An Open-Source Algorithm for 3D ROck Slope Kinematic Analysis (ROKA)

Menegoni, Niccolò; Giordan, Daniele; Perotti, Cesare

doi:10.3390/app11041698

Cited by 14 publications

(4 citation statements)

References 43 publications

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“…However, the description and interpretation of the result from an individual joint set are not included in the context of this study. The susceptibility to failure is represented in the range of 0 to 100, categorized into five classes: very low (0-20), low (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40), moderate (41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59)(60), high (61)(62)(63)(64)(65)(66)(67)(68)(69)…”

Section: Resultsmentioning

confidence: 99%

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A GIS-Based Kinematic Analysis for Jointed Rock Slope Stability: An Application to Himalayan Slopes

Kundu

Sarkar

Ghaderpour

et al. 2023

Land

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GIS-based kinematic stability analysis in rock slopes is a rare practice in geological engineering despite its immense potential to delineate unstable zones in a mountainous region. In this article, we have used a GIS-based modified technique to assess the efficiency of kinematic analysis in predicting shallow landslides in the rock slopes of the Himalayan mountains on a regional scale. The limited use of this technique is primarily due to the complexities involved in its practical application. To make this technique more effective and convenient usability, we present modified methods and a new application, ‘GISMR’, that works with the aid of GIS software for the determination of kinematic susceptibility. A modified kinematic analysis method was implemented to define the stability in terms of failure susceptibility on a scale of 0 to 100 rather than a conservative result, such as failure or non-failure. We also present another functionality of the GISMR that provides optimised slope angles over a region. This functionality could aid the decision-making process when selecting a suitable location for a road path or other engineering constructions that are impacted by unstable mountain slopes. The applicability of this new method was demonstrated in a rock failure-prone region in the mountains of the Indian Himalayas. The outcomes delineate the unstable slopes in the region, which are intersected by a strategic National Highway 05 and have a long history of landslide-related hazards. It was found that 9.61% of the area is susceptible to failure. However, 2.28% is classified as a low susceptible region, and 2.58% of the area is very-low susceptible. The regions with moderately high, high, and very-high susceptibility cover 2.78%, 1.49%, and 0.46% of the whole area, respectively. The results were evaluated by receiver operating characteristic curve and a frequency ratio method to represent the association between kinematic susceptibility and the mass movement inventory in the area. It is concluded that kinematic susceptibility has a strong relationship with landslide activity in the rock slopes of the Himalayan region.

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Section: Resultsmentioning

confidence: 99%

“…There are instances of assessing the rock slope susceptibility utilising laser scanning or UAV point clouds [55][56][57]. A few algorithms have recently been developed to perform three-dimensional kinematic analysis on point clouds [58,59].…”

Section: State-of-the-artmentioning

confidence: 99%

A GIS-Based Kinematic Analysis for Jointed Rock Slope Stability: An Application to Himalayan Slopes

Kundu

Sarkar

Ghaderpour

et al. 2023

Land

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“…The results of the ROKA algorithm show the critical To identify potential modes of failures of the investigated slope, a kinematic analysis of large areas was performed through the open-source algorithm rock slope kinematic analysis (ROKA). The advantage of this method is that the effect of slope faces in different orientations can be considered and failure modes can be directly visualized on a 3D point cloud [50]. In particular, the size and spatial distribution of each extracted set of discontinuities must be provided to the algorithm as input data before execution.…”

Section: Kinematic Analysismentioning

confidence: 99%

3D Rock Structure Digital Characterization Using Airborne LiDAR and Unmanned Aerial Vehicle Techniques for Stability Analysis of a Blocky Rock Mass Slope

Liu

et al. 2022

Remote Sensing

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Airborne light detection and ranging (LiDAR) and unmanned aerial vehicle-structure from motion (UAV-SfM) provide point clouds with unprecedented resolution and accuracy that are well suited for the digital characterization of rock outcrops where direct contact measurements cannot be obtained due to terrain or safety constraints. Today, however, how to better apply these techniques to the practice of geostructural analysis is a topic of research that must be further explored. This study presents a processing procedure for extracting three-dimensional (3D) rock structure parameters directly from point clouds using open-source software and a three-dimensional distinct element code-assisted (3DEC) simulation of slope failure based on carbonate rock cliffs in the Jiuzhaigou Scenic Area. The procedure involves (1) processing point clouds obtained with different remote sensing techniques; (2) using the Hough transform to estimate normals for the hue, saturation, and value (HSV) rendering of unstructured point clouds; (3) automatically clustering and extracting the set-based point clouds; (4) estimating set-based geometric parameters; and (5) performing a subsequent stability analysis based on rock structure parameters. The results show that integrating different remote sensing techniques and rock structure computing can provide a quick way for slope engineers to assess the safety of blocky rock masses.

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“…The method allows to locate potential source areas, also estimating the potential for large volume failures. Eventually, Menegoni et al (2021) introduced an algorithm to identify possible critical combinations between rock discontinuities and local orientation of the slope, to infer the possibility of failure even on large and complex areas.…”

Section: Physically Based Rockfall Modelingmentioning

confidence: 99%

Rockfall susceptibility and network-ranked susceptibility along the Italian railway

Alvioli,

Santangelo,

Fiorucci

et al. 2021

Preprint

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Rockfalls pose a substantial threat to ground transportation, due to their rapidity, destructive potential and high probability of occurrence on steep topographies, often found along roads and railway routes. Various factors can trigger rockfalls, including intense rainfall and seismic activity, and diverse phenomena affect their probability of occurrence. Approaches for the assessment of rockfall susceptibility range from purely phenomenological methods and statistical methods, suitable for modeling large areas, to purely deterministic ones, usually easier to use in local analyses. A common requirement is the need to locate potential detachment points, often found uphill on cliffs, and the subsequent assessment of the runout areas of rockfalls stemming from such points.Here, we apply a physically based model for the calculation of rockfall trajectories along the whole Italian railway network, within a corridor of total length of about 17,000 km and varying width. We propose a data-driven method for the location of rockfall source points based on expert mapping of potential source areas on sample representative locations. Using empirical distributions of gridded slope values in source areas mapped by experts, we derived probabilistic maps of rockfall sources in the proximity of the railway network, regardless of a particular trigger.Source areas act as starting points of simulated trajectories, within the three-dimensional model STONE. The program provides a pixel-by-pixel trajectory count, which we classify into a susceptibility map. We obtained the map analyzing the railway track as a collection of segments, for which we provide segment-wise rockfall susceptibility.Eventually, we considered an equivalent graph representation of the network, which helps classifying the segments both on the basis of rockfall susceptibility and the role of each segment in the network, resulting in a network-ranked susceptibility.

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An Open-Source Algorithm for 3D ROck Slope Kinematic Analysis (ROKA)

Cited by 14 publications

References 43 publications

A GIS-Based Kinematic Analysis for Jointed Rock Slope Stability: An Application to Himalayan Slopes

A GIS-Based Kinematic Analysis for Jointed Rock Slope Stability: An Application to Himalayan Slopes

3D Rock Structure Digital Characterization Using Airborne LiDAR and Unmanned Aerial Vehicle Techniques for Stability Analysis of a Blocky Rock Mass Slope

Rockfall susceptibility and network-ranked susceptibility along the Italian railway

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