Rockfall Source Areas Research Articles

Impact of discontinuity data acquisition methods on rockfall susceptibility assessment using high-resolution 3D point cloud

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.

A Novel Approach to Assess the Influence of Rockfall Source Areas: The Case Study of Bardonecchia (Italy)

In this research article, we propose a practical methodology for evaluating the affecting potential of detachment areas in rockfalls. Our innovative approach combines an assessment of the visibility of rockfall source areas, with reference to specific rockfall scenarios and elements at risk, considering the rockfall Susceptibility Index to Failure (SIF) of these areas. The result is the characterization of source areas through a rockfall Source Affecting Index (SAI), which considers both the morphology of the slope and the geostructural conditions of the rock walls. This information can be very useful since it aids in optimizing more in-depth analyses, as well as the placement of monitoring instruments or stabilization systems. The proposed methodology has been implemented in the open-source software QGIS through the development of an easy-to-use plugin named Ranking of the Affecting Potential of Detachment Areas in Rockfalls, or “RADAR”. RADAR is designed to be used in conjunction with QPROTO, a well-known QGIS plugin for preliminary rockfall susceptibility/hazard analyses based on a visibility analysis and a simplified mechanical method. To demonstrate the effectiveness of the proposed approach, an application to a case study located in the Western Alps (Bardonecchia, Italy) is presented and discussed in the paper.

Potential Rockfall Source Identification and Hazard Assessment in High Mountains (Maoyaba Basin) of the Tibetan Plateau

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.

Digital Rock Mass Analysis for the Evaluation of Rockfall Magnitude at Poorly Accessible Cliffs

The analysis of a digital rock cliff model, built by airborne photogrammetric data and infrared thermal images, is herein presented as an alternative tool for rock mass study in restricted and poorly accessible areas. Photogrammetric and infrared thermography techniques were combined for the geostructural and morphological characterization of an unstable cliff located in a nature reserve, where the rock mass extension and the environmental preservation rules required the use of minimally invasive surveying solutions. This methodological approach provided quantitative and qualitative data on both the spatial orientation of discontinuities and the location of major structural features, jutting blocks and past rockfall source areas. The digitally derived spatial data were used to carry out a rock mass kinematic analysis, highlighting the most recurring unstable failure patterns. Thermal images were overlapped to the photogrammetric cliff model to exploit the data combination and to analyze the presence of protruding rock mass volumes to be referred to as potential unstable volumes. Based on this activity, rock volumes were quantified on the digital model and the results were used to provide a zonation map of the potential magnitude of future rockfalls threatening the reserve. Digital data were validated by a field surveying campaign, which returned a satisfactory match, proving the usefulness and suitability of the approach, as well as allowing the quick and reliable rock mass characterization in the frame of practical use and risk management purposes.

Rockfall source areas identification at local scale by integrating discontinuity-based threshold slope angle and rockfall trajectory analyses

Rockfall source areas identification of high steep fractured rock slope is a challenging task for hazard mitigation. Considering this difficulty, a new method integrating discontinuity-based threshold slope angle and rockfall trajectory analyses is introduced in this study and applied to a railway bridge in China. First, abundant discontinuity data are collected by means of the modern unmanned aerial vehicle (UAV) digital photogrammetry technique. Then, a threshold slope angle used to delineate rockfall-prone areas is comprehensively determined by probabilistic kinematic and block theory analyses. Next, physically based rockfall trajectory simulation with consideration of mean block size is used to distinguish the hazard level of each release point. Finally, rockfall sources causing moderate and high risks to the train tunnel entrance at the base of high steep fractured rock slope are determined using a semiquantitative risk matrix approach. The final rockfall source map can provide a quantitative reference for hazard mitigation. At the end of this paper, some issues associated with the proposed approach are discussed, such as parameter importance analysis of threshold slope angle, comparison between the two probabilistic approaches and uncertainties in rockfall source areas identification.

Rockfall Hazard Assessment in the Taihang Grand Canyon Scenic Area Integrating Regional-Scale Identification of Potential Rockfall Sources

Frequent rockfall events pose a major threat to the safe operation of the Taihang Grand Canyon Scenic Area (GCSA) in China. The traditional techniques for identifying potential rockfall sources and hazard assessment methods are often challenged in the alpine canyon landform. This study aims to establish an early identification framework for regional potential rockfall sources applicable to the canyon region and to assess rockfall hazards in potentially hazardous areas using unmanned aerial vehicle (UAV) photogrammetry. Specifically, by incorporating high-precision topographic information and geotechnical properties, the slope angle distribution method was used for static identification of potential rockfall sources. Moreover, SBAS-InSAR technology was used to describe the activity of potential rockfall sources. Finally, taking the key potentially hazardous area of the Sky City scenic spot as an example, the Rockfall Analyst tool was used to analyze the rockfall frequency, bounce height and energy characteristics based on the high-precision UAV 3D real scene model, and the analytic hierarchy process was introduced to achieve quantitative rockfall hazard assessment. The results show that the potential rockfall source areas in the Taihang GCSA is 33.47 km2 (21.47%), mainly distributed in strips on the cliffs on both sides of the canyon, of which the active rockfall source area is 2.96 km2 (8.84%). Taking the scenic spot of Sky City as example, the proposed UAV-based real scene modeling technology was proven to be able to quickly and accurately construct a 3D high-precision model of the canyon area. Moreover, the 3D rockfall simulation showed that the high-energy rockfall area was mainly distributed at the foot of the steep cliff, which mainly threatens the tourist distribution center below. The early identification and quantitative evaluation scheme of rockfall events proposed in this study can provide technical reference for the prevention and control of rockfall hazards in similar alpine valley areas.

Identification of rockfall source areas using the seed cell concept and bivariate susceptibility modelling

The objective of this research was to prepare a rockfall susceptibility map. Explorations were conducted in the Dubračina River basin (Croatia). The input data included a geological map, an orthophoto and a 1-m digital terrain model (DTM). After a talus inventory was prepared, the seed cell concept was applied to define the rockfall source areas. The contributing factors (predictors) of rockfalls were evaluated by the chi-squared test. The analysis confirmed the following predictors: CORINE land cover, lithology, slope, aspect, distance from a spring, distance from a road, distance from a fault, distance from a stream, and distance from the rock-soil geological boundary. A matrix pairwise comparison of the predictor ratings was used to define the most significant contributing factors. The predictors that affected the susceptibility map in the share of 86.3% were the slope (61.6%), lithology (13.4%), CORINE land cover (6.2%), and distance from the rock-soil geological boundary (5.1%). Two susceptibility maps were prepared: one using all nine contributing factors and another using the four most significant factors. The analysis showed that both maps were good, with the same areas under the receiver operating characteristic (ROC) curves. The map prepared with only four contributing factors can be considered a better map due to its more precise spatial definition of critical areas. It can be concluded that geological map, 1-m DTM and orthophoto provide enough data to prepare reliable rockfall susceptibility map. The application of the bivariate statistical zonation method called the “frequency ratio method” was proven to be successful. This research demonstrates that the application of the seed cell concept can be useful to speed up the process of rockfall source area detections in large research regions.

Rockfall hazard assessment of the Monte Gallo Oriented Nature Reserve area (Southern Italy)

The Monte Gallo area is a carbonate relief that develops a significant nature reserve and highly attracts tourism to the urbanized area of the City of Palermo (Southern Italy). The slopes are affected by several rockfall events, which have also caused death, injuries, material damage, and a strong social and economic impact. Here, a detailed geological and geotechnical study to assess the rockfall hazard relating to two sectors of the mount has been carried out. The hazard assessment at the slope scale was performed based on geological, geomorphological, geomechanical, and seismic analysis. Using both analytical and empirical methods and by means of different software, the reconstruction of the propagation areas for the eastern sector of the Mount was possible. Results were used to better understand the overall structure, characterize the rockfall source areas’ kinematics, and recognize the basic failure mechanisms. The obtained runout areas were compared with each other and with those of previous studies conducted in a neighboring area, as well as with the corresponding hazard area maps of the official cartography, which is being updated. It is expected to be supplemented with maps derived from empirical models.

Identification of potential rockfall sources using UAV-derived point cloud

Recent advances in remote sensing techniques and computer algorithms allow accurate, abundant, and high-resolution geometric information retrieval for rock mass characterization from 3D point clouds. The automatic application of the extracted information for local scale rockfall susceptibility assessment, where discontinuities characteristics play a major role in rocky slope stability, requires step by step logical procedures. This paper presents a novel methodology to use the extracted discontinuity set characteristics for a local scale rockfall susceptibility assessment, tailored for Uncrewed Aerial Vehicle (UAV) data acquisition. The method consists of 4 steps: (i) 3D slope model reconstruction using UAV digital photogrammetry, (ii) automatic characterization of discontinuity sets, (iii) slope stability analysis, and (iv) susceptibility assessment using a new Rockfall Susceptibility Index. The proposed method was applied to a road cut rocky slope in a mountainous area of the Samaria National Park, in Crete Island, Greece. Visual validation indicates that the areas of higher and moderate rockfall susceptibility on the 3D model of the rocky slope are adjacent to rockfall source areas marked by the presence of fallen blocks on the foot of the slope. The proposed methodological workflow presents novelties related to the use of point clouds for the estimation of the Rock Quality Designation (RQD) index, the visualization of discontinuity set spacing, the evaluation of the persistence and the Slope Mass Rating (SMR) index, as well as the incorporation of the persistence of overhangs into the rockfall susceptibility assessment and visualization.

A New Approach for Identification of Potential Rockfall Source Areas Controlled by Rock Mass Strength at a Regional Scale

The identification of rockfall source areas is a fundamental work for rockfall disaster prevention and mitigation. Based on the Culmann model, a pair of important indicators to estimate the state of slope stability is the relief and slope angles. Considering the limit of field survey and the increasing requirements for identification over a large area, a new approach using the relief–slope angle relationship to identify rockfall source areas controlled by rock mass strength at a regional scale is proposed in this paper. Using data from helicopter-based remote sensing imagery, a digital elevation model of 10 m resolution, and field work, historical rockfalls in the Wolong study area of Tibet where frequent rockfalls occur are identified. A clear inverse relationship between the relief and slope angles of historical rockfalls enables us to calculate the rock mass strength of the landscape scale by the Culmann model and the relief–slope angle relationship curve. Other parameters used in our proposed approach are calculated by ArcGIS and statistic tools. By applying our approach, the potential rockfall source areas in the study are identified and further zoned into three susceptibility classes that could be used as a reference for a regional rockfall susceptibility study. Using the space partition of historical rockfall inventory, our prediction result is validated. Most of the rockfall source areas (i.e., 71.92%) identified in the validation area are occupied by historical rockfalls, which proves the good prediction of our approach. The dominant uncertainty in this paper is derived from the process of calculating rock mass strength, defining the specific area for searching potential rockfall source areas, and the resolution of the digital elevation model.

Probabilistic identification of rockfall source areas at regional scale in El Hierro (Canary Islands, Spain)

Modelling rockfall phenomena is complex and requires various inputs, including an accurate location of the source areas. Source areas are controlled by geomorphological, geological, or other geo-environmental factors and may largely influence the results of the modelling. In the Canary Islands, rockfalls are extremely common and pose a major threat to society, costing lives, disrupting infrastructure, and destroying livelihoods. In 2011, the volcanic event on the island of El Hierro triggered numerous rockfalls that affected strategic infrastructures, with a substantial impact on the local population. During the emergency, the efforts performed to map the source areas and to model the rockfalls in the considerably steep landscape characterising the island were not trivial. To better identify the rockfall source areas, we propose a probabilistic modelling framework that applies a combination of multiple statistical models using the source area locations mapped in the field as the dependent variable and a set of thematic data as independent variables. The models use as input morphometric parameters derived from the Digital Elevation Model and lithological data as an expression of the mechanical behaviour of the rocks. The analysis of different training and validation scenarios allowed us to test the model sensitivity to the input data, select the optimal model training configuration, and evaluate the model applicability outside the training areas. The final map obtained from the model for the entire island of El Hierro provides the probability of a given location being a potential source area and can be used as the input for rockfall runout simulation modelling.

High mountain rockfall dynamics: rockfall activity and runout assessment under the aspect of a changing cryosphere

ABSTRACT Rockfalls are a major aspect concerning morphodynamics in high mountain areas and represent a serious hazard for people and infrastructure. Recently, an increase of rockfall activity has been observed which is probably related to the destabilization of rock slopes through climate-related changes of the mountain cryosphere. This study investigates the rockfall distribution during a 4-year monitoring period by systematic observation with bi-temporal Airborne Laser Scanning DTMs in an area of 610.7 km² in the Ötztal Alps/Tyrol, Austria. The analyses of the 93 detected rockfall events indicate that rockfall activity is highest in proglacial areas. Further 83.9% of all rockfall source areas were mapped in bedrock where the modelled mean annual ground temperature (MAGT) indicates perennial frozen conditions. The results demonstrate the importance of thermal effects on the destabilization of rock faces and show that the triggering of rockfalls is closely related to changes in the glacier and permafrost regime. 18 low-magnitude rockfalls with volumes between 69 ± 3 m³ and 8420 ± 89 m³ are examined in detail. On the base of the analysis of these events energy line angles of 28.7° for the Fahrböschung and 19.9° for the minimum shadow angle can be derived and significantly longer runout distances on glaciated rockfall paths are observed.

A New Methodology for Mapping Past Rockfall Events: From Mobile Crowdsourcing to Rockfall Simulation Validation

Rockfalls are one of the most common natural hazards in mountainous areas that pose high risk to people and their activities. Rockfall risk assessment is commonly performed with the use of models that can simulate the potential rockfall source, propagation and runout areas. The quality of the models can be improved by collecting data on past rockfall events. Mobile crowdsourcing is becoming a common approach for collecting field data by using smartphones, the main advantages of which are the use of a harmonised protocol, and the possibility of creating large datasets due to the simultaneous use by multiple users. This paper presents a new methodology for collecting past rockfall events with a mobile application, where the locations and attributes of rockfall source areas and rockfall deposits are collected, and the data are stored in an online database which can be accessed via the WebGIS platform. The methodology also presents an approach for calculating an actual source location based on viewshed analysis which greatly reduces the problem of field mapping of inaccessible source areas. Additionally, we present a rockfall database in the Alpine Space that has been created by the presented methodology, and an application of collected data for the calibration and validation of two rockfall models (CONEFALL and Rockyfor3D).

Rockfall Investigation and Hazard Assessment from Nang County to Jiacha County in Tibet

The influences of rockfall on human engineering have been increasing in Tibet with the rapid development of the western region of China. This study proposed a multi-approach to carry out rockfall investigation and hazard assessment. As a case study, the rockfall hazard from Nang County to Jiacha County in Tibet was assessed. Firstly, we summarized the characteristics of spatial distributions of typical rockfall sources using Digital Elevation Model (DEM) and unmanned aerial vehicle (UAV) aerial images with resolution of 10 m. According to the thresholds of slope angle, slope aspect and elevation distribution of typical rockfall sources, we obtained all of the rockfall source areas in study area semi-automatically in ArcGIS platform. Secondly, we improved the efficiency and accuracy of detailed field investigation by using a three-dimensional (3D) point cloud model and rock mass structure extraction software. According to the analysis result, the dominant joint set was J1, whose orientation was basically consistent with the Yarlung Tsangpo Fault. The combination of J1, J2 and J4 cut the rock mass into blocks of wedge with J1 as potential sliding planes. It was indicated that the stability of the rock mass in study area was mainly controlled by the characters of joint sets. Finally, we applied the improved reclassification criteria of the Rockfall Hazard Vector (RHV) method in rockfall hazard assessment according to protection capabilities of the current protection facilities, making the result more valuable for geohazards prevention work. Based on this multi-approach, we obtained that 10.92% of the 306 provincial highway and 9.38% of the power line were threatened by potential rockfall hazards in study area. The hazard assessment results of study area were also of certain guiding value to the linear project planning and geohazards prevention work.

Reconstruction of Surficial Rock Blocks by Means of Rock Structure Modelling of 3D TLS Point Clouds: The 2013 Long-Chang Rockfall

Terrestrial laser scanning (TLS) enables the digital representation of rock outcrops with unprecedented resolution and accuracy. Currently, extracting full-scale block structures from raw TLS data (e.g. for assessing rockfall source areas) requires special techniques. This contribution describes processing methods for reconstructing three-dimensional representations of blocky rock masses from raw point cloud data. The developed workflow involves extracting structural and topographical details, fitting location-dependent discontinuities bounding the rock blocks, and reconstructing the block array embedded in three-dimensional geomorphology. The method is applied to a case study of the 2013 Long-Chang rockfall located in the Guizhou Province of China. Based on these initial results, the workflow will be applied to rockfall source evaluations throughout the karstified Kaili region within Guizhou.

Augmented Reality Mapping of Rock Mass Discontinuities and Rockfall Susceptibility Based on Unmanned Aerial Vehicle Photogrammetry

In rockfall hazard management, the investigation and detection of potential rockfall source areas on rock cliffs by remote-sensing-based susceptibility analysis are of primary importance. However, when the rockfall analysis results are used as feedback to the fieldwork, the irregular slope surface morphology makes it difficult to objectively locate the risk zones of hazard maps on the real slopes, and the problem of straightforward on-site visualization of rockfall susceptibility remains a research gap. This paper presents some of the pioneering studies on the augmented reality (AR) mapping of geospatial information from cyberspace within 2D screens to the physical world for on-site visualization, which directly recognizes the rock mass and superimposes corresponding rock discontinuities and rockfall susceptibility onto the real slopes. A novel method of edge-based tracking of the rock mass target for mobile AR is proposed, where the model edges extracted from unmanned aerial vehicle (UAV) structure-from-motion (SfM) 3D reconstructions are aligned with the corresponding actual rock mass to estimate the camera pose accurately. Specifically, the visually prominent edges of dominant structural planes were first explored and discovered to be a robust visual feature of rock mass for AR tracking. The novel approaches of visual-geometric synthetic image (VGSI) and prominent structural plane (Pro-SP) were developed to extract structural planes with identified prominent edges as 3D template models which could provide a pose estimation reference. An experiment verified that the proposed Pro-SP template model could effectively improve the edge tracking performance and quality, and this approach was relatively robust to the changes of sunlight conditions. A case study was carried out on a typical roadcut cliff in the Mentougou District of Beijing, China. The results validate the scalability of the proposed mobile AR strategy, which is applicable and suitable for cliff-scale fieldwork. The results also demonstrate the feasibility, efficiency, and significance of the geoinformation AR mapping methodology for on-site zoning and locating of potential rockfalls, and providing relevant guidance for subsequent detailed site investigation.

Influence of digital elevation model resolution on rockfall modelling

Spatial models are an effective tool for determining potential rockfall source, transit and deposit areas. The reliability of the final rockfall modelling results depends on the quality of the input data, which is mostly based on the digital elevation model (DEM). The spatial resolution of the DEM holds key information about the main morphological properties of the surface, which is crucially important when modelling this kind of geomorphological phenomenon. Therefore, this article studies the influence of DEM spatial resolution on the modelling of rockfall source, transit and deposit areas. Modelling was carried out at five different DEM spatial resolutions available for Slovenia (1 m, 5 m, 12.5 m, 25 m and 100 m). Rockfall source areas were identified using a geomorphometric approach based on a high resolution DEM and a geographical information system. Rockfall transit and deposit areas were modelled using the Conefall computer program, which is designed to estimate potential rockfall risk areas. The area of study was the municipality of Vipava (107.4 km2) in Slovenia, EU. A spatial resolution of 1 m was chosen as a reference layer to which all modelling results of the other spatial resolutions were compared. Validation of modelling included rockfall source area comparison with orthorectified aerial images and location collection of silent witnesses (rock deposits) in the field for estimating maximum runout zones. The modelling results indicate that a spatial resolution of 1 m is the most suitable for modelling on a local scale; resolutions of 5, 12.5 and 25 m can be used for modelling on a regional scale (depending on the purpose of the modelling results); and a resolution of 100 m should not be used for rockfall modelling. Major differences between spatial resolutions can be observed when modelling rockfall source areas, i.e. in areas with the most diverse topography, while in deposit areas the observed differences are smaller due to the less rugged surface.

A novel rockfall hazard assessment using laser scanning data and 3D modelling in GIS

Rockfall hazards occur widely in regions with steep terrain such as Kinta Valley, Malaysia. Rockfalls threaten urban areas and the transportation corridors that pass through such areas. This paper proposes a comprehensive rockfall hazard assessment strategy based on high-resolution laser scanning data (LiDAR), both airborne and terrestrial. It provides (1) rockfall source identification by developing a hybrid model based on a bagging neural network (BBNN), which is compared with various machine learning algorithms and ensemble models (bagging, boosting, voting) and a Gaussian mixture model; (2) 3D modelling of rockfall kinematic processes (trajectory distribution, frequency, velocity, kinetic energy, bounce height, impact location); and (3) hazard zonation based on spatial modelling in combination with an analytical hierarchy process (AHP) in a geographic information system (GIS). In addition, mitigation measures are suggested based on the modelling results. The proposed methodology was validated in three study areas to test the applicability and generalisability of the methods. The results show that the proposed hybrid model can accurately identify rockfall source areas at the regional scale. It achieved a 97% training accuracy and 5-fold cross-validation area under curve (AUC) value of 0.96. The mechanical parameters of the developed 3D model were calibrated with an accuracy of 97%, 93% and 95% for Gunung Lang, Gua Tambun and Gunung Rapat areas, respectively. In addition, the proposed spatial model effectively delineates areas at risk of rockfalls. This method provides a comprehensive understanding of rockfall hazards that can assist authorities to develop proper management and protection of urban areas and transportation corridors.

A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data

The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.

The artificial neural network for the rockfall susceptibility assessment. A case study in Basilicata (Southern Italy)

This paper presents the results obtained by the elaboration of an artificial neuronal network for the creation of a rockfall susceptibility map. The analysis was carried out by analysing the predisposing and triggering factors of the rockfall phenomenon. The parameters considered for this study and representing the input data of the artificial neural network are factors such as: gradient, soil use, lithology, rockfall source areas and kinetic energy values obtained by considering the probable pathways of the blocks through simulations with dedicated softwares, DEMs and niches of the rockfalls that have already occurred in the past. The processing of this data (required in a versatile dedicated software for the realization of the artificial neural network in ASCII format) is done using GIS softwares, useful tools for the creation of hazard maps. An important step is the realization of the rockfall inventory map: it allows to identify the training set (consisting of 50% of the pixels relative to the rockfall niches) for the network training and the testing set (considering the remaining 50% of the pixels relative to the rockfall niches) to assess the network accuracy by overlaying the rockfall niches belonging to the testing set with the obtained susceptibility map.