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An enormous amount of construction and demolition waste is generated globally every year, and it increases disposal costs in landfills. The advantage of adopting crushed concrete aggregate as an alternative cushioning material provides a novel approach for reusing and recycling waste materials. However, a lack of understanding of the dynamic responses of recycled concrete aggregate (RCA) inhibits their potential use. In this study, large-scale field tests are carried out to replicate dynamic impact loading on an instrumented concrete shed that is shielded by a 1 m-thick RCA cushioning layer. Six successive large-scale field boulder impact tests with energy levels reaching 70 kJ are conducted. Two different RCA particle sizes—RS (100–150 mm) and RL (200–250 mm)—are investigated. The results show that up to 82% maximum transmitted load can be reduced if the RL cushioning layer is replaced with RS cushioning layer. This phenomenon is attributed to the force chains composed of small particles that are more susceptible to collapse than large particles. To optimize the load-reduction performance of the RCA cushioning layer, practitioners should adopt a small particle size when considering a single boulder impact. In contrast, after six impacts, the maximum transmitted load for Rs is approximately 4.2 times larger than that for RL. This increased load is caused by the relative particle breakage index (Br) for RL being at least 1.3 times larger than that for Rs. This finding indicates that the amount of crushing RCA particles increases with increasing particle size. This phenomenon induces force chains to collapse more easily, and the transmitted load decreases. An RCA cushioning layer with a large particle size can effectively reduce the transmitted load under the consideration of successive impacts. This implies that the combined effects of particle size and number of successive impacts strongly influence the load distributions exerted on structures shielded by an RCA cushioning layer. Highlights: Six successive large-scale field boulder impact tests with energy levels reaching 70 kJ are conducted. [ABSTRACT FROM AUTHOR]

The aim of our work is to develop a methodology to identify the areas most prone to natural rockfall retention through the integrated use of remote sensing data. The area chosen as a case study is located in Campania (Italy) nearby Mount San Liberatore. In this area, which is itself geomorphologically predisposed to landslide risk, there are several rockfall risk hotspots, so defined because of the high exposed value constituted by an articulated infrastructure network located along the northwest slope of the mountain. The area is largely covered by dense vegetation, of which holm oak is the most representative type, characterized by a taproot apparatus that, giving it strength and stability, makes it an ideal tree for slope protection. Based on high-resolution multispectral satellite images, vegetation indices (VIs) were calculated to estimate health status, approximate age, average height, robustness, and vigor. Morphometric parameters suitable for describing slope dynamics were also calculated, derived from LiDAR data. The classification of areas with similar characteristics was carried out using Self-Organizing Maps. The results made it possible to identify all those areas where there is a greater contribution of protective forests in the mitigation of rockfall risk and, consequently, to identify areas to carry out a combined strengthening of protective actions. [ABSTRACT FROM AUTHOR]

Proximity remote sensing techniques, both land- and drone-based, allow for a significant improvement of the quality and quantity of raw data employed in the analysis of rockfall phenomena. In particular, the large amount of data these techniques can provide allows for the use of probabilistic approaches to rock mass characterization, with particular reference to block volume and shape definition. These, in return, are key parameters required for a proper rockfall hazard assessment and the optimization of countermeasures design. This study aims at providing a sort of guide, starting from the data gathering phase to the processing, up to the implementation of the outputs in a probabilistic-based scenario, which is able to associate a probability of not being exceeded with total kinetic energy values. By doing so, we were able to introduce a new approach for the choice of design parameters and the evaluation of the effectiveness of mitigation techniques. For this purpose, a suitable case study located in Varaita Valley (Cuneo, Italy) has been selected. The area has been surveyed, and a model of the slope and a digital model of the rock faces have been defined. The results show that a 6.5 m3 block has a probability of not being exceeded of 75%; subsequent simulations show that the level of kinetic energy involved in such a rockfall is extremely high. Some mitigation techniques are discussed. [ABSTRACT FROM AUTHOR]

Rockfall presents a significant risk to the safety and economy of communities and infrastructure in mountainous regions. The recently-developed Rockfall Activity Index (RAI) utilizes high-resolution terrestrial lidar-derived digital elevation models (DEMs) of rock slopes to categorize a slope face into seven distinct morphological units, or "RAI classes". This paper focuses on a comprehensive study conducted at four sites in Alaska, USA, where a robust lidar-based five-year inventory of 4381 rockfall events was analyzed. The primary objective was to investigate variations in failure characteristics, such as cumulative magnitude–frequency distributions, non-cumulative power–law parameters, average annual failure rates, and average failure depths, among the different RAI classes. The findings demonstrate that the seven RAI classes effectively differentiate the rock slope based on unique mass-wasting characteristics. Furthermore, the research explores spatial and temporal variations in these failure characteristics. Based on the study's outcomes, recommendations are provided for modifying the RAI parameters for each RAI class, specifically the annual failure rate and average failure depth. These modifications aim to enhance the accuracy and effectiveness of rockfall hazard assessments. [ABSTRACT FROM AUTHOR]

Rockfall event is common on rocky terrain, and it threatens people. Recent advances in remote sensing technologies allow us to model the terrain with high accuracy and resolution. In this study, we show the application of modeling a rockfall site in three-dimensional (3D) using an unmanned aerial vehicle. The acquisition of information about discontinuities in the rock masses using 3D point clouds is vital to characterize rockfall dynamics. We obtained 3D spatial information and point clouds of a rocky slope from acquired images. We extracted 10 discontinuity sets from the 3D model as they have significant effects on the failure mechanism. Details in mapping discontinuities have improved significantly with the help of point clouds. The results are beneficial for modeling the terrain of inaccessible areas with high resolution and obtaining information from those areas. This paper shows how can point cloud analysis be applied to characterize discontinuity sets. [ABSTRACT FROM AUTHOR]

In mountain regions, rockfall is a very widespread natural hazard, difficult to be numerically simulated, from the initial detachment of the block to its impact on natural/artificial strata. When a rock block impacts on a granular stratum, the interaction is dominated by inertial effects and is severely affected by block mass, shape, velocity magnitude/direction, and soil geomechanical properties. The kinematic description of the response of the block during the impact requires complex and time-consuming numerical modeling approaches. Moreover, these numerical approaches cannot be easily coupled with classical mass-lumped rockfall analysis tools employed to simulate blocks trajectory. To overcome this problem, a dynamic upscaled visco-plastic rheological model (BIMPAM), suitable for simulating inclined impacts on generally inclined deformable strata, has been conceived in the past by one of the authors. Up to now, due to the absence of suitable numerical and experimental data, BIMPAM has been only validated on experimental large-scale vertical impacts on horizontal strata. In this paper, the impact problem is analyzed, by performing numerical analyses by means of a coupled Discrete Element and Finite Difference numerical model (DEM-FDM), calibrated on available experimental data, to provide (i) a novel numerical dataset highlighting the crucial role played by the impacting velocity inclination on the dynamic interaction between soil stratum and penetrating rigid object and (ii) a detailed micromechanical description identifying the processes responsible for the complex macroscopic behavior. The obtained numerical results have allowed to both validate BIMPAM model, even in case of inclined velocities, and provide a micromechanical interpretation of its constitutive assumptions. Highlights: The obtained numerical DEM-FDM results have allowed the authors to discuss how the initial velocity inclination affects impact kinematics. An upscaled constitutive relationship (BIMPAM model), previously conceived, has been validated for any impact inclination using the novel dataset obtained in the current work. The problem of DEM-FDM data reliability has been critically tackled proposing an original procedure for the generation/calibration of the coupled DEM-FDM model. The role of grain damaging, when the impact energy is sufficiently large, has been highlighted, from the direct comparison with large scale experimental test results. [ABSTRACT FROM AUTHOR]

Shelter caves serve as crucial repositories that provide valuable insights into Late Pleistocene–Holocene depositional mechanisms and environmental changes. In this study, we conducted a stratigraphic analysis of the easternmost cave-fill succession within the Santuario della Madonna cave, located along the Tyrrhenian coasts of southern Italy. By examining the cave-fill deposits and their relationship with archaeological successions from previous excavation campaigns, we aimed to enhance our understanding of sedimentary evolution, specifically, the interplay between local and global environmental factors. A comprehensive sedimentological analysis was conducted, enabling the identification of three distinct sedimentary facies within the clastic succession that overlays the calcareous cave roof. Our findings reveal a noticeable shift in cave sedimentation processes, characterized by a gap in detritus accumulation followed by the deposition of flowstones. Furthermore, the presence of oversized boulders within the succession was attributed to failures from the cliffs that overhang the cave opening. We interpret these boulders as possible evidence of cave collapses induced by earthquakes, similarly to rockfall phenomena observed in the archaeological test pits within the shelter, which show a strong correlation with paleoseismic events. [ABSTRACT FROM AUTHOR]

Rockfalls and landslide events are caused by different factors among which are included geomorphological and climatic factors and also human interaction. Therefore, the economic and social impacts can be significant and the remote monitoring of such hazards has become an essential topic in various applications. Wireless sensor networks (WSNs) are well suited for the deployment of monitoring systems, benefiting from the different technologies and topologies that are available and evolving nowadays. This review paper aims to summarize and overview the up-to-date state of the art of rockfall and landslide monitoring systems based on WSNs. The implementation and methods were analyzed for each solution, along with the system architecture and relevant hardware aspects. All the retrieved data were used to analyze the current trends and future possibilities in the field of WSN geohazard monitoring. [ABSTRACT FROM AUTHOR]

With the widespread construction of railways, many mountainous single-line railway yards need to be expanded, and existing protection measures against rockfall are inadequate to protect stations and other infrastructure following expansion. Based on the actual engineering background, in this paper the movement trajectory of falling rocks on a high and steep slope is simulated using RocFall software, and the bouncing height, movement speed and impact energy of falling rocks are derived. According to the numerical simulation results, the rockfall protection measure of rockfall drapery systems plus the combination of rockfall embankments and rock sheds is proposed. The structure of a rockfall embankment–rock shed is a new type of combined protection measure, in which the rockfall embankments are built on top, with the existing rock shed or new portal foundation and top plate working as the lower foundation. This study shows that this new combination structure can resist the impact of falling rocks with a high factor of safety; the effective interception height of rockfall embankments is increased and the problem of rockfall crossing is solved with the construction of rockfall embankments on top of a rock shed or portal foundation. [ABSTRACT FROM AUTHOR]

Despite the good results that have been achieved in unimodal segmentation, the inherent limitations of individual data increase the difficulty of achieving breakthroughs in performance. For that reason, multi-modal learning is increasingly being explored within the field of remote sensing. The present multi-modal methods usually map high-dimensional features to low-dimensional spaces as a preprocess before feature extraction to address the nonnegligible domain gap, which inevitably leads to information loss. To address this issue, in this paper we present our novel I mbalance K nowledge- D riven Multi-modal Net work (IKD-Net) to extract features from multi-modal heterogeneous data of aerial images and LiDAR directly. IKD-Net is capable of mining imbalance information across modalities while utilizing a strong modal to drive the feature map refinement of the weaker ones in the global and categorical perspectives by way of two sophisticated plug-and-play modules: the G lobal K nowledge- G uided (GKG) and C lass K nowledge- G uided (CKG) gated modules. The whole network then is optimized using a joint loss function. While we were developing IKD-Net, we also established a new dataset called the N ational Agriculture Imagery Program and 3 D Elevation Program C ombined dataset in California (N3C-California) , which provides a particular benchmark for multi-modal joint segmentation tasks. In our experiments, IKD-Net outperformed the benchmarks and state-of-the-art methods both in the N3C-California and the small-scale ISPRS Vaihingen dataset. IKD-Net has been ranked first on the real-time leaderboard for the GRSS DFC 2018 challenge evaluation until this paper's submission. Our code and N3C-California dataset are available at https://github.com/wymqqq/IKDNet-pytorch. [ABSTRACT FROM AUTHOR]

Owing to drifting snow processes, snow accumulation and surface density in polar environments are variable in space and time. We present new field data of manual measurements, repeat terrestrial laser scanning and snow micro-penetrometry from Dronning Maud Land, Antarctica, showing the density of new snow accumulations. We combine these data with published drifting snow mass flux observations, to evaluate the performance of the 1-D, detailed, physics-based snow cover model SNOWPACK in representing drifting snow and surface density. For two sites in East Antarctica with multiple years of data, we found a coefficient of determination for the simulated drifting snow of r 2 = 0.42 and r 2 = 0.50, respectively. The field observations show the existence of low-density snow accumulations during low wind conditions. Successive high wind speed events generally erode these low-density layers while producing spatially variable erosion/deposition patterns with typical length scales of a few metres. We found that a model setup that is able to represent low-density snow accumulating during low wind speed conditions, as well as subsequent snow erosion and redeposition at higher densities during drifting snow events was mostly able to describe the observed temporal variability of surface density in the field. [ABSTRACT FROM AUTHOR]

Among the types of landslides that occur in Alpine areas, rockfalls are one of the most frequent and dangerous. Rockfalls affect every type of rock mass with greater or lesser incidence based on the intrinsic characteristics of rocks (structural setting, lithotype, geotechnical quality, weathering conditions, etc.) and climate features of geographic areas considered. In order to assess the hazard and subsequently the risk associated with these phenomena, it is first necessary to identify areas most likely to be affected. This paper presents a methodology applicable on a regional scale to identify the most susceptible Alpine areas to rockfalls. The methodology is based on statistical cross-analyses of environmental factors to identify the Alpine areas most susceptible to rockfalls. The predisposing factors considered to generate a rockfall susceptibility map are both qualitative (geological variables) and quantitative (morphometric, altimetric and climatic variables) and have been compared with a selection of historical data on rockfalls occurrence and distribution (consisting in 2800 events). As result, a classification of the Piemonte's Alpine territory identifying 5 classes characterized by a greater or lesser propensity to generate rockfalls has been obtained. The regional susceptibility map has been subsequently used as basis to identify road networks more exposed to rockfall hazard to obtain a preliminary risk analysis at regional scale. [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]

Geofoam with good buffer performance and low density is proposed to replace part of the sand, forming a composite cushion to resist rockfall impact. On the other hand, falling rock is usually variable and irregular in shape. In this study, laboratory tests and numerical research are conducted to study the buffer performance of geofoam, as well as the effect of the rock shape. When the rock shape changes from the flat form to the cone form, more time is needed to undergo the impact process and the maximum impact force decreases. Thicker geofoam is advantageous for reducing the impact force. However, the decrease degree is affected by the rock shape. Both the geofoam thickness and the rock shape have an obvious effect on the maximum deformation and the vertical stress in the geofoam. Thicker geofoam can amplify the influence of the rock shape on the stress in the beam. Accordingly, in the design of an effective composite cushion in a rock-shed, the geofoam thickness necessarily requires appropriate determination to meet both the buffer performance and the cushion deformation. Furthermore, the rock shape plays a crucial role in evaluating the buffer performance of the composite cushion. • A series of laboratory impact tests are carried out to discuss the impact process of falling rocks. • A numerical model is validated by a large-scale physical experiment and the laboratory impact tests. • The effect of geofoam thickness and rock shape on the dynamic responses of rock-shed is discussed. [ABSTRACT FROM AUTHOR]

Recent successes in point cloud semantic segmentation heavily rely on a large amount of annotated data. Furthermore, three-dimensional point cloud data are generally sparse and unorganized, and a frame of point cloud usually includes more than 100,000 points, which increases the difficulty of point cloud annotation. To reduce the annotation efforts, we propose a multi-granularity semisupervised active learning pipeline which aims to select representative, uncertain and diverse data to annotate. To better exploit annotating budget, we first leverage the conventional point cloud registration algorithm to develop a matching score function which is used to select a representative subset. And then we change the annotating units from a point cloud scan to segmented regions through two semisupervised methods. Subsequently, in each active selection step, segmented region information is calculated with two terms: softmax entropy and point cloud intensity, and the latter serves to encourage region diversity. Finally, to further reduce annotation effort, semisupervised learning is introduced to our pipeline to automatically select a portion of unlabeled segmented regions with high confidence and assign pseudolabels to them. Extensive experiments show that our approach greatly outperforms previous active learning methods, and we obtain the mean class intersection-over-union performance of 95% fully supervised learning with merely 3% of labeled data on SemanticKITTI dataset. [ABSTRACT FROM AUTHOR]

Point cloud registration is of great significance to the reconstruction of high‐precision 3D city models. There are some challenges when aligning aerial and close‐range photogrammetric point clouds, such as huge view differences caused by the different sights of the sensors, massive noisy points due to the error in dense matching, and scale uncertainty since there are no control points for absolute orientation. To achieve complementary advantages of aerial and close‐range point clouds, in this paper, a robust cross‐source point clouds registration method is proposed using image visual context features and scale consistency. First, a cross‐view image matching method based on image visual context features is proposed to obtain corresponding points. Second, to overcome the challenges of noisy points and scale differences, an outlier filtering method is designed based on scale consistency. Finally, the dual quaternions model considering the scale factor is introduced to solve the spatial transformation model. To analyze the feasibility of this method qualitatively and quantitatively, experiments are conducted using the public scene dataset of Dortmund, Germany, and the scene dataset of Zhengzhou City, China. Three kinds of cross‐source point clouds registration experiments are conducted in this paper, including aerial and close‐range point clouds registration in Dortmund, and aerial and ground point clouds registrations in both Dortmund and Zhengzhou. The chamfer distances of the three sets of experiments are 4.48 m, 5.97 m and 4.78 m, respectively. The ablation study shows that the outlier filtering method and the dual quaternions model improve the accuracy by at least 14% and 25%, respectively. The experiments demonstrate that the method accomplishes the cross‐source point clouds registration in large‐scale scenes accurately and efficiently, providing a solid foundation for subsequent fine 3D reconstruction. [ABSTRACT FROM AUTHOR]

Rockwall erosion by rockfall is largely controlled by frost weathering in high alpine environments. As alpine rock types are characterized by crack‐dominated porosity and high rock strength, frost cracking observations from low strength and grain supported pore‐space rocks cannot be transferred. Here, we conducted laboratory experiments on Wetterstein limestone samples with different initial crack density and saturation to test their influence on frost cracking efficacy. We exposed rocks to real‐rockwall freezing conditions and monitored acoustic emissions as a proxy for cracking. To differentiate triggers of observed cracking, we modeled ice pressure and thermal stresses. Our results show initial full saturation is not a singular prerequisite for frost cracking. We also observe higher cracking rates in less‐fractured rock. Finally, we find that the temperature threshold for frost cracking in alpine rocks falls below −7°C. Thus, colder, north‐exposed rock faces in the Alps likely experience more frost cracking than southern‐facing counterparts. Plain Language Summary: Freezing results in the formation of ice that exerts stresses on fracture walls and draws in additional moisture to supply further growth and break down rocks, a process termed frost cracking. Frost cracking drives much erosion and rockfall in alpine environments. Here we test hypotheses from prior work about how frost cracking is impacted by saturation and rock properties. We exposed rock samples of different strength and saturation to identical freezing conditions in laboratory experiments. We monitored rock temperature and acoustic emissions (AE), assuming frost cracking produces the recorded AE hits. We find that initial full saturation is not required for frost cracking, as water transport is enhanced by fractures in alpine rocks. Furthermore, rock with initial higher short‐term strength showed more frost cracking because, we infer, of stiffness properties that make these rocks more brittle compared to lower strength rocks. Frost cracking occurred at a wide range of temperatures below freezing and was highest between −9 and −7°C. We thus conclude that frost cracking is most impacted by temperature and rock short‐term strength. In Alpine environments, this may result in more frost cracking and rockfall on colder north‐facing rockwalls than warmer southern exposures. Key Points: Initial saturation levels do not limit the efficacy of ice segregation in fractured alpine rocksRock initial crack density impacts rock stiffness and thermal properties and thus frost cracking efficacyThe "frost cracking window" temperature range is dependent on rock strength and crack‐controlled porosity in alpine rocks [ABSTRACT FROM AUTHOR]

Huge coastal boulders are useful to reconstruct the size of past extreme waves such as those associated with tsunamis and storms using inverse-type or forward-type boulder transport models. These models fundamentally require the precise shape of boulders. Traditionally, they have often been assumed to be rectangular or ellipsoidal with three axes measured in the field. However, if the boulder's shape is complex, this method is unable to represent the actual shape accurately. Therefore, it prevents estimation of the tsunami or storm size reasonably using models. For this reason, boulders have recently been surveyed using 3D scanning techniques such as LiDAR. However, coastal boulders now on land in tropical and subtropical areas such as Japan and Tonga are often covered by deep vegetation, which makes 3D surveys difficult. This report presents new methods to ascertain boulder shapes when they are obscured by vegetation. First, using UAV-type and mobile-type LiDAR, we scanned well-known tsunami boulders in southwestern Japan that had been covered with deep vegetation. Then, we developed a new method to extract only boulders and filter out vegetation from a point cloud. Thereby, we created 3D models of the boulders. We improved the boulder transport model further to assume the 3D boulder model accurately. In addition to coastal boulders, this filtering method is expected to be useful for unveiling any object, such as an archaeological structure, that is hidden in deep vegetation. [ABSTRACT FROM AUTHOR]

Potential rockfall source areas are widely distributed in the high mountain areas of the Tibetan Plateau, posing significant hazards to human lives, infrastructures, and lifeline facilities. In a combination of field investigation, high-precision aerial photogrammetry, and numerical simulation, we took the Maoyaba basin as an example to explore a rapid identification method for high-altitude rockfall sources. An automatic potential rockfall source identification (PRSI) procedure was introduced to simplify the process of rockfall source identification. The study revealed that rockfall sources are concentrated in areas with intense frost weathering. Our identification results were validated using rockfall inventory data detection from remote sensing images and field investigation. Of the rockfall source areas identified by the PRSI procedure, 80.85% overlapped with the remote sensing images result. The accuracy assessment using precision, recall, and F1 score was 0.91, 0.81, and 0.85, respectively, which validates the reliability and effectiveness of the PRSI procedure. Meanwhile, we compared the rockfall source distribution of five DEMs with different resolutions and four neighborhood areas. We discovered that, in addition to high-resolution DEMs (i.e., 1 m and 2 m), medium-resolution DEMs (i.e., 5 m, 12.5 m) also perform well in identifying rockfall sources. Finally, we conducted a hazard assessment based on Culmann's two-dimensional slope stability model and rockfall hazard vector method. Appropriate protective measures should be taken at high-hazard sections to safeguard pedestrians, vehicles, and related infrastructure from rockfalls. [ABSTRACT FROM AUTHOR]

Mountain forests have a substantial protective function in preventing natural hazards, in part due to the presence of dead wood on the forest floor. Rates of deadwood accumulation have increased within the Alps and are predicted to rise further, due to natural disturbances. In particular, higher windthrow event frequencies are expected, primarily due to large-scale even-aged forest stands in many alpine regions combined with climate change. We quantified the rockfall protection effect of mountain forests with and without deadwood, in unprecedented detail, in experiments using two rock shapes with important hazard potential and masses of 200–3200 kg. Based on a multi-camera setup, pre- and post-experimentally retrieved high-resolution lidar data, and rock data measured in situ, we precisely reconstructed 63 trajectories. The principal parameters of interest describing the rockfall kinematics were retrieved for each trajectory. A total of 164 tree impacts and 55 deadwood impacts were observed, and the currently applied energy absorption curves – partially only derived theoretically – could consequently be corroborated or even expanded to a greater absorption performance of certain species than hitherto assumed. Standing trees, in general, and deadwood, in particular, were found to strongly impede the notorious lateral spreading of platy rocks. Platy rocks featured a shorter mean runout distance than their compact counterparts of similar weight, even in the absence of deadwood. These results indicate that the higher hazard potential of platy rocks compared with more compact rocks, previously postulated for open-field terrain, applies less to forested areas. Last, reproducing the experimental setting showcases how complex forest states can be treated within rockfall simulations. Overall, the results of this study highlight the importance of incorporating horizontal forest structures accurately in simulations in order to obtain realistic deposition patterns. [ABSTRACT FROM AUTHOR]

This paper presents the results of laboratory testing and Finite Element Method (FEM) modelling of high-strength double-twisted steel hexagonal wire mesh used for constructing gabion cages, slope protection systems, rockfall protection barriers. Gabion cages, filled with soil (usually rock particles) are commonly used in civil engineering (for example, in order to form a retaining wall). Static tensile tests of single wire and double-twisted wire were performed. The stiffness and ultimate tensile strength were examined. Special attention was paid to the double-twist behaviour. The unloading tests were also performed and the range of elastic deformation of both single wire and double-twisted wire were determined. The obtained laboratory results (stress--strain relationships for single wire and double-twisted wire) were included in a numerical model of the repeatable cell of mesh (truss model). The simulation in both directions, parallel and perpendicular to the double twist, was performed. On the basis of the obtained load-strain relationship, an anisotropic membrane model for mesh was proposed and calibrated. The obtained value of tensile strength of the mesh (266 kN/m) is much higher than for other meshes known form literature (30--60 kN/m). [ABSTRACT FROM AUTHOR]

Rockfall simulations are often performed at various levels of detail depending on the required safety margins of rockfall-hazard-related assessments. As a pseudo benchmark, the simulation results from different models can be put side-by-side and compared with reconstructed rockfall trajectories, and mapped deposited block fragments from real events. This allows for assessing the objectivity, predictability, and sensitivity of the models. For this exercise, mapped data of past events from the Mel de la Niva site are used in this paper for a qualitative comparison with simulation results obtained from early calibration stages of the Flow-R 2.0.9, Rockyfor3D 5.2.15 and RAMMS::ROCKFALL 1.6.70 software. The large block fragments, reaching hundreds of megajoules during their fall, greatly exceed the rockfall energies of the empirical databases used for the development of most rockfall models. The comparison for this challenging site shows that the models could be improved and that combining the use of software programs with different behaviors could be a workaround in the interim. The findings also highlight the inconvenient importance of calibrating the simulations on a per-site basis from onsite observations. To complement this process, a back calculation tool is briefly described and provided. This work also emphasizes the need to better understand rockfall dynamics to help improve rebound models. [ABSTRACT FROM AUTHOR]

The safety of buried gas pipelines in mountainous cities is at risk due to potential hazards such as landslides and rock falls. To ensure the safety of pipelines, this paper develops a three‐dimensional dynamic response model to reveal the impact of rockfall radius, rockfall impact velocity, and pipe burial depth on the dynamic response of buried polyethylene pipelines (PE pipelines) under rockfall conditions. Subsequently, an orthogonal experimental design and analysis of variance (ANOVA) are performed to identify critical factors. Ultimately, a multi‐factor limit state equation is constructed to assess the safety of PE pipelines accordingly failure prevention actions for buried gas pipelines under the impact of rockfall is specified. Overall, this proposed method contributes to safety analysis of buried PE pipelines in rockfall‐prone areas. [ABSTRACT FROM AUTHOR]

• The Bafoussam-Dshang region in West Cameroon Highlands records numbers of landslides. • The Analytical Hierarchical Process (AHP) delineate the landslide susceptibility. • Geology, orography, hydrography and vegetation cover are landslide causative factors. • Landslides susceptibility defines the Low, Moderate, High, and Very High classes. • Landslides fall into the high to very high susceptibility zone at ∼ 87% in the BDR. The main goal of this study is to produce a landslide susceptibility map of the Bafoussam-Dschang region (BDR) which is often subjected to landsliding by using Analytical Hierarchical Process (AHP). To achieve this objective, landslide triggering factors such as the lithology, slope, soil, land use, flow density, curvature, elevation and aspect have been combined with field observations. These Parameters were plotted on thematic layers using Geographical Information System (GIS) according to the AHP principles. Factors of weights were attributed based on the frequency of mass movements. The impact of one to another was assessed, allowing weights to be assigned to the different parameters. Subsequently, field observations revealed 100 mass movements including 97 landslides, 01 mudflow, 01 rock fall and 01 collapse within - the BDR. The field data including remote sensing techniques have subdivided the landslides susceptibility map into "Low (3%)", "Moderate (10%)", "High (21%)", and "Very High (66%)" susceptibility zones respectively. The majority of these mass movements fall into the high to very high susceptibility zones equivalent to ∼ 87% of landslides. These results permit to identify the landslide susceptibility zones linked to the steep landscaping West Cameroon Highland (Cameroon Volcanic Line). [ABSTRACT FROM AUTHOR]

Digital geological survey methods have become supplementary approaches for traditional geological survey in the last two decades. In this paper, the Unmanned Aerial Vehicle (UAV)‐based photogrammetry technology is used to obtain the 3D point cloud model of rock outcrops. The clustering algorithm is used to automatically identify the rock discontinuity parameters. However, the obtained 3D point cloud model with high resolution often has a huge point data which usually poses a great challenge to the computational efficiency of the automatic identification. In fact, too‐dense point cloud data may not be necessary for cases when the rock mass is relatively intact. The optimal point cloud resolution, which balances the accuracy and efficiency, depends on the degrees of fragmentation of the rock mass under investigation. For a model with the same resolution, large‐size discontinuities may have quite a few redundant point cloud data that are of little use to improve the identification accuracy whereas small‐size discontinuities may not be properly identified due to insufficient number of data points. In this paper, the influence of the degree of fragmentation of rock mass on the identified results was investigated. The uniform grid method was adopted to sparse the 3D point cloud model. The optimal point cloud resolution for different discontinuities was suggested. The applicability and feasibility of the proposed approach were verified via three illustrative examples of typical rock slopes. [ABSTRACT FROM AUTHOR]

Rockfall constitutes a major threat to the safety and sustainability of transport corridors bordered by rocky cliffs. This research introduces a new approach to rockfall susceptibility modeling for the identification of potential rockfall source zones. This is achieved by developing a data-driven model to assess the local slope morphological attributes with respect to the rock slope evolution processes. The ability to address "where" a rockfall is more likely to occur via the analysis of historical event inventories with respect to terrain attributes and to define the probability of a given area producing a rockfall is a critical advance toward effective transport corridor management. The availability of high-quality digital volumetric change detection products permits new developments in rockfall assessment and prediction. We explore the potential of simulating the conceptualization of slope-scale rockfall susceptibility modeling using computer power and artificial intelligence (AI). We employ advanced 3D computer vision algorithms for analyzing point clouds to interpret high-resolution digital observations capturing the rock slope evolution via long-term, LiDAR-based 3D differencing. The approach has been developed and tested on data from three rock slopes: two in Canada and one in the UK. The results indicate clear potential for AI advances to develop local susceptibility indicators from local geometry and learning from recent rockfall activity. The resultant models produce slope-wide rockfall susceptibility maps in high resolution, producing up to 75% agreement with validated occurrences. [ABSTRACT FROM AUTHOR]

This study evaluated the potential rockfall hazards in the Kayseri-Soğanlı settlement using the energy angle method and 3-dimensional probabilistic rockfall modeling. The high-resolution digital surface model (DSM) was obtained with the help of unmanned aerial vehicles (UAV) and high-resolution orthophoto. 3-dimensional probabilistic rockfall simulations were conducted on the DSM using the CONEFALL software, and rockfall zones were determined according to the energy line angle method. The dimensions of previously fallen rock blocks were determined using fieldwork and orthophoto generated by UAV. As a result of 3-dimensional probabilistic analyses, the maximum kinetic energy values of 15,000 kJ and bounce height of 15 m were determined during the movement of 3-meter rock blocks along the slope. When the energy line angle method was considered, it was found that the previously fallen blocks were mostly concentrated in the 40° energy line angle zone in the southern part of the slope. On the other hand, although the rolling lines obtained from probabilistic 3-dimensional rockfall analyses for 3 metre block size reach up to the maximum 30° energy line angle zone, these rolling lines end in the 40? energy line angle zone, especially in the southern part of the slope. Therefore, the empirical method, 3-dimensional probabilistic method, and the positions of measured blocks in the field show general consistency. [ABSTRACT FROM AUTHOR]

Light detection and ranging (LiDAR)-derived point cloud has become the standard spatial data for digital terrain model (DTM) construction; however, it suffers from huge data with much redundant information due to the oversampling. This often causes considerable inconvenience in the downstream data processing. To this end, an adaptive coarse-to-fine clustering and terrain feature-aware-based method is proposed to reduce data points in the context of terrain modeling in this paper. Firstly, a coarse-to-fine clustering method with the consideration of terrain complexity is developed to adaptively cluster LiDAR terrain points. Then, according to the geometric properties of terrain breaklines, a terrain feature-aware multi-strategy method is presented to pick representative points in the clusters. Finally, important boundary points including inflection point on the boundary curve and critical point on terrain features are further selected. The proposed method is compared with seven state-of-the-art point cloud simplification methods under six data reduction ratios on six plots with different terrain characteristics. Results indicate that the proposed method obtains a good balance between terrain-feature preservation and uniform distribution of data points. Compared to the state-of-the-art methods, the proposed method reduces the average root mean square errors (absolute errors) of the DTMs by 12.2%-51.7% (7.69%-83.8%) on the six plots. Moreover, the proposed method obtains the mean terrain slope and terrain roughness more reasonably approximate to the references. In short, the newly developed method can be considered as an alternative tool to select representative points from the huge remote-sensing-derived point cloud in the context of DTM production. [ABSTRACT FROM AUTHOR]

Building point clouds classification is an important task for a Smart City. This paper proposes a method based on multi‐scale and multi‐level cloth simulation to classify buildings in airborne LiDAR point clouds. First, the point clouds are preprocessed to denoise, filter ground and normalise height. The height distribution of point clouds in the whole area is then counted. Point clouds are segmented with similar heights on the top of the internal buildings by using the watershed algorithm based on height hierarchical labelling. Finally, the multi‐scale cloth simulation is used to crudely extract the seed points on the top of the buildings. These seed points are grown to realise the complete classification of airborne building point clouds. Multiple sets of data are selected for experimental verification. The results show that this method has higher classification accuracy and better applicability with a correct classification rate of 96.83%, 95.94% and 94.36%, and a recall rate of 98.18%, 96.32% and 92.33% in point level. [ABSTRACT FROM AUTHOR]

In this paper, a stability analysis method for the structure of a large tourist karst cave was proposed. The advantages of various point cloud acquisition technologies were considered, the collected point clouds were classified according to the characteristics of vegetation distribution and data acquisition. Then different algorithms were used to complete the ground point cloud filtering and registration. A three-dimensional model of the above-ground and underground integration of large karst caves was constructed in accordance with the accuracy requirements of general engineering applications using the Delaunay triangulation algorithm. This 3D model was taken as the simulation object, the strength and characteristics of the structure were calculated by the static analysis and modal analysis with fast computational speed, and then the deformation response of the structure was calculated by the dynamic time-history analysis during rare earthquakes. The results showed that: (1) the proposed algorithm of cloth simulation combined with the hue filter was effective in filtering point cloud in mountain terrain; (2) the over-ground and underground integrated modeling method was feasible; (3) the structure had no obvious structural damage during rare earthquakes. Finally, the 3D geospatial coordinates of the local stress concentration area were given, which can provide reference data for the protection work in the tourist development of the karst cave. A new idea for demonstrating structural safety before the development of karst cave tourism was provided. [ABSTRACT FROM AUTHOR]

Highlights: The experimental survival probability of one irregular shaped rock was established via 105 drop tests using mortar replicas. The derivation and validation of an analytical model to predict the survival probability of brittle rocks of irregular shape upon collinear impact is presented. The survival probability predicted by the model was found to fall withing 5% of the experimental data with an excellent goodness of fit coefficient (R2 ~ 93%). [ABSTRACT FROM AUTHOR]

The aim of this study was to delimit potential rockfall propagation zones based on simulated 2 m resolution rockfall trajectories using Rockyfor3D for block volume scenarios ranging from 0.05–30 m3, with explicit inclusion of the barrier effect of standing trees, for an area of approx. 7200 km2 in Switzerland and Liechtenstein. For the determination of the start cells, as well as the slope surface characteristics, we used the terrain morphology derived from a 1 m resolution digital terrain model, as well as the topographic landscape model geodataset of swisstopo and information from geological maps. The forest structure was defined by individual trees with their coordinates, diameters, and tree type (coniferous or broadleaved). These were generated from detected individual trees combined with generated trees on the basis of statistical relationships between the detected trees, remote sensing-based forest structure type definitions, and stem numbers from field inventory data. From the simulated rockfall propagation zones we delimited rockfall hazard indication zones (HIZ), as called by the practitioners (because they serve as a basis for the Swiss hazard index map), on the basis of the simulated reach probability rasters. As validation, 1554 mapped past rockfall events were used. The results of the more than 89 billion simulated trajectories showed that 94% of the mapped silent witnesses could be reproduced by the simulations and at least 82% are included in the delimited HIZ. [ABSTRACT FROM AUTHOR]

Low-energy rockfall catch fences are designed to protect infrastructure such as railways and roads wherein the kinetic energy of falling rocks is less than 100 kJ. The typical design consists of a double-twisted steel wire mesh supported by ground posts and strengthened by anchoring wire ropes. The fence stops falling rocks by dissipating the impact energy mainly through elastoplastic stretching of steel wires in the mesh. In this study, a three-dimensional finite element model for double-twisted wire mesh was developed in Abaqus/Explicit. The model has been verified using both quasi-static loading and impact tests. It was found that proper geometrical representation is essential for accurate simulation of wire deformation modes and the interaction between double-twisted wires. The model also enables the application of the real stress–strain relationship of a single steel wire in constitutive models. [ABSTRACT FROM AUTHOR]

Although the principal aim of the rockfall management is to prevent rock boulders from reaching the buildings instead of the buildings resisting the boulder impacts, there usually exists a residual risk that has to be assessed, even when structural protection measurements are taken. The evaluation of the expected damage of buildings due to rockfalls using empirical data from past events is not always possible, as transferring and applying damage observations from one area to another can be unrealistic. In order to simulate potential rockfall scenarios and their damage on buildings, numerical methods can be an alternative. However due to their increased requirements in expertise and computational costs, their integration into the risk analysis is limited, and simpler tools to assess the rockfall vulnerability of buildings are needed. This paper focuses on the application of artificial intelligence AI methods for providing the expected damage of masonry walls which are subjected to rockfall impacts. First, a damage database with 672 datasets was created numerically using the particle finite element method and the finite element method. The input variables are the rock volume (VR), the rock velocity (RV), the masonry wall (t) and the masonry tensile strength f m . The output variable is a damage index (DI) equal to the percentage of the damaged wall area. Different AI algorithms were investigated and the ANN LM 4-21-1 model was selected to optimally assess the expected wall damage. The optimum model is provided here (a) as an analytical equation and (b) in the form of contour graphs, mapping the DI value. Known the VR and the RV, the DI can be directly used as an input for the vulnerability of masonry walls into the quantitative rockfall risk assessment equation. [ABSTRACT FROM AUTHOR]

For autonomous vehicles, the acquisition frequency difference between LiDAR (10–20 Hz) and camera (over 100 Hz) makes simultaneous update of two perceptive systems (2D/3D) less efficient. Nowadays, frame interpolation is in urgent need for increasing frame rate of point cloud sequences obtained by LiDAR. However, a major limitation of current full supervised methods is that high frame rate ground truth sequences are hard to access. We propose a novel Self-supervised Point Cloud Frame Interpolation Network (SPINet) accommodating with variable motion situation, retaining geometric consistency, but without the necessity of utilizing G.T. data. Extensive experiments show that our proposed SPINet outperforms the current full supervised methods. [ABSTRACT FROM AUTHOR]

Gravel cushions are widely laid on the top of structures or rock sheds to absorb the impact energy of rockfalls in mountainous districts. Based on the discrete element method, a numerical model of a rockfall impacting a 2D mixed-size gravel cushion layer at an initial angular velocity was established in this study. The penetration depth of the rockfall, impact force of the cushion surface, and energy dissipation ratio were investigated. Increasing the initial angular velocity and decreasing the particle size of the cushion were found to evidently reduce the maximum penetration depth of the rockfall and increase the impact force of the cushion surface, respectively. The energy dissipation ratio after collision was affected by the particle size of the cushion and the ratio of the angular kinetic energy. Omitting the initial angular velocity led to an underestimation of the energy dissipation ratio, by up to 40.8%. With decreasing particle size of the cushion, the energy dissipation ratio first increased but then decreased. The study results provide a theoretical basis for the design of gravel cushions intended for rockfall protection. [ABSTRACT FROM AUTHOR]

The digital preservation of heritage resources has emerged as an essential method for communicating the significance of artifacts, buildings, and landscapes to descendant communities and the wider public. While virtual representations are becoming more commonplace, physical representations (physicalization) of heritage sites via 3D printing are used to a lesser degree. Physicalization provides new perspectives through the interplay between touch and vision and can facilitate a deeper understanding of the history being conveyed. This paper discusses how the physical models of heritage buildings and landscape features on Qikiqtaruk/Herschel Island Territorial Park were created from terrestrial laser scanning and UAV photogrammetry data. We demonstrate how to use this physicalization of polar heritage to communicate the significance of the buildings and landscape of the island to the local Indigenous communities and global audiences, as well as how they are being threatened by climate change. We also explore the transformation of a cove on the island into puzzles and data sculptures. In addition to the Cove, the fabricating of important buildings on larger scales has been a requirement. This multi-scale printing raises the issue of connecting the large-scale buildings with their small instances/copies on the Island (similar to focus + context visualization in the digital form). Due to the limitation of physicalization compared with digital representations, new methods, metaphors and designs are needed for supporting focus + context visualization. We have designed and implemented several such methods in our specific physicalization of heritage buildings and landscape on Qikiqtaruk/Herschel Island. We presented our physicalizations to the members of the Inuvialuit community of Aklavik NWT and received a positive response. [ABSTRACT FROM AUTHOR]

Since the launch of the Special Issue, a total of 39 well-known scholars have submitted their research work to this Special Issue. Special Issue Content Gao et al. [[1]] established a unified model based on transfer learning for cross-regional DFSM to realize the rational use of debris flow sample resources and improve the modeling efficiency. This Special Issue aims at soliciting contributions within the scope of the comprehensive risk assessment methods and hazards early warning system of geological hazards on major projects in the mountain area. [Extracted from the article]

Terrain models are widely used to depict the shape of the Earth's surface. With the development of photogrammetric methods, point cloud data have become one of the most popular data sources for terrain modelling. However, the obtained point clouds are of high density, which often increases redundancy rather than improving accuracy. Therefore, point cloud simplification should be a core component of terrain modelling. This paper proposes a point cloud simplification method by integrating topographic knowledge into terrain modelling (TKPCS). The method contains two steps: (1) topographic knowledge recognition and construction and (2) point cloud simplification using this topographic knowledge for terrain modelling. The proposed approach is benchmarked against improved versions of existing methods to validate its capability and accuracy in digital elevation model construction and terrain derivative extraction. The results show that the simplified points of the TKPCS method can generate finer resolution terrain models with higher accuracy and greater information entropy. The good performance of the TKPCS method is also stable at different scales. This work endeavours to transform perceptive topographic knowledge into a process of point cloud simplification and can benefit future research related to terrain modelling. [ABSTRACT FROM AUTHOR]

This study is addressed at the cultural heritage of the UNESCO historical centre of Urbino (Italy) through the focus on a very peculiar building and ornamental carbonate porous (spongy) stone also found in the opus quadratum Roman dry walls. For these rocks, the mathematician and historian Bernardino Baldi (16th century AD) and the mineralogist Francesco Rodolico (middle of the 20th century AD) introduced, respectively, the popular terms of Tufo spugnoso or Pietra Spugna. Physical observations and stable isotope data (δ13C and δ18O) of these rocks allowed, for the first time, their classification as calcareous tufas, thus contributing to the valorization of the stone heritage of the city. This carbonate lithotype was formed by the chemical precipitation of CaCO3, driven by the CO2 degassing of supersaturated calcium-bicarbonate-rich waters, coupled with the passive encrustations of organic material in continental environments. Radiocarbon analyses dated these stones mostly between 9100 and 4700 yr. BP when a maximum growth of these carbonate continental deposits occurred in Mediterranean regions and northern Europe, i.e., during the Holocene Atlantic climatic optimum. Work is still in progress on a perched springline of calcareous tufas found along the Metauro Valley (a few km from Urbino), being good candidates for provenance, at least for those blocks exploited by the Romans and successively reused in the architectural framework of Urbino. [ABSTRACT FROM AUTHOR]

Bridges located in mountainous areas are vulnerable to rockfall accidents, posing a threat to bridge engineering construction and operation safety in these regions. Under the coupling effect of complex environments and engineering disturbances, integrated rockfall risk simulation has become increasingly important for canyon bridge structural protection in long‐term construction and operation phases. One of the main scientific challenges in rockfall risk simulation is studying the interaction between rockfalls and the topography and engineering environments during consecutive contacts. To systematically simulate the integrated bridge rockfall risk, an integrated construction of multivariable elements coupled with rockfall risk environments and scenarios is required. In this article, we proposed a VGE‐based integrated rockfall scenario simulation method that uses the "associated representation—integrated modelling—interactional simulation" core strategy. Our method constructs a virtual rockfall risk environment by fusing multisource data to represent rockfall factors that induce rockfall disasters, hazard‐forming environments, and elements at risk. We design rockfall scenarios under different bridge engineering construction conditions and extreme environmental conditions to analyze the interactional rockfall risks. The results demonstrate that our method enables a systematic analysis of the potential integrated rockfall risk, providing realistic reference value for the timely and effective disposal of emergencies, and reducing the harm and losses caused by such emergencies. [ABSTRACT FROM AUTHOR]

Quantitative hazard analysis of rockfalls is a fundamental tool for sustainable risk management, even more so in places where the preservation of natural heritage and people's safety must find the right balance. The first step consists in determining the magnitude-frequency relationship, which corresponds to the apparently simple question: how big and how often will a rockfall be detached from anywhere in the cliff? However, there is usually only scarce data on past activity from which to derive a quantitative answer. Methods are proposed to optimize the exploitation of multi-source inventories, introducing sampling extent as a main attribute for the analysis. This work explores the maximum possible synergy between data sources as different as traditional inventories of observed events and current remote sensing techniques. Both information sources may converge, providing complementary results in the magnitude-frequency relationship, taking advantage of each strength that overcomes the correspondent weakness. Results allow characterizing rockfall detachment hazardous conditions and reveal many of the underlying conditioning factors, which are analyzed in this paper. High variability of the hazard over time and space has been found, with strong dependencies on influential external factors. Therefore, it will be necessary to give the appropriate reading to the magnitude-frequency scenarios, depending on the application of risk management tools (e.g., hazard zoning, quantitative risk analysis, or actions that bring us closer to its forecast). In this sense, some criteria and proxies for hazard assessment are proposed in the paper. [ABSTRACT FROM AUTHOR]

We examine the coseismic influence of the 5 July 2019, MW7.1 Ridgecrest and the 24 June 2020 MW5.8 Owens Lake earthquakes on rockfall distributions in two undisturbed high-altitude areas of the southern Sierra Nevada Mountains, California, USA. These events occurred within the geologically recent (<2 Mya) Walker Lane/eastern California shear zone. While both study areas are characterized as plutonic, the Owens Lake event largely affected terrain that was formerly glaciated and oversteepened while the Ridgecrest event affected non-glaciated terrain. Our inventory of rockfall locations was derived from analysis of Sentinel-2 images acquired just prior to and immediately after the events. This difference mapping approach using readily-available Sentinel-2 imagery allows for rapid rockfall and landslide mapping. GIS analysis shows that even though the total area assessed for both earthquakes was similar (~1500 km2), the significantly lower magnitude Owens Lake event produced nearly twice as many (102) mappable rockslides as the significantly stronger Ridgecrest event (58), a difference likely due to slope oversteepening in the formerly glaciated area. Significant seismic amplification by topography and reactivation of preexisting failures was apparent for both areas. Inclusion of these factors may improve failure predictions and rockfall probability estimation. [ABSTRACT FROM AUTHOR]

With the rapid development of urban rail transit and the aging of transportation infrastructure, the demand for shield tunnel disaster detection is about to break out. Most of the traditional monitoring methods require considerable manpower and time costs, which cannot satisfy the increasing requirements of tunnel operation and maintenance. Free-form model construction and deviation mechanism analysis are investigated in this paper to monitor the geometric deformation information of shield tunnels quickly and accurately. A method for identifying geometric features of tunnel sections based on the free-form B-spline approximation is proposed. The innovation of this paper lies in the intelligent recognition of common interference targets by the residual classification method. Furthermore, various Root Mean Squared Error (RMSE) distributions are investigated, which successfully realizes and verifies the clustering analysis of certain point cloud features. [ABSTRACT FROM AUTHOR]

Collapse hazards occur frequently in mountainous areas. Geosynthetics-reinforced soil (GRS) wall, combing the damping characteristics of soil and the tensile properties of reinforcement materials, can effectively resist rockfall impact through its flexible deformation. However, excessive deformation is easy to occur near the impact point of reinforced soil retaining wall subjected to impact loading, resulting in instantaneous instability and long repair time as well as high repair cost of the structure. Therefore, the prestressed GRS wall with buffer layer was proposed in this paper. Four retaining walls with different types and the impactor consist of pendulum device and solid steel ball was designed to study the impact resistance and dynamic stability of the retaining wall. The results show that the cumulative deformation of the wall panel experiences acceleration phase, deceleration phase and stable stage subjected to the impact loading. The application of buffer layer and prestress member can effectively improve the impact resistance and dynamic stability of retaining wall, and further control the deformation of retaining wall under the impact loading, in comparison with ordinary reinforced retaining wall. The peak impact stress of the retaining wall and the responsive strain of the reinforcement increase gradually as the distance between the measure point and the impact point decreases. The research results can provide reference for the design and the application of prestressed GRS wall under the impact of rockfall. [ABSTRACT FROM AUTHOR]