definition by discontinuity characterization and the SLBL concept. • Failure scenario return period estimation by volume-frequency relationship considering the uncertainties. [ABSTRACT FROM AUTHOR]

Analogue methods provide a statistical precipitation prediction based on synoptic predictors supplied by general circulation models or numerical weather prediction models. The method samples a selection of days in the archives that are similar to the target day to be predicted, and consider their set of corresponding observed precipitation (the predictand) as the conditional distribution for the target day. The relationship between the predictors and predictands relies on some parameters that characterize how and where the similarity between two atmospheric situations is defined. This relationship is usually established by a semi-automatic sequential procedure that has strong limitations: (i) it cannot automatically choose the pressure levels and temporal windows (hour of the day) for a given meteorological variable, (ii) it cannot handle dependencies between parameters, and (iii) it cannot easily handle new degrees of freedom. In this work, a global optimization approach relying on genetic algorithms could optimize all parameters jointly and automatically. The global optimization was applied to some variants of the analogue method for the Rhône catchment in the Swiss Alps. The performance scores increased compared to reference methods, especially for days with high precipitation totals. The resulting parameters were found to be relevant and coherent between the different subregions of the catchment. Moreover, they were obtained automatically and objectively, which reduces the effort that needs to be invested in exploration attempts when adapting the method to a new region or for a new predictand. For example, it obviates the need to assess a large number of combinations of pressure levels and temporal windows of predictor variables that were manually selected beforehand. The optimization could also take into account parameter inter-dependencies. In addition, the approach allowed for new degrees of freedom, such as a possible weighting between pressure levels, and non-overlapping spatial windows. [ABSTRACT FROM AUTHOR]

In this work an overview of the potential rock fall source areas and propagation assessment in the Province of Potenza territory has been presented. The rock fall process is characterized by two steps: the detachment of blocks and subsequently their propagation along the slope. The adopted methodology, used for the first time in the study area, and the software Histofit and FlowR have been very useful tools for the preliminary assessment of rock fall susceptibility at a regional scale, in particular because they have required low data of the study area. Only the DEM may be sufficient together with an appropriate choice of the input parameters and algorithms, that is to say: calculation method, directions algorithm, inertial algorithm and friction loss function. The output of the model is a map of the rock fall source areas, the propagation probabilities and the propagation kinetic energy. The results show that the adopted methodology is successful for the identification of rock fall source areas at a regional scale and the propagation probability obtaining an interesting rock fall susceptibility map. [ABSTRACT FROM AUTHOR]

Analog methods are based on a statistical relationship between synoptic meteorological variables (predictors) and local weather (predictand, to be predicted). This relationship is defined by several parameters,which are often calibrated by means of a semiautomatic sequential procedure. This calibration approach is fast, but has strong limitations. It proceeds through successive steps, and thus cannot handle all parameter dependencies. Furthermore, it cannot automatically optimize some parameters, such as the selection of pressure levels and temporal windows (hours of the day) at which the predictors are compared. To overcome these limitations, the global optimization technique of genetic algorithms is considered, which can jointly optimize all parameters of the method, and get closer to a global optimum, by taking into account the dependencies of the parameters. Moreover, it can objectively calibrate parameters that were previously assessed manually and can take into account new degrees of freedom. However, genetic algorithms must be tailored to the problem under consideration. Multiple combinations of algorithms were assessed, and new algorithms were developed (e.g., the chromosome of adaptive search radius, which is found to be very robust), in order to provide recommendations regarding the use of genetic algorithms for optimizing several variants of analog methods. A global optimization approach provides new perspectives for the improvement of analogmethods, and for their application to new regions or new predictands. [ABSTRACT FROM AUTHOR]

Debris flows have been recognized to be linked to the amounts of material temporarily stored in torrent channels. Hence, sediment supply and storage changes from low-order channels of the Manival catchment, a small tributary valley with an active torrent system located exclusively in sedimentary rocks of the Chartreuse Massif (French Alps), were surveyed periodically for 16 months using terrestrial laser scanning (TLS) to study the coupling between sediment dynamics and torrent responses in terms of debris flow events, which occurred twice during the monitoring period. Sediment transfer in the main torrent was monitored with cross-section surveys. Sediment budgets were generated seasonally using sequential TLS data differencing and morphological extrapolations. Debris production depends strongly on rockfall occurring during the winter-early spring season, following a power law distribution for volumes of rockfall events above 0.1 m3, while hillslope sediment reworking dominates debris recharge in spring and autumn, which shows effective hillslope-channel coupling. The occurrence of both debris flow events that occurred during the monitoring was linked to recharge from previous debris pulses coming from the hillside and from bedload transfer. Headwater debris sources display an ambiguous behaviour in sediment transfer: low geomorphic activity occurred in the production zone, despite rainstorms inducing debris flows in the torrent; still, a general reactivation of sediment transport in headwater channels was observed in autumn without new debris supply, suggesting that the stored debris was not exhausted. The seasonal cycle of sediment yield seems to depend not only on debris supply and runoff (flow capacity) but also on geomorphic conditions that destabilize remnant debris stocks. This study shows that monitoring the changes within a torrent's in-channel storage and its debris supply can improve knowledge on recharge thresholds leading to debris flow. [ABSTRACT FROM AUTHOR]

Process-based rockfall simulation models attempt to better emulate rockfall dynamics to different degrees. As no model is perfect, their development is often accompanied and validated by the valuable collection of rockfall databases covering a range of site geometries, rock masses, velocities, and related energies that the models are designed for. Additionally, such rockfall data can serve as a base for assessing the model's sensitivity to different parameters, evaluating their predictability and helping calibrate the model's parameters from back calculation and analyses. As the involved rock volumes/masses increase, the complexity of conducting field-test experiments to build up rockfall databases increases to a point where such experiments become impracticable. To the author's knowledge, none have reconstructed rockfall data in 3D from real events involving block fragments of approximately 500 metric tons. A back analysis of the 2015 Mel de la Niva rockfall event is performed in this paper, contributing to a novel documentation in terms of kinetic energy values, bounce heights, velocities, and 3D lateral deviations of these rare events involving block fragments of approximately 200 m3. Rockfall simulations are then performed on a "per-impact" basis to illustrate how the reconstructed data from the site can be used to validate results from simulation models. [ABSTRACT FROM AUTHOR]

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform. [ABSTRACT FROM AUTHOR]

Abstract: Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches. [Copyright &y& Elsevier]

Abstract: Sackung is a widespread post-glacial morphological feature affecting Alpine mountains and creating characteristic geomorphological expression that can be detected from topography. Over long time evolution, internal deformation can lead to the formation of rapidly moving phenomena such as a rock-slide or rock avalanche. In this study, a detailed description of the Sierre rock-avalanche (SW Switzerland) is presented. This convex-shaped postglacial instability is one of the larger rock-avalanche in the Alps, involving more than 1.5billionm3 with a run-out distance of about 14km and extremely low Fahrböschung angle. This study presents comprehensive analyses of the structural and geological characteristics leading to the development of the Sierre rock-avalanche. In particular, by combining field observations, digital elevation model analyses and numerical modelling, the strong influence of both ductile and brittle tectonic structures on the failure mechanism and on the failure surface geometry is highlighted. The detection of pre-failure deformation indicates that the development of the rock avalanche corresponds to the last evolutionary stage of a pre-existing deep seated gravitational slope instability. These analyses accompanied by the dating and the characterization of rock avalanche deposits, allow the proposal of a destabilization model that clarifies the different phases leading to the development of the Sierre rock avalanche. [Copyright &y& Elsevier]

Purpose – The purpose of this paper is to describe empirical research intended to fill the perceived gap in practical guidance methodologies for assessing resilience. Design/methodology/approach – To do so, an interdisciplinary team of researchers studied landslide risk in four different communities of Central and Eastern Nepal using a case study approach. Two case studies on flood-affected communities were developed for comparison sake in more urban areas. Methods combined qualitative participatory approaches to develop indicators of resilience as well as a household survey and focus group discussions for collecting data on the indicators. Findings – What the research results demonstrate is a relatively straightforward and simple means for obtaining data on the state of a community's resilience as a relatively simple "snapshot" of resilience at one period in time, assuming that resilience is an outcome that can be improved over time with the "right" set of interventions. Research limitations/implications – The main limitation of this research is that it focussed mainly on outcome indicators; although some process indicators of resilience were identified (i.e. grazing management practices, skills training, organizational skills and learning through education), these need to be more comprehensive and validated through community consultations. Originality/value – The paper provided data and a straightforward methodology for measuring resilience and has thus contributed to the literature on this topic, while providing practical ideas for future research on resilience building measures and indicators. [ABSTRACT FROM AUTHOR]

Abstract: The Champlain Sea clays of Eastern Canada are incised by numerous rivers. Their slopes have been modified by landslides: on the Chacoura River near Trois-Rivières (Quebec), several large landslide scars, more or less recent, are visible. The role of erosion (channel incision, lateral channel migration and erosion of slopes due to agricultural drainage) as a trigger of these landslides is important. The aim of this study is to understand how erosion and landslides are related to valley development. From a detailed analysis of aerial photographs and DEMs, a map of the phenomena has been drawn by identifying various elements such as landslides, limits of the slope, position of the channel, and the area covered by forest. It is shown that channel change and erosion are strongly linked to landslides by the fact that they change the bank morphology in an unstable way. A slide in itself is a natural way for the slope to achieve stability. But when it occurs in a stream, it creates a disturbance to the stream flow enhancing local erosion which may change the river path and generate more erosion downstream or upstream resulting in more slides. Cross-valley sections and a longitudinal profile show that landslides are a major factor of valley formation. It appears that the upper part of the Chacoura River valley is still unaffected by landslides and has V-shaped sections. The lower part has been subject to intense erosion and many landslide scars can be seen. This shows that the valley morphology is transient, and that future activity is more likely to occur in the upper part of the river. Therefore the identification of areas prone to erosion will help determine the possible location of future large landslides just like the ones that occurred in the lower part. [Copyright &y& Elsevier]

Abstract: In 1903, the eastern slope of Turtle Mountain (Alberta) was affected by a 30 M m3-rockslide named Frank Slide that resulted in more than 70 casualties. Assuming that the main discontinuity sets, including bedding, control part of the slope morphology, the structural features of Turtle Mountain were investigated using a digital elevation model (DEM). Using new landscape analysis techniques, we have identified three main joint and fault sets. These results are in agreement with those sets identified through field observations. Landscape analysis techniques, using a DEM, confirm and refine the most recent geology model of the Frank Slide. The rockslide was initiated along bedding and a fault at the base of the slope and propagated up slope by a regressive process following a surface composed of pre-existing discontinuities. The DEM analysis also permits the identification of important geological structures along the 1903 slide scar. Based on the so called Sloping Local Base Level (SLBL) an estimation was made of the present unstable volumes in the main scar delimited by the cracks, and around the south area of the scar (South Peak). The SLBL is a method permitting a geometric interpretation of the failure surface based on a DEM. Finally we propose a failure mechanism permitting the progressive failure of the rock mass that considers gentle dipping wedges (30°). The prisms or wedges defined by two discontinuity sets permit the creation of a failure surface by progressive failure. Such structures are more commonly observed in recent rockslides. This method is efficient and is recommended as a preliminary analysis prior to field investigation. [Copyright &y& Elsevier]

This research evaluates the influence of various discontinuity data acquisition methods on three-dimensional rockfall susceptibility assessments, employing a high-resolution 3D point cloud of the Špičunak rock slope in Croatia. Discontinuity mapping was conducted utilising manual and semi-automated methods. Manual mapping was done in open-source software CloudCompare, while semi-automated mapping was done using Discontinuity Set Extractor and two CloudCompare plug-ins, qFacet Fast Marching and qFacet Kd-Tree algorithm. Significant differences were observed between the methods in terms of the number of identified discontinuity planes, sets, mean orientation values, and weighted densities associated with specific sets. Based on the mapping results, three-dimensional rockfall susceptibility maps were generated. The 3D rockfall susceptibility assessment employed a Kinematic Hazard Index (KHI) for planar, wedge, and flexural toppling failure mechanisms, which determines the percentage of discontinuity planes that meet the geometrical conditions specific to each type of failure. The findings underscore that the mapping results greatly affect the 3D rockfall susceptibility assessment, impacting the identification of potential rockfall source areas. The study emphasizes the importance of integrating manual and semi-automated mapping for reliable 3D rockfall susceptibility assessment. Additionally, this study evaluated the effect of varying the number of discontinuity orientation input data on rockfall susceptibility by comparing nine scenarios, each involving a reduction in the number of discontinuity orientation data. The results indicate that accurate discontinuity mapping is more critical than the sheer number of mapped discontinuities for reliable rockfall susceptibility assessment. Therefore, prioritizing the precise determination of discontinuity set numbers and their associated weighted densities is essential for reliable susceptibility evaluations. • High-resolution point cloud enables accurate representation of rock mass topology. • Rockfall susceptibility maps reveal the impact of mapping techniques on susceptibility assessments. • Misleading susceptibility results arise from neglecting critical discontinuity sets. • Researchers should prioritize correct discontinuity densities over extensive mapping for accurate susceptibility assessment. [ABSTRACT FROM AUTHOR]

The published version of this article, unfortunately, contained error. Authors found out that in equation 5, two deltas (Δ) were missing. Given in this article is the correct equation. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of slope instabilities is critical to mitigate the associated hazards, but their direct observation is often difficult due to their remote locations and their spontaneous nature. Seismology allows us to get unique information on these events, including on their dynamics. However, the link between the properties of these events (mass and kinematics) and the seismic signals generated is still poorly understood. We conducted a controlled rockfall experiment in the Riou Bourdoux torrent (southern French Alps) to try to better decipher those links. We deployed a dense seismic network and inferred the dynamics of the block from the reconstruction of the 3D trajectory from terrestrial and airborne high-resolution stereophotogrammetry. We propose a new approach based on machine learning to predict the mass and the velocity of each block. Our results show that we can predict those quantities with average errors of approximately 10 % for the velocity and 25 % for the mass. These accuracies are as good as or better than those obtained by other approaches, but our approach has the advantage in that it does not require the source to be localised, nor does it require a high-resolution velocity model or a strong assumption on the seismic wave attenuation model. Finally, the machine learning approach allows us to explore more widely the correlations between the features of the seismic signal generated by the rockfalls and their physical properties, and it might eventually lead to better constraints on the physical models in the future. [ABSTRACT FROM AUTHOR]

We propose an explicit GPU-based solver within the material point method (MPM) framework using graphics processing units (GPUs) to resolve elastoplastic problems under two- and three-dimensional configurations (i.e. granular collapses and slumping mechanics). Modern GPU architectures, including Ampere, Turing and Volta, provide a computational framework that is well suited to the locality of the material point method in view of high-performance computing. For intense and non-local computational aspects (i.e. the back-and-forth mapping between the nodes of the background mesh and the material points), we use straightforward atomic operations (the scattering paradigm). We select the generalized interpolation material point method (GIMPM) to resolve the cell-crossing error, which typically arises in the original MPM, because of the C0 continuity of the linear basis function. We validate our GPU-based in-house solver by comparing numerical results for granular collapses with the available experimental data sets. Good agreement is found between the numerical results and experimental results for the free surface and failure surface. We further evaluate the performance of our GPU-based implementation for the three-dimensional elastoplastic slumping mechanics problem. We report (i) a maximum 200-fold performance gain between a CPU- and a single-GPU-based implementation, provided that (ii) the hardware limit (i.e. the peak memory bandwidth) of the device is reached. Furthermore, our multi-GPU implementation can resolve models with nearly a billion material points. We finally showcase an application to slumping mechanics and demonstrate the importance of a three-dimensional configuration coupled with heterogeneous properties to resolve complex material behaviour. [ABSTRACT FROM AUTHOR]

We propose an explicit GPU-based solver within the material point method (MPM) framework on a single graphics pro-cessing unit (GPU) to resolve elastoplastic problems under two- and three-dimensional configurations (i.e., granular collapses and slumping mechanics). Modern GPU architectures, including Ampere, Turing and Volta, provide a computational framework that is well suited to the locality of the material point method in view of high-performance computing. For intense and nonlocal computational aspects (i.e., the back-and-forth mapping between the nodes of the background mesh and the material points), we use straightforward atomic operations (the scattering paradigm). We select the generalized interpolation material point method (GIMPM) to resolve the cell-crossing error, which typically arises in the original MPM, because of the C0 continuity of the linear basis function. We validate our GPU-based in-house solver by comparing numerical results for granular collapses with the available experimental data sets. Good agreement is found between the numerical results and experimental results for the free surface and failure surface. We further evaluate the performance of our GPU-based implementation for the three-dimensional elastoplastic slumping mechanics problem. We report i) a maximum performance gain of x200 between a CPU- and GPU-based implementation, provided that ii) the hardware limit (i.e., the peak memory bandwidth) of the device is reached. We finally showcase an application to slumping mechanics and demonstrate the importance of a three-dimensional configuration coupled with heterogeneous properties to resolve complex material behaviour. [ABSTRACT FROM AUTHOR]

Characterization of rock discontinuities and rock bridges is required to define stability conditions of fractured rock masses in both natural and engineered environments. Although remote sensing methods for mapping discontinuities have improved in recent years, remote detection of intact rock bridges on cliff faces remains challenging, with their existence typically confirmed only after failure. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along cliff-parallel exfoliation joints, with rock bridges playing a key role in the stability of partially detached exfoliation sheets. We employed infrared thermal imaging (i.e., thermography) as a new means of detecting intact rock bridges prior to failure. An infrared thermal panorama of El Capitan revealed cold thermal signatures for the surfaces of two granitic exfoliation sheets, consistent with the expectation that air circulation cools the back of the partially detached sheets. However, we also noted small areas of warm thermal anomalies on these same sheets, even during periods of nocturnal rock cooling. Rock attachment via rock bridges is the likely cause for the warm anomalies in the thermal data. 2-D model simulations of the thermal behavior of one of the monitored sheets reproduce the observed anomalies and explain the temperature differences detected in the rock bridge area. Based on combined thermal and ground-based lidar imaging, and using geometric and rock fracture mechanics analysis, we are able to quantify the stability of both sheets. Our analysis demonstrates that thermography can remotely detect intact rock bridges and thereby greatly improve rockfall hazard assessment. [ABSTRACT FROM AUTHOR]

The southeastern side of Mont Blanc is constituted of high granitic peaks affected bydifferent degree of fracturing. In the last hundred years, two major ice-rock avalanche eventstook place on the Brenva Glacier involving volumes of more than 2×106 m3. In September2016, a volume of 35’000 m3 detached from the previous rock avalanche scar and wasdeposited on the higher part of the Brenva Glacier. This new event has pushed Aosta ValleyAutonomous Region authorities to investigate in more detail the "Sperone della Brenva" rockmass. Between July 2017 and October 2018, three Photogrammetric Points Clouds (PPCs)were generated using structure-from-motion techniques from hundreds of pictures takenduring helicopter flights. The structural analysis of PPCs enabled to identify four major fracture sets in the rockavalanche scar. By fitting planes deeply along these fractures, different potentiallyunstable volumes were calculated and several scenarios were defined. During autumn2017, deformation of the rock wall was also monitored with a ground-based InSARsystem. No significant mass movement was detected; nevertheless, three rockfallevents occurred between July 2017 and October 2018, indicating that some activityremains. Heliported infrared thermal images were also acquired in October 2018. Althoughthermal signatures are not simple to analyze at the rock face scale, thermograms show thatsome fractures are colder and residual ice areas display negative temperatures. Presence ofwater leaking on the rock wall is clearly visible on these images, suggesting that theinteraction between permafrost and melted water influence greatly the stability of the Speronedella Brenva. By combining all these observations, the scenarios have been ranked in hazard levels. Ifthe collapse of mid-volumes of about 1×105 m3 is rather likely within a short delay, thefailure probability is lower for larger volumes. However, due to global warming and annualsnow cover variations, the monitoring (measuring instruments and/or monitoring activity)needs to be continued in order to permanently re-evaluate the probability of failure of eachscenario. [ABSTRACT FROM AUTHOR]

Hyperspectral cameras are actually pushbroom line-scanner. For groundbased acquisitions, they require a motorized rotating platform and often a logistics (external batteries and computer) quite heavy for real fieldwork. In 2018, a new small and handy camera was proposed on the market, the Specim IQ. It covers visible and near infrared bands (400-1000 nm), with a spectral resolution of 7 nm (204 spectral bands), a spatial sampling of 512x512 pixels, for a total weight of 1.3 kg (+ a photo tripod). We proceeded to some tests on various rocks (granite, peridotite, metamorphic gneisses, limestone, marble and detritic rocks) in outdoor conditions. Spectralon plates were used for spectrum referencing. The goal of these preliminary experiments is to identify the potential of this device to distinguish rock types, surface weathering stages, and the limitations due to light conditions and incidence angles. [ABSTRACT FROM AUTHOR]

A very important issue in rockfall analysis is to evaluate the rate of rock surface erosion, which is a crucial index to indicate rockfall activities. Over the last 15 years, point clouds datasets for evaluating the rate of rock surface erosion and rock mass structure analysis were mainly acquired by LiDAR and Structure-from-Motion photogrammetry (SfM). More recently, new scanning equipments called GeoSLAM and Sense 3D, easy to carry because their small size/weight and mainly used for 3D reconstruction of object indoors, showed great potential to be applied to extract the topography of a rock outcrop. However, to date no detailed comparative study about the accuracy and density of point clouds acquired by LiDAR, SfM, GeosLAM and Sense 3D has been reported. By using these three last techniques, we first performed an indoor experiment to acquire three different point clouds of a small rectangular box (6.5×4.4×3.7 cm3) placed on a table. The preliminary results show that SfM and Sense 3D models have a higher resolution and point density than the one acquired with GeoSLAM. The second experiment performed outdoor to monitor fast erosion of a molassic rock wall of 3 m-high by 2 m-width using the four techniques. The aim of this work is to find the most suitable method to monitor in fine scale erosion and deformation of rock wall surface to study rock mass degradation. [ABSTRACT FROM AUTHOR]

This paper presents an overview of a historic case of a rock avalanche that was potentially induced by an earthquake in the area of Korbous Nothern East of Tunisia. This study is important because Tunisia suffers from the lack of historical events archive and of any previous detailed study about rockslides and landslides. We analyze here the morphological and seismotectonic settings that are considered as the key parameters for earthquake-induced rockslides analysis. Northern East of Tunisia is an active tectonic area (earthquakes, active faults, etc...) due to its seismotectonic settings in the context of the Africa-Eurasia plate boundary. The region of Korbous is affected by different slope mass movements types mainly triggered by rainfall as it has been the case in fall 2018. But earthquakes acting as rockslide-trigger have not been considered yet. The cliff of Korbous, situated in the eastern part of the Gulf of Tunis, is about 35km and 60km distance from the faults of Tunis and Utique, the two most important historical seismogenic faults in the region, which could be the cause of an earthquake-induced rockslide favored by local geological and morphological conditions. By using landscape analysis techniques combined with field observations and measurements, structural measurements (Angelier 1990) and aerial photos interpretation we i) identified the main joints orientation that confirmed the geology model of the cliff (the main scarp cracks orientation and failure surface) and ii) determined the initial localization of the source area, the volume and the propagation trajectory of the rockslide.By dating several samples from the quaternary sedimentary sequence at the foot of the slope associated with the rockslide deposit we could define the material ages and consequently the timing of related mass movement and corresponding seismic event. We found that most criteria of identification that mark a "typical earthquake-triggered landslides" described by Havenith and Storm (2018) and Havenith and Bourdeau (2010) are fulfilled in the case of Korbous rock avalanche. [ABSTRACT FROM AUTHOR]

In the field of rock mechanics, the characterization of discontinuity persistence and intact rock bridges is needed to define stability conditions of fractured rock masses. Although methods for mapping these structural features have improved in recent years, remote imagery detection of intact rock bridges has not yet been performed. In steep exfoliating cliffs, such as El Capitan in Yosemite Valley (California, USA), rockfalls mainly occur along exfoliation joints (i.e., surface-parallel fractures separating exfoliation sheets) (Collins and Stock, 2016; Collins et al., 2018; Stock et al., 2018). Thus, we focused on the detection of rock bridges responsible for the stability of partially detached exfoliation sheets. We conducted InfraRed Thermography (IRT) monitoring, in conjunction with Terrestrial Laser Scanning (TLS) surveying to characterize the stability of two well-delimited granitic exfoliation sheets. By examining the final phase of diurnal cooling of these flakes with IRT, we found that they always remain colder than the surrounding rock walls. We interpret this colder thermal signature as a result of the air circulation that envelops and cools the detached parts from the cliff. Detailed analysis of each thermal image also revealed that the temperature patterns are not homogeneous – warmer thermal anomalies are visible on the surface of both monitored flakes. We interpret these warmer areas as a sign of the possible presence of rock bridges that would conduct heat from the rock mass located behind the exfoliation sheets. The detection of rock bridges from our IRT analysis is supported by the results of 2-D thermal modeling. These simulations reproduced the observed thermal signatures and improved our understanding of the temperature differences detected in the rock bridge area. By draping IRT images on TLS meshes, we were then able to measure the geometry of the potential rock bridge surfaces and subsequently evaluate the exfoliation sheet stability conditions using fracture mechanics analysis. This study demonstrates that thermal imaging combined with high-resolution 3D topography have great potential for rock failure hazard assessment. [ABSTRACT FROM AUTHOR]

We present an efficient MATLAB-based implementation of the material point method (MPM) and its most recent variants. MPM has gained popularity over the last decade, especially for problems in solid mechanics in which large deformations are involved, such as cantilever beam problems, granular collapses and even large-scale snow avalanches. Although its numerical accuracy is lower than that of the widely accepted finite element method (FEM), MPM has proven useful for overcoming some of the limitations of FEM, such as excessive mesh distortions. We demonstrate that MATLAB is an efficient high-level language for MPM implementations that solve elasto-dynamic and elasto-plastic problems. We accelerate the MATLAB-based implementation of the MPM method by using the numerical techniques recently developed for FEM optimization in MATLAB. These techniques include vectorization, the use of native MATLAB functions and the maintenance of optimal RAM-to-cache communication, among others. We validate our in-house code with classical MPM benchmarks including (i) the elastic collapse of a column under its own weight; (ii) the elastic cantilever beam problem; and (iii) existing experimental and numerical results, i.e. granular collapses and slumping mechanics respectively. We report an improvement in performance by a factor of 28 for a vectorized code compared with a classical iterative version. The computational performance of the solver is at least 2.8 times greater than those of previously reported MPM implementations in Julia under a similar computational architecture. [ABSTRACT FROM AUTHOR]

Across a large mountain area of the western Swiss Alps, we used occurrence data (presence‐only points) of bird species to find suitable modelling solutions and build reliable distribution maps to deal with biodiversity and conservation necessities of bird species at finer scales. We have performed a multi‐scale method of modelling, which uses distance, climatic, and focal variables at different scales (neighboring window sizes), to estimate the efficient scale of each environmental predictor and enhance our knowledge on how birds interact with their complex environment. To identify the best radius for each focal variable and the most efficient impact scale of each predictor, we have fitted univariate models per species. In the last step, the final set of variables were subsequently employed to build ensemble of small models (ESMs) at a fine spatial resolution of 100 m and generate species distribution maps as tools of conservation. We could build useful habitat suitability models for the three groups of species in the national red list. Our results indicate that, in general, the most important variables were in the group of bioclimatic variables including "Bio11" (Mean Temperature of Coldest Quarter), and "Bio 4" (Temperature Seasonality), then in the focal variables including "Forest", "Orchard", and "Agriculture area" as potential foraging, feeding and nesting sites. Our distribution maps are useful for identifying the most threatened species and their habitat and also for improving conservation effort to locate bird hotspots. It is a powerful strategy to improve the ecological understanding of the distribution of bird species in a dynamic heterogeneous environment. [ABSTRACT FROM AUTHOR]

• Self-made mixed label landslide dataset is constructed using open-source optical remote sensing images. • A weight transfer function is designed to enable autonomous learning of mask segmentation information through boundary regression. • Mask score calculation method is proposed to self-correct loess landslide detection mask. • Average precision of loess landslide classification is improved by 20.7%. Loess landslides pose a severe threat of destruction, and detecting them is crucial for minimizing their impact on society. They typically consist of wind-deposited clay and silt, which makes them challenging to detect using conventional methods. Techniques like visual interpretation and field surveys are the most useful, yet these methods can be laborious, expensive, and require a certain level of prior knowledge. Furthermore, remote sensing approaches face the challenge of distinguishing between natural erosion and landslides. Recently, deep learning for landslide detection has the potential to speed up and improve detection accuracy. Nonetheless, deep learning models require large amounts of labeled data and the development of robust algorithms capable of extracting meaningful features from remote sensing data. In this article, a novel approach is introduced to improve the Mask Regional Convolutional Neural Network (Mask-RCNN) algorithm for accurately detecting landslides when the number of available segmentation mask samples is limited. Specifically, A novel loess landslides dataset is established using high-resolution remote sensing images in Gansu Province. In the context of partially supervised learning, a neural network branch containing a weight transfer function is developed to capture mask information from bounding boxes. Additionally, a mask-scoring network block is used to learn the quality of predicted instance masks. Our modified algorithm achieves an average precision improvement of 20.7% compared to the original Mask R-CNN algorithm in small landslide detection. The mask IoU threshold value of 0.5 is used to estimate the average accuracy higher than 0.75. The average precision of the segmentation mask is improved by 16.7% in test set. By proposing a solution that can achieve accurate landslide detection while using limited labeled samples, this study makes a valuable contribution to the application of deep learning in the domains of remote sensing and landslide detection. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so- called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; (3) geometric distortions that are foreshortening, layover and shadowing. If in the case of satellites SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition one can expect in terms of range and azimuth resolution, Line of Sight (LoS) distance and geometric distortions to select the best installation location when several are possible. We developed a tool which estimates those parameters from a Digital Elevation Model (DEM), knowing the GB-InSAR and the Slope of Interest (Sol) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the Sol geometry on the acquisition characteristics and on two real cases; cliffs located in Switzerland, one in the Ticino canton and on in the Vaud canton. [ABSTRACT FROM AUTHOR]

The reliable in situ quantification of rock mass fracturing and engineering quality is critical for slope stability, surface mining and rock engineering applications, yet it remains difficult due to the heterogeneous nature of fracture networks. We propose a method to quantify and map the slope-scale geomechanical quality of fractured rock masses using infrared thermography (IRT). We use the Mt. Gorsa quarry (Trentino, Italy) as a field laboratory to upscale a physics-based approach, which was developed in the laboratory, to in situ conditions, including the effects of fracture heterogeneity, environmental conditions and IRT limitations. We reconstructed the slope in 3D using UAV photogrammetry, characterized the rock mass quality in the field at selected outcrops in terms of the Geological Strength Index (GSI) and measured their cooling behavior through 18h time-lapse IRT surveys. With ad hoc field experiments, we developed a novel procedure to correct IRT data in outdoor environments with complex topography. This allowed for a spatially distributed quantification of the rock mass surface cooling behavior in terms of a Curve Shape Parameter (CSP). Using non-linear regression, we established a quantitative CSP-GSI relationship, which allowed for the CSP to be translated into GSI maps. Our results demonstrate the possibility of applying infrared thermography to the slope-scale mapping of rock mass fracturing based on a physics-based experimental methodology. [ABSTRACT FROM AUTHOR]

An introduction to articles published within the issue, from research papers discussed at the 2nd Virtual Geoscience Conference 2016 held in Bergen, Norway, from September 21-23, 2016 showcasing scientific developments at the interface between geomatics, geoscience and related disciplines, is presented.

The influence of gravitational slope deformation (GSD) on erosion rates and the shape of mountain belts has been identified worldwide, particularly in valleys affected by glacial retreat. However, due to a lack of understanding about the main predisposing factors influencing their spatial distribution, size and failure mechanisms, the effective impact of GSD on the evolution of the landscape remains difficult to quantify. This study presents the first detailed, regional-scale GSD inventory of the entire Upper Rhone catchment (western Switzerland). The detection and mapping of GSD are performed by combining different remote sensing approaches. Moreover, we propose a detailed characterisation of GSD, taking into account geometry, morphology and failure mechanisms. Based on these analyses, more than 300 GSD are identified, corresponding to 11 % of the entire study area. Spatial and statistical analyses indicate that GSD are not uniformly distributed across the study area: six GSD clusters are highlighted, containing more than 80 % of the GSD events detected. Our observations suggest that the distribution of GSDs is primarily related to coexisting active tectonic processes (including high uplift gradients and earthquake activity) and pre-existing regional-scale, tectonic weakness zones. The region's lithological and structural conditions, on the other hand, appear largely to influence the failure mechanisms and the sizes of the GSD detected. [ABSTRACT FROM AUTHOR]

The article focuses on the use of three-dimensional (3D) remote sensing techniques for the investigation diverse geo-hazards. Topics discussed include use of 3D point clouds for the investigation of Earth surface processes, investigation of dynamic surface processes such as lava flows, investigation of rocky cliffs shaped by sea erosion, investigation of geohazards along transportation corridors, assessing seismic hazard on analysis of channel offsets and morphotectonic features.

Foreland basin tectonics along the eastern Palaeo-Tethys Ocean produced a complex and dynamic pattern of sediment delivery to adjacent basins. Environmental processes at the local scale significantly disrupt regional ones, making the analysis of sedimentary evolution difficult. This study investigated the Lower Permian Liangshan Formation black shale formed in such geological setting, rich in cherts with exceptionally high silica and fluctuating major and trace element concentrations, detected using XRD, XRF, and ICP-MS techniques. Different types of silica, including detrital quartz, recrystallised radiolaria, microcrystalline quartz, and quartz veins, were identified using SEM and SEM-CL imaging. Geochemical characterisation and enrichment pattern analyses indicated that the structural setting was characterised by proximity to the oceanic island arc, continental island arc, and passive margin, and the major zone of sediment accumulation was a semi-restricted back-arc basin under the subduction zone. The processes controlling sediment accumulation included hydrothermal activity, upwelling, biogenic silica, and terrestrial inputs. Although upwelling interfered with the mobility and migration of hydrothermal elements, it introduced abundant nutrients, and together with hydrothermal fluids, it contributed to the subsequent boom in siliceous organisms. Terrigenous inputs induced by land uplift significantly diluted the components from other sources. This multi-source proxies approach not only enables researchers to disentangle local from regional processes but also sheds light on how these diverse environmental forces interact within intricate earth systems, which enhance our comprehension of geologic history and inform ongoing studies focused on climate change mitigation strategies. • Excess silica in Liangshan Formation black shale is of siliceous radiolarian origin. • The Liangshan Formation reveals a semi-restricted back-arc basin environment. • Gallium correlates with terrestrial input, indicating the back-arc basin's constriction level. • Vertical variations and correlations analysis of multi-source proxies identify the local from regional processes. [ABSTRACT FROM AUTHOR]

Purpose According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. Method About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). Results The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Conclusion Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information. [ABSTRACT FROM AUTHOR]

Purpose The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. Methods We looked at about 240 000 IRC measurements carried out in about 150 000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m 3 . Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. Results Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. Conclusions IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements. [ABSTRACT FROM AUTHOR]

We present a long-term spatio-temporal analysis of rock slope evolution using a Terrestrial LiDAR aiming to improve our understanding of the link between pre-failure deformation and the spatial prediction of rockfalls. We monitored the pilot study area located at the Puigcercós cliff (Catalonia, Spain) over a period of 1,705 days and detected the deformation of nine different cliff regions together with a high rockfall activity. An exact match was observed between the progressively deformed areas and the regions recently affected by three of the highest magnitude rockfall events, demonstrating a causal relationship between pre-failure deformation and rockfall occurrence. These findings allowed us to make a forward spatial prediction of future failures, hypothesizing a high probability of failure in the six remaining regions. We observed an exponential acceleration of the deformation close to failure, in accordance with tertiary creep theory. However, the temporal analysis of the deformed areas showed a complex and variable behavior, so no exact prediction of the date of failure can yet be made. Our findings have broadened our understanding of the pre-failure behavior of rockfalls and have clear implications for the future implementation of early warning systems. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: In Switzerland, nationwide large-scale radon surveys have been conducted since the early 1980s to establish the distribution of indoor radon concentrations (IRC). The aim of this work was to study the factors influencing IRC in Switzerland using univariate analyses that take into account biases caused by spatial irregularities of sampling. Methods: About 212,000 IRC measurements carried out in more than 136,000 dwellings were available for this study. A probability map to assess risk of exceeding an IRC of 300 Bq/m3 was produced using basic geostatistical techniques. Univariate analyses of IRC for different variables, namely the type of radon detector, various building characteristics such as foundation type, year of construction and building type, as well as the altitude, the average outdoor temperature during measurement and the lithology, were performed comparing 95% confidence intervals among classes of each variable. Furthermore, a map showing the spatial aggregation of the number of measurements was generated for each class of variable in order to assess biases due to spatially irregular sampling. Results: IRC measurements carried out with electret detectors were 35% higher than measurements performed with track detectors. Regarding building characteristics, the IRC of apartments are significantly lower than individual houses. Furthermore, buildings with concrete foundations have the lowest IRC. A significant decrease in IRC was found in buildings constructed after 1900 and again after 1970. Moreover, IRC decreases at higher outdoor temperatures. There is also a tendency to have higher IRC with altitude. Regarding lithology, carbonate rock in the Jura Mountains produces significantly higher IRC, almost by a factor of 2, than carbonate rock in the Alps. Sedimentary rock and sediment produce the lowest IRC while carbonate rock from the Jura Mountains and igneous rock produce the highest IRC. Potential biases due to spatially unbalanced sampling of measurements were identified for several influencing factors. Conclusions: Significant associations were found between IRC and all variables under study. However, we showed that the spatial distribution of samples strongly affected the relevance of those associations. Therefore, future methods to estimate local radon hazards should take the multidimensionality of the process of IRC into account. [Copyright &y& Elsevier]

Abstract: Initial topography and inherited structural discontinuities are known to play a dominant role in rock slope stability. Previous 2-D physical modeling results demonstrated that even if few preexisting fractures are activated/propagated during gravitational failure all of those heterogeneities had a great influence on mobilized volume and its kinematics. The question we address in the present study is to determine if such a result is also observed in 3-D. As in 2-D previous models we examine geologically stable model configuration, based upon the well documented landslide at Randa, Switzerland. The 3-D models consisted of a homogeneous material in which several fracture zones were introduced in order to study simplified but realistic configurations of discontinuities (e.g. based on natural example rather than a parametric study). Results showed that the type of gravitational failure (deep-seated landslide or sequential failure) and resulting slope morphology evolution are the result of the interplay of initial topography and inherited preexisting fractures (orientation and density). The three main results are i) the initial topography exerts a strong control on gravitational slope failure. Indeed in each tested configuration (even in the isotropic one without fractures) the model is affected by a rock slide, ii) the number of simulated fracture sets greatly influences the volume mobilized and its kinematics, and iii) the failure zone involved in the 1991 event is smaller than the results produced by the analog modeling. This failure may indicate that the zone mobilized in 1991 is potentially only a part of a larger deep-seated landslide and/or wider deep seated gravitational slope deformation. [Copyright &y& Elsevier]

Abstract: This study proposes a new concept for upscaling local information on failure surfaces derived from geophysical data, in order to develop the spatial information and quickly estimate the magnitude and intensity of a landslide. A new vision of seismic interpretation on landslides is also demonstrated by taking into account basic geomorphic information with a numeric method based on the Sloping Local Base Level (SLBL). The SLBL is a generalization of the base level defined in geomorphology applied to landslides, and allows the calculation of the potential geometry of the landslide failure surface. This approach was applied to a large scale landslide formed mainly in gypsum and situated in a former glacial valley along the Rhône within the Western European Alps. Previous studies identified the existence of two sliding surfaces that may continue below the level of the valley. In this study, seismic refraction–reflexion surveys were carried out to verify the existence of these failure surfaces. The analysis of the seismic data provides a four-layer model where three velocity layers (<1000ms−1, 1500ms−1 and 3000ms−1) are interpreted as the mobilized mass at different weathering levels and compaction. The highest velocity layer (>4000ms−1) with a maximum depth of ~58m is interpreted as the stable anhydrite bedrock. Two failure surfaces were interpreted from the seismic surveys: an upper failure and a much deeper one (respectively 25 and 50m deep). The upper failure surface depth deduced from geophysics is slightly different from the results obtained using the SLBL, and the deeper failure surface depth calculated with the SLBL method is underestimated in comparison with the geophysical interpretations. Optimal results were therefore obtained by including the seismic data in the SLBL calculations according to the geomorphic limits of the landslide (maximal volume of mobilized mass=7.5×106 m3). [Copyright &y& Elsevier]