Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data

Article


Singh, Sarvesh Kumar, Banerjee, Bikram Pratap, Lato, Matthew J., Sammut, Claude and Raval, Simit. 2022. "Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data." International Journal of Rock Mechanics and Mining Sciences. 152, pp. 1-17. https://doi.org/10.1016/j.ijrmms.2022.105072
Article Title

Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data

ERA Journal ID4029
Article CategoryArticle
AuthorsSingh, Sarvesh Kumar, Banerjee, Bikram Pratap, Lato, Matthew J., Sammut, Claude and Raval, Simit
Journal TitleInternational Journal of Rock Mechanics and Mining Sciences
Journal Citation152, pp. 1-17
Article Number105072
Number of Pages17
Year2022
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN0020-7624
0148-9062
1365-1609
1873-4545
Digital Object Identifier (DOI)https://doi.org/10.1016/j.ijrmms.2022.105072
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S1365160922000405
AbstractLaser scanning is an efficient approach for collecting rock mass point cloud scans to characterise structural discontinuities. However, developing computationally efficient and robust analytical workflows remains an open research problem. Existing semi-automated and automated approaches rely on point normals which are prone to mapping error when high variability exists in the local-support region. This study proposes a new automated algorithm that uses the spatial distribution of points on discontinuities to capture unique signatures in the form of sinusoidal waves. The discontinuities are then effectively characterised by clustering the amplitude and phase profiles of the sinusoidal waves. The presented amplitude and phase decomposition (APD) approach requires minimal pre-processing. Moreover, it can be applied directly to raw point clouds as filtering is inherently included through the fast Fourier transform (FFT) based decomposition of the signals. The method was evaluated on an underground tunnel dataset with exposed structural discontinuity planes. The efficacy of the developed approach was tested against manual segmentation using virtual compass plugin in open-source software (Cloud Compare), semi-automated open-source (discontinuity set extractor) and proprietary (Maptek PointStudio) software, and other automated algorithmic approaches based on point normal clustering and region growing. The APD approach produced the least error in estimating mean discontinuity dip angle and dip direction which was ±1.15° and ±1.39° with a dispersion error of ±2.24° and ±1.54°, respectively.
KeywordsDigital outcrop; Discontinuity characterisation; LiDAR; Stereonet; Rock mass characterisation
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020401306. Surveying (incl. hydrographic surveying)
401905. Mining engineering
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsUniversity of New South Wales
Agriculture Victoria
BGC Engineering Inc
Permalink -

https://research.usq.edu.au/item/z3081/automated-rock-mass-discontinuity-set-characterisation-using-amplitude-and-phase-decomposition-of-point-cloud-data

  • 13
    total views
  • 0
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Geotechnical characterisation of coal spoil piles using high-resolution optical and multispectral data: A machine learning approach
Thiruchittampalam, Sureka, Banerjee, Bikram Pratap, Glenn, Nancy F. and Raval, Simit. 2024. "Geotechnical characterisation of coal spoil piles using high-resolution optical and multispectral data: A machine learning approach." Engineering Geology. 329. https://doi.org/10.1016/j.enggeo.2024.107406
Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach
Bandopadhyay, Subhajit, Barnali, Das, Sánchez, Alexander Cotrina, Banerjee, Sankar Prasad, Banerjee, Bikram P. and Ghosh, Subhasis. 2023. "Canopy Scale High-Resolution Forest Biophysical Parameter (LAI, fAPAR, and fCover) Retrieval Through Machine Learning and Cloud Computation Approach." 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS). Hyderabad, India 27 - 29 Jan 2023 Hyderabad, India. https://doi.org/10.1109/MIGARS57353.2023.10064558
An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse
Sharma, Neelesh, Banerjee, Bikram Pratap, Hayden, Matthew and Kant, Surya. 2023. "An Open-Source Package for Thermal and Multispectral Image Analysis for Plants in Glasshouse." Plants. 12 (2). https://doi.org/10.3390/plants12020317
Evaluation of Segmentation Methods for Spoil Pile Delineation Using UAV Images
Thiruchittampalam, S., Banerjee, B. P., Singh, S. K., Glenn, N. F. and Raval, S.. 2023. "Evaluation of Segmentation Methods for Spoil Pile Delineation Using UAV Images." IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium. United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IGARSS52108.2023.10283351
Spoil characterisation using UAV‑based optical remote sensing in coal mine dumps
Thiruchittampalam, Sureka, Singh, Sarvesh Kumar, Banerjee, Bikram Pratap, Glenn, Nancy F. and Raval, Simit. 2023. "Spoil characterisation using UAV‑based optical remote sensing in coal mine dumps." International Journal of Coal Science and Technology. 10 (1). https://doi.org/10.1007/s40789-023-00622-4
Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping
Thoday-Kennedy, Emily, Banerjee, Bikram, Panozzo, Joe, Maharjan, Pankaj, Hudson, David, Spangenberg, German, Hayden, Matthew and Kant, Surya. 2023. "Dissecting Physiological and Agronomic Diversity in Safflower Populations Using Proximal Phenotyping." Agriculture. 13 (3). https://doi.org/10.3390/agriculture13030620
Mapping Sensitive Vegetation Communities in Mining Eco-space using UAV-LiDAR
Banerjee, Bikram Pratap and Raval, Simit. 2022. "Mapping Sensitive Vegetation Communities in Mining Eco-space using UAV-LiDAR." International Journal of Coal Science and Technology. 9 (1), pp. 1-16. https://doi.org/10.1007/s40789-022-00509-w
Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping
Koh, Joshua C. O., Banerjee, Bikram P., Spangenberg, German and Kant, Surya. 2022. "Automated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping." New Phytologist. 233 (6), pp. 2659-2670. https://doi.org/10.1111/nph.17947
Roots’ Drought Adaptive Traits in Crop Improvement
Shoaib, Mirza, Banerjee, Bikram P., Hayden, Matthew and Kant, Surya. 2022. "Roots’ Drought Adaptive Traits in Crop Improvement." Plants. 11 (17). https://doi.org/10.3390/plants11172256
Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing
Tefera, Abeya Temesgen, Banerjee, Bikram Pratap, Pandey, Babu Ram, James, Laura, Puri, Ramesh Raj, Cooray, Onella, Marsh, Jasmine, Richards, Mark, Kant, Surya, Fitzgerald, Glenn J. and Cooray, Onella. 2022. "Estimating early season growth and biomass of field pea for selection of divergent ideotypes using proximal sensing." Field Crops Research. 277. https://doi.org/10.1016/j.fcr.2021.108407
A Particle Swarm Optimization Based Approach to Pre-tune Programmable Hyperspectral Sensors
Banerjee, Bikram Pratap and Raval, Simit. 2021. "A Particle Swarm Optimization Based Approach to Pre-tune Programmable Hyperspectral Sensors." Remote Sensing. 13 (16). https://doi.org/10.3390/rs13163295
Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery
Banerjee, Bikram P., Sharma, Vikas, Spangenberg, German and Kant, Surya. 2021. "Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery." Remote Sensing. 13 (15). https://doi.org/10.3390/rs13152918
CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements
Banerjee, Bikram Pratap, Spangenberg, German and Kant, Surya. 2021. "CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements." Biosensors. 12 (1), pp. 1-19. https://doi.org/10.3390/bios12010016
Three-Dimensional Unique-Identifier-Based Automated Georeferencing and Coregistration of Point Clouds in Underground Mines
Singh, Sarvesh Kumar, Banerjee, Bikram Pratap and Raval, Simit. 2021. "Three-Dimensional Unique-Identifier-Based Automated Georeferencing and Coregistration of Point Clouds in Underground Mines." Remote Sensing. 13 (16). https://doi.org/10.3390/rs13163145
Automated structural discontinuity mapping in a rock face occluded by vegetation using mobile laser scanning
Singh, Sarvesh Kumar, Raval, Simit and Banerjee, Bikram Pratap. 2021. "Automated structural discontinuity mapping in a rock face occluded by vegetation using mobile laser scanning." Engineering Geology. 285. https://doi.org/10.1016/j.enggeo.2021.106040
High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response
Banerjee, Bikram P., Joshi, Sameer, Thoday-Kennedy, Emily, Pasam, Raj K., Tibbits, Josquin, Hayden, Matthew, Spangenberg, German and Kant, Surya. 2020. "High-throughput phenotyping using digital and hyperspectral imaging-derived biomarkers for genotypic nitrogen response." Journal of Experimental Botany. 71 (15), pp. 4604-4615. https://doi.org/10.1093/jxb/eraa143
UAV-hyperspectral imaging of spectrally complex environments
Banerjee, Bikram Pratap, Raval, Simit and Cullen, P. J.. 2020. "UAV-hyperspectral imaging of spectrally complex environments." International Journal of Remote Sensing. 41 (11), pp. 4136-4159. https://doi.org/10.1080/01431161.2020.1714771
Fusion of Spectral and Structural Information from Aerial Images for Improved Biomass Estimation
Banerjee, Bikram Pratap, Spangenberg, German and Kant, Surya. 2020. "Fusion of Spectral and Structural Information from Aerial Images for Improved Biomass Estimation." Remote Sensing. 12 (19). https://doi.org/10.3390/rs12193164
Roof bolt identification in underground coal mines from 3D point cloud data using local point descriptors and artificial neural network
Singh, Sarvesh Kumar, Raval, Simit and Banerjee, Bikram. 2020. "Roof bolt identification in underground coal mines from 3D point cloud data using local point descriptors and artificial neural network." International Journal of Remote Sensing. 42 (1), pp. 367-377. https://doi.org/10.1080/2150704x.2020.1809734
Evaluation of a UAV-LiDAR system for mapping geological structures in an open pit highwall
Raval, S, Banerjee, B P, Shen, X, Masoumi, H and Tannant, D. 2018. "Evaluation of a UAV-LiDAR system for mapping geological structures in an open pit highwall." The 4th Australasian Ground Control in Mining Conference (AusRock). Sydney, Australia 28 - 30 Nov 2018 https://www.ausimm.com/publications/conference-proceedings/the-fourth-australasian-ground-control-in-mining-conference-ausrock/evaluation-of-a-uav-lidar-system-for-mapping-geological-structures-in-an-open-pit-highwall/.
High-resolution mapping of upland swamp vegetation using an unmanned aerial vehicle-hyperspectral system
Banerjee, Bikram Pratap, Raval, Simit and Cullen, Patrick Joseph. 2017. "High-resolution mapping of upland swamp vegetation using an unmanned aerial vehicle-hyperspectral system." Journal of Spectral Imaging. 6 (1). https://doi.org/10.1255/jsi.2017.a6
Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data
Banerjee, Bikram Pratap, Raval, Simit, Zhai, Hao and Cullen, Patrick Joseph. 2017. "Health condition assessment for vegetation exposed to heavy metal pollution through airborne hyperspectral data." Environmental Monitoring and Assessment. 189 (12). https://doi.org/10.1007/s10661-017-6333-4
Evaluation of rainfall and wetland water area variability at Thirlmere Lakes using Landsat time-series data
Banerjee, B. P., Raval, S. and Timms, W.. 2016. "Evaluation of rainfall and wetland water area variability at Thirlmere Lakes using Landsat time-series data." International Journal of Environmental Science and Technology. 13, p. 1781–1792. https://doi.org/10.1007/s13762-016-1018-z