Skip to main content
Log in

Bias Correction for View-limited Lidar Scanning of Rock Outcrops for Structural Characterization

  • Original Paper
  • Published:
Rock Mechanics and Rock Engineering Aims and scope Submit manuscript

Abstract

Lidar is a remote sensing technology that uses time-of-flight and line-of-sight to calculate the accurate locations of physical objects in a known space (the known space is in relation to the scanner). The resultant point-cloud data can be used to virtually identify and measure geomechanical data such as joint set orientations, spacing and roughness. The line-of-sight property of static Lidar scanners results in occluded (hidden) zones in the point-cloud and significant quantifiable bias when analyzing the data generated from a single scanning location. While the use of multiple scanning locations and orientations, with merging of aligned (registered) scans, is recommended, practical limitations often limit setup to a single location or a consistent orientation with respect to the slope and rock structure. Such setups require correction for measurement bias. Recent advancements in Lidar scanning and processing technology have facilitated the routine use of Lidar data for geotechnical investigation. Current developments in static scanning have lead to large datasets and generated the need for automated bias correction methods. In addition to the traditional bias correction due to outcrop or scanline orientation, this paper presents a methodology for correction of measurement bias due to the orientation of a discrete discontinuity surface with respect to the line-of-sight of the Lidar scanner and for occlusion. Bias can be mathematically minimized from the analyzed discontinuity orientation data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  • Abellan A, Jaboyedoff M, Oppikofer T, Vilaplana JM (2009) Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event. Nat Hazards Earth Syst Sci 9:365–372

    Article  Google Scholar 

  • Amann MC, Bosch T, Lescure M, Myllyla R (2001) Laser ranging: a critical review of usual techniques for distance measurement. Opt Eng 40(1):10–19

    Article  Google Scholar 

  • Barton N, Lien R, Lunde J (1974) Engineering classification of rock masses for the design of rock support. Rock Mech 6:189–236

    Article  Google Scholar 

  • Beacher GB (1980) Progressively censored sampling of rock joint traces. Math Geol 12(1):33–40

    Article  Google Scholar 

  • Beacher GB (1983) Statistical analysis of rock mass fracturing. Math Geol 15(2):329–348

    Article  Google Scholar 

  • Besl PJ, McKay ND (1992) A method for registration of 3-D shapes. IEEE Trans Pattern Anal Mach Intell 14:239–256

    Article  Google Scholar 

  • Bieniawski ZT (1989) Engineering rock mass classification. Wiley-Interscience, London

    Google Scholar 

  • Bonnaffe F, Jennette D, Andrews J (2007) A method for acquiring and processing ground-based Lidar data in difficult-to-access outcrops for use in three-dimensional, virtual-reality models. Geosphere 3:501–510

    Article  Google Scholar 

  • Buckley SJ, Howell JA, Enge HD, Kurz TH (2008) Terrestrial laser scanning in geology: data acquisition, processing and accuracy considerations. J Geol Soc 165:625–638

    Article  Google Scholar 

  • Fekete S, Diederichs M, Lato M (2009) Geotechnical applications of Lidar scanning in tunnelling. RockEng. Diederichs and Grasselli, Toronto, pp 1–12

    Google Scholar 

  • Feng QH, Roshoff K (2004) In situ mapping and documentation of rock fases using a full-coverage 3-D laser scanning technique. Int J Rock Mech Min Sci 41(3):379

    Article  Google Scholar 

  • Ferrero AM, Forlani G, Roncella R, Voyat HI (2009) Advanced geostructural survey methods applied to rock mass chrazaterization. Rock Mech Rock Eng 42(i):631–665

    Article  Google Scholar 

  • Goodman RE (1980) Introduction to rock mechanics (Chapter 8). Wiley, Toronto

    Google Scholar 

  • Hammah RE, Curran JH (1999) On distance measures for the fuzzy k-means algorithm for joint data. Rock Mech Rock Eng 32(1):1–27

    Article  Google Scholar 

  • Hanberg WC (2008) Using close range terrestrial digital photogrammetry for 3-D rock slope modelling and discontinuity mapping in the United States. Bull Eng Geol Environ 67:457–469

    Article  Google Scholar 

  • InnovMetric (2008) PolyWorks V10.1. InnovMetric, Quebec

    Google Scholar 

  • Kemeny J, Post R (2003) Estimating three-dimensional rock discontinuty orientation from digital images of fracture traces. Comput Geosci 29:65–77

    Article  Google Scholar 

  • Kemeny J, Turner K (2008) Ground-based LiDAR rock slope mapping and assessment. Federal Highway Administration, p 114

  • Kemeny J, Turner K, Norton B (2006) LIDAR for rock mass characterization: hardware, software, accuracy and best-practices. In: Tonon F, Kottenstette J (eds) Laser and photogrammetric methods for rock face characterization. ARMA Golden, Colorado

    Google Scholar 

  • Lan H, Martin CD, Lim CH (2007) Rockfall analyst: a GIS extension for three-dimensional and spatially distributed rockfall hazard monitoring. Comput Geosci 33:262–279

    Article  Google Scholar 

  • Lato M, Hutchinson J, Diederichs M, Kalenchuk K (2007) Evaluating block shape and block volume distributions of rock faces using LiDAR and 3DEC. Geophys Res Abstr (European Geosciences Union) 9:1–2

    Google Scholar 

  • Lato M, Hutchinson DJ, Diederichs MS, Harrap R (2009) Optimization of LiDAR scanning and processing for automated structural evaluation of discontinuities in rockmasses. Int J Rock Mech Min Sci 46:194–199

    Article  Google Scholar 

  • Leica Geosystems HDS LLC (2008) Cyclone 602 Build 980, USA

  • Lichti DD, Jamtsho S (2006) Angular resolution of terrestrial laser scanners. The Photogrammetric Record 21(114):141–160

    Google Scholar 

  • McCaffrey KW et al (2005) Unlocking the spatial dimension: digital technologies and the future of geoscience fieldwork. J Geol Soc Lond 162:927–938

    Article  Google Scholar 

  • Mechelke K, Kersten TP, Lindstaedt M (2007) Comparative investigation into the accuracy behaviour of the new generation of terrestrial laser scanning systems. Optical 3-D Measurement Techniques VIII. Gruen and Kahmen, Zurich, pp 319–327

    Google Scholar 

  • Mekni M, Sahli N, Moulin B (2008) A geosimulation approach involving spatially-aware agents: A case study on the identification of risky areas for trains. SpringSim, Ottawa, pp 37–45

    Google Scholar 

  • Palmstrom A (1995) RMi—a rock mass characterization system for rock engineering purposes. University of Oslo, Oslo

    Google Scholar 

  • Park HJ, West TR (2002) Sampling bias of discontinuity orientation caused by linear sampling technique. Eng Geol 66:99–110

    Article  Google Scholar 

  • Park ES, Cheon DS, Synn JH, Jung YB, Choi YK (2008) Characterization of discontinuities using 3-D Laser scanner. Am Rock Mech Assoc, San Francicso, USA

    Google Scholar 

  • Peacock DCP (2006) Predicting variability in joint frequencies from boreholes. J Struct Geol 28:353–361

    Article  Google Scholar 

  • Priest SD, Hudson JA (1976) Discontinuity spacings in rock. Int J Rock Mech Min Sci 13:135–148

    Google Scholar 

  • Reid TR, Harrison JP (2000) A semi-automated methodology for discontinuity trace detection in digital images of rock mass exposures. Int J Rock Mech Min Sci 37:1073–1089

    Article  Google Scholar 

  • RocScience (2006) Dips 6.0. Structural data processing software. Toronto

  • Roncella R, Forlani G (2005) Extraction of planar patches from point clouds to retrieve dip and dip direction of rock discontinuities. ISPRS WG III/3, III/4, V/3 Workshop “Laser scanning 2005”. Enschede, Netherlands

  • Rosser N, Dunning SA, Lim M, Petley DN (2005) Terrestrial laser scanning for quantitative rockfall hazard assessment. In: Hunger O, Fell R, Couture R, Eberhardt E (eds) Landslide risk management. Balkema, Rotterdam, p 091

    Google Scholar 

  • Slob S, Hack R, van Knapen B, Turner K, Kemeny J (2005) A Method for automated discontinuity analysis of rock slopes with 3D laser scanning. Transportation Research Board, Washington DC

    Google Scholar 

  • Sturzenegger M, Stead D (2009a) Close-range terrestrial digital photogrammetry and terrestrial laser scanning for discontinuity characterization on rock cuts. Eng Geol 106:163–182

    Article  Google Scholar 

  • Sturzenegger M, Stead D (2009b) Quantifying discontinuity orientation and persistence on high mountain rock slopes and large landslides using terrestrial remote sensing techniques. Nat Hazards Earth Syst Sci 9:267–287

    Article  Google Scholar 

  • Sturzenegger M, Yan M, Stead D, Elmo D (2007) Applications and limitations of ground-based laser scanning in rock slope characterization. In: Eberhardt E, Stead D, Morrison T (eds) Proceedings of the first Canadian US rock mechanics symposium, vol 1. Taylor and Francis, London, pp 29–36

    Google Scholar 

  • Terzaghi RD (1965) Source of error in joint surveys. Geotechnique 15:287–304

    Article  Google Scholar 

  • Tonon F, Kottensette JT (2006) Laser and photogrammetric methods for rock face characterization: a workshop. In: Tonon F, Kottenstette J (eds) Laser and photogrammetric methods for rock face characterization. Golden, Colorado

    Google Scholar 

  • Trinks I et al (2005) Mapping and analysing virtual outcrops. Vis Geosci 1–7

  • Turner AK, Kemeny J, Slob S, Hack R (2006) Evaluation, and management of unstable rock slopes by 3-D laser scanning. International Association for Engineering Geology and the Environment. The Geological Society of London, pp 1–11

  • Zinber T, Schmidt J, Niemann H (2003) A refined ICP algorithm for robust 3-D correspondence estimation. IEEE Xplore 11:695–698

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank the generous funding of NSERC and the GEOIDE Network as well as the guidance and discussion of the topic during the development of the theory with Rob Harrap. A special thanks to Isabel Coderre for editing numerous drafts along the way.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mark S. Diederichs.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lato, M.J., Diederichs, M.S. & Hutchinson, D.J. Bias Correction for View-limited Lidar Scanning of Rock Outcrops for Structural Characterization. Rock Mech Rock Eng 43, 615–628 (2010). https://doi.org/10.1007/s00603-010-0086-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00603-010-0086-5

Keywords

Navigation