3D mapping of discontinuity traces using fusion of point cloud and image data

Zhang, Peng; Zhao, Qingqing; Tannant, Dwayne D.; Ji, Tingting; Zhu, Hehua

doi:10.1007/s10064-018-1280-z

Cited by 36 publications

(6 citation statements)

References 22 publications

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“…After the establishment of the 3D HRPC model described previously, the model was analyzed to identify the main characteristics of the rock mass structure, such as the detection and mapping of the discontinuities and discontinuity sets, orientation and dip of discontinuities, spacing of discontinuities, persistence of discontinuities, and roughness of discontinues, as well as determination of rock block volumes. Due to the increasing use of UAV photogrammetry and the SfM technique to create 3D HRPC models, various automatic and semi-automatic techniques and methods have been developed to detect and map the discontinuities and discontinuity sets [20,[22][23][24][25][26]28,31,, orientation and dip direction of discontinuities [18,20,22,23,26,28,29,31,[37][38][39][40][42][43][44][45]48,49,[54][55][56][57][59][60][61][62][63][64][65][66][67][68][69][70][71][72]…”

Section: In Situ and Remote Sensing Surveysmentioning

confidence: 99%

Geotechnical Study of Raspadalica Cliff Rockfall, Croatia

2022

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The Raspadalica Cliff is an almost vertical 100 m high limestone cliff with a railway line at its foot and is known for numerous rockfall occurrences in the past. This article presents the results of the geotechnical study of the cliff based on a traditional geological and geotechnical field survey and remote sensing analysis. Both the traditional geological and geotechnical field survey and remote sensing surveys and analyses enabled the establishment of the structural model of the Raspadalica Cliff and the determination of the discontinuity sets and discontinuity features, such as orientation, spacing, persistence, roughness, discontinuity wall strength, aperture, degree of weathering of discontinuity wall, seepage conditions, and the presence and hardness of discontinuity filling. Kinematic analyses were performed on five cliff zones with slightly different structural features, indicating a relatively low probability of typical failures in the cliff rock mass that precede the rockfall occurrences. Although rockfall phenomena from the cliff face are relatively frequent, the kinematic analyses did not indicate a high probability of their occurrence. The aim of this manuscript is to make scientists and practitioners aware that investigation of rock mass cliffs and possible rockfall failures must not be based on usual methods without critical review of the obtained results and consequences. The combined use of traditional geological and geotechnical methods and more commonly used advanced remote sensing methods leads to better modelling, while the analysis of more associated failure modes can explain the triggering of rockfall.

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Section: In Situ and Remote Sensing Surveysmentioning

confidence: 99%

Geotechnical Study of Raspadalica Cliff Rockfall, Croatia

2022

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“…A common issue of geometry-based methods for discontinuity extraction is that they fail to properly recognize discontinuity planes that are perpendicular to rock faces, which are only exposed as traces (Menegoni et al, 2019) or those with slight curvature changes (Guo et al, 2019;P. Zhang et al, 2019).…”

Section: Summary Challenges and Solutionsmentioning

confidence: 99%

A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfaces

Daghigh

Tannant

Daghigh

et al. 2022

Computers & Geosciences

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“…With the advancement of remote sensing technology, non-contact measurement methods such as photogrammetry [12] and LiDAR [13] have been introduced, facilitating rapid scanning of the rock surfaces within the study area. This generates high-precision point clouds composed of numerous three-dimensional coordinates, overcoming the limitations associated with traditional methods [14,15].…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Discontinuity Extraction Based on an Improved Naive Bayes Classifier

Lu,

Zhu,

Cao

et al. 2024

Applied Sciences

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An increasing number of methods are being used to extract rock discontinuities from 3D point cloud data of rock surfaces. In this paper, a new method for automatic extraction of rock discontinuity based on an improved Naive Bayes classifier is proposed. The method first uses principal component analysis to find the normal vectors of the points, and then generates a certain number of random point sets around the selected training points for training the classifier. The trained, improved Naive Bayes classifier is based on point normal vectors and is able to automatically remove noise points due to various reasons in conjunction with the knee point algorithm, realizing high-precision extraction of the discontinuity sets. Subsequently, the individual discontinuities are segmented using a hierarchical density-based spatial clustering method with noise application. Finally, the PCA algorithm is used to complete the orientation by plane fitting the individual discontinuities. The method was applied in two cases, Kingston and Colorado, and the reliability and advantages of the new method were verified by comparing the results with those of previous research, and the discussion and analysis determined the optimal values of the relevant parameters in the algorithm.

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3D mapping of discontinuity traces using fusion of point cloud and image data

Cited by 36 publications

References 22 publications

Geotechnical Study of Raspadalica Cliff Rockfall, Croatia

Geotechnical Study of Raspadalica Cliff Rockfall, Croatia

A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfaces

A New Approach for Discontinuity Extraction Based on an Improved Naive Bayes Classifier

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