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Evaluating roadside rockmasses for rockfall hazards using LiDAR data: optimizing data collection and processing protocols

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Abstract

Highways and railroads situated within rugged terrain are often subjected to the hazard of rockfalls. The task of assessing roadside rockmasses for potential hazards typically involves an on-site visual investigation of the rockmass by an engineer or geologist. At that time, numerous parameters associated with discontinuity orientations and spacing, block size (volume) and shape distributions, slope geometry, and ditch profile are either measured or estimated. Measurements are typically tallied according to a formal hazard rating system, and a hazard level is determined for the site. This methodology often involves direct exposure of the evaluating engineer to the hazard and can also create a potentially non-unique record of the assessed slope based on the skill, knowledge and background of the evaluating engineer. Light Detection and Ranging (LiDAR)–based technologies have the capability to produce spatially accurate, high-resolution digital models of physical objects, known as point clouds. Mobile terrestrial LiDAR equipment can collect, at traffic speed, roadside data along highways and rail lines, scanning continual distances of hundreds of kilometres per day. Through the use of mobile terrestrial LiDAR, in conjunction with airborne and static systems for problem areas, rockfall hazard analysis workflows can be modified and optimized to produce minimally biased, repeatable results. Traditional rockfall hazard analysis inputs include two distinct, but related sets of variables related to geological or geometric control. Geologically controlled inputs to hazard rating systems include kinematic stability (joint identification/orientation) and rock block shape and size distributions. Geometrically controlled inputs include outcrop shape and size, road, ditch and outcrop profile, road curvature and vehicle line of sight. Inputs from both categories can be extracted or calculated from LiDAR data, although there are some limitations and special sampling and processing considerations related to structural character of the rockmass, as detailed in this paper.

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References

  • Abbott B, Bruce I, Keegan T, Oboni F, Savigny W (1998) A methodology for the assessment of rockfall hazard and risk along linear transportation corridors. In: 8th Congress, international association of engineering geology, a global view from the Pacific rim, Vancouver, vol 2. A. A. Balkema, Vancouver, pp 1195–1200

  • Abellán 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 

  • Abellán A, Vilaplana JM, Martínez J (2006) Application of a long-range Terrestrial Laser Scanner to a detailed rockfall study at Vall de Núria (Eastern Pyrenees, Spain). Eng Geol 88(3–4):136–148

    Article  Google Scholar 

  • Agliardi F, Crosta GB (2003) High resolution three-dimensional numerical modelling of rockfalls. Int J Rock Mech Min Sci 40:455–471

    Article  Google Scholar 

  • Alshawa M, Smigiel E, Grussenmeyer P, Landes T (2007). Integration of a terrestrial LiDAR on a mobile mapping platform: first experiences. In: 5th International symposium on mobile mapping technology, Italy, p 6

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

    Article  Google Scholar 

  • Ambercore (2007) ALMIS. Ottawa, Canada

  • Ambercore (2009) TITAN. Ottawa, Canada

  • Arattano M, Marchi L (2008) Systems and sensors for debris-flow monitoring and warning. Sensors 8:2436–2452

    Article  Google Scholar 

  • Barber D, Mills J, Smith-Voysey S (2008) Geometric validation of a ground-based mobile laser scanning system. J Photogramm Remote Sens 63:128–141

    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 

  • Bauer A, Paar G, Kaltenböck A (2005) Mass movement monitoring using terrestrial laser scanner for rock fall management. In: Geo-information for disaster management, vol 5. Springer, Berlin, pp 393–406

  • Bellian JA, Kerans C, Jennette DC (2005) Digital outcrop models: applications of terrestrial scanning LiDAR technology in stratigraphic modelling. J Sediment Res 2(75):166–176

    Article  Google Scholar 

  • Bieniawski ZT (1989) Engineering rock mass classification. Wiley, New York

    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(6):501–510

    Article  Google Scholar 

  • Bourrier F, Dorren L, Nicot F, Berger F, Darve F (2009) Toward objective rockfall trajectory simulation using a stochastic impact model. Geomorphology 110:68–79

    Article  Google Scholar 

  • Bruce Geotechnical Consultants Inc. in association with Oboni Associates Inc (1997) Canadian National Railway Rockfall Hazard and Risk Assessment System. Field Implementation Manual

  • 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 

  • Bunce CM, Cruden DM, Morgenstern NR (1997) Assessment of the hazard from rock fall on a highway. Can Geotech J 34:344–356

    Article  Google Scholar 

  • Carr SD, Easton RM, Jamieson RA, Culshaw NG (2000) Geologic transect across the Grenville Orogen of Ontario and New York. Can J Earth Sci 37:193–216

    Article  Google Scholar 

  • Chau KT, Wong RH, Wu JJ (2002) Coefficient of restitution and rotational motions of rockfall impacts. Int J Rock Mech Min Sci 39:69–77

    Article  Google Scholar 

  • Cushing HP (1908) Lower portion of the Paleozoic section in northwestern New York. Geol Soc Am Bull 19:155–176

    Google Scholar 

  • Derron MH, Jaboyedoff M, Blikra LH (2005) Preliminary assessment of rockslide and rockfall hazards using a DEM (Oppstadhornet, Norway). Nat Hazards Earth Syst Sci 5:285–292

    Article  Google Scholar 

  • Donovan J, Raza AW (2008) A change detection method for slope monitoring and identification of potential rockfall using three-dimensional imaging. American Rock Mechanics Association, San Francisco

    Google Scholar 

  • El-Rabbany A (2006) Introduction to GPS: the global positioning system, 2nd edn. Artech House Publishers, Norwood

    Google Scholar 

  • ESRI (2008) ArcGIS V9.3 (Build 1770)

  • Fekete S, Diederichs MS, Lato M (2009) Geotechnical and operational applications for dimensional laser scanning in drill and blast tunnels. Tunn Undergr Space Technol; submitted Oct 2009 (manuscript 18 pages, 28 figures)

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

    Google Scholar 

  • Feng QH, Röshoff K (2004) In Situ mapping and documentation of rock faces using a full-coverage 3D laser scanning technique. Int J Rock Mech Min Sci 41(3):1–6

    Google Scholar 

  • Franklin JA, Senior SA (1997) Outline of RHRON, the Ontario rockfall hazard rating system. In: Proceedings of the international symposium on engineering geology and the environment, Athens, pp 647–656

  • Glennie C (2007a) Reign of point clouds: a kinematic terrestrial LiDAR scanning system. In: InsideGNSS, pp 21–31

  • Glennie C (2007b) Rigorous 3D error analysis of kinematic scanning LiDAR systems. J Appl Geodesy 1:147–157

    Article  Google Scholar 

  • Holm K, Jakob M (2009) Long rockfall runout, Pascua, Chile. Can Geotech J 46:225–230

    Article  Google Scholar 

  • Hungr O, Fletcher L, Jakob M, MacKay C, Evans SG (2003) A system of rock fall and rock slide hazard rating for a railway. In: Geohazards, Edmonton, pp 277–283

  • Iavarone A, Vagners D (2003) Sensor fusion: generating 3D by combining airborne and tripod mounted LiDAR data. In: International archives of photogrammetry, remote sensing and spatial information sciences, vol XXXIV. ISPRS, Regensburg, pp 1–7

  • InnovMetric (2008) PolyWorks V11.0.1. Quebec City, Canada

  • Janeras M, Navarro M, Ruiz A, Kornus W, Talaya J, Barbera M et al. (2004) LiDAR applications to rock fall hazard assessment in Vall de Nuria. In: 4th ICA Mountain Cartography Workshop, Spain, pp 1–14

  • Kalenchuk K, Diederichs MS, McKinnon S (2006) Characterizing block geometry in jointed rockmasses. Int J Rock Mech Min Sci 43:1212–1225

    Article  Google Scholar 

  • Kemeny J, Turner K (2008) Ground-based LiDAR rock slope mapping and assessment. Federal Lands Highway Technology Deployment Initiatives and Partnership Program. Federal Highway Administration, Lakewood

    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 (2008) Optimization of LiDAR scanning and processing for automated structural evaluation of discontinuities in rockmasses. Int J Rock Mech Min Sci 46:194–199

    Google Scholar 

  • Lato M, Diederichs MS, Hutchinson DJ (2009a) Bias correction for static LiDAR scanning of rock outcrops for structural characterization. Rock Mech Rock Eng 23:5–7. doi:10.1007/s00603-010-0086-4

    Google Scholar 

  • Lato M, Hutchinson DJ, Diederichs MS, Ball D, Harrap R (2009b) Engineering monitoring of rockfall hazards along transportation corridors: using mobile terrestrial LiDAR. Nat Hazards Earth Syst Sci 9:935–946

    Article  Google Scholar 

  • Leica Geosystems (2007) HDS6000. Heerbrugg, Switzerland

  • Leica Geosystems HDS LLC (2008) Cyclone 6.0.2 Build 980. Heerbrugg, Switzerland

  • Lemy F, Hadjigeorgiou J (2004) A digital face mapping case study in an underground hard rock mine. Can Geotech J 41:1011–1025

    Article  Google Scholar 

  • Lemy F, Yong S, Schultz T (2006) A case study of monitoring tunnel wall displacement using laser scanning technology. In: IAEG. The Geological Society of London, Nottingham, pp 1–11

  • Maerz NH (2000). Highway rock cut stability assessment in rock massed not conducive to stability calculations. In: Proceedings of the 51st annual highway geology symposium, Seattle, pp 249–259

  • Maptek (2007) I-Site 4400. Denver, Co, USA

  • McCaffrey KW, Jones R, Holdsworth R, Wilson R, Clegg P, Imber J (2005) Unlocking the spatial dimension: digital technologies and the future of geoscience fieldwork. J Geol Soc Lond 162:927–938

    Article  Google Scholar 

  • McFall GH (1993) Structural Elements and Neotectonics of Prince Edward County, Southern Ontario. Geographie Physique et Quaternaire 47(3):303–312

    Google Scholar 

  • McFarlane RB (1992) Stratigraphy, paleoenvironmental interpretation, and sequences of the Middle Ordovician Black River Group. Queen’s University at Kingston, Kingston (Publication No. AAT MM80627)

  • McHugh EL (2004) Video motion detection for real-time hazard warnings in surface mines. In: SME annual meeting. Society for Mining, Metallurgy, and Exploration, Denver, p 10

  • McKean J, Roering J (2004) Objective landslide detection and surface morphology mapping using high-resolution airborne laser altimetry. Geomorphology 57:331–351

    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. In: Optical 3D measurement techniques, vol VIII. Gruen and Kahmen, Zurich, pp 319–327

  • 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 1-56555-319-5, 37-45

  • Moore HL (1986) Wedge rockfalls along Tennessee highways in the Appalachian region: their occurrence and correction. Bull As Eng Geol 23(4):441–460

    Google Scholar 

  • Optech (2008) Lynx Mobile Mapper. Toronto

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

    Article  Google Scholar 

  • Pedrazzini A, Jaboyedoff M (2008). Structures and failure mechanisms analysis of turtle mountain. In: Locat DPJ (ed) Geohazards, Quebec City, pp 349–356

  • Perret S, Dolf F, Kienholz H (2004) Rockfalls into forests: analysis and simulation of rockfall trajectories—considerations with respect to mountainous forests in Switzerland. Landslides 1:123–130

    Article  Google Scholar 

  • Pierson LA (1991) “Rockfall hazard rating system” final report. Federal Highway Administration, Oregon State Highway Division, Salem

    Google Scholar 

  • Priest SD (1993) Discontinuity analysis for rock engineering. Chapman and Hall, London

    Book  Google Scholar 

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

    Google Scholar 

  • Pringle J, Gardiner A, Westerman R (2004) Virtual geological outcrops—fieldwork and analysis made less exhaustive. Geol Today 20(2):67–72

    Article  Google Scholar 

  • Pritchard M, Porter M, Savigny KW, Bruce I, Oboni F, Keegan T (2005) CN rockfall hazard risk management system: Experience, enhancements, and future direction. The American Railway Engineering and Maintenance-of-Way Association, Chicago

    Google Scholar 

  • Ritchie AM (1963) Highway Research Record 17: evaluation of rockfall and its control. Highway Research Board, National Research Council. Transportation Research Board, Washington

  • RocScience (2006) Dips 5.1. Toronto

  • RocScience (2007) RocFall 4.045. Toronto, Canada

  • 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

  • Rosser N, Dunning SA, Lim M, Petley DN (2005) Terresterial laser scanning for quantitative rockfall hazard assessment. In: Hungr, Fell, Couture, Eberhardt (eds) Landslide risk management, Paper 91. Balekema, Rotterdam

  • Stover BK (1992) Highway rockfall research report. Geological Survey Special Publication, Denver

    Google Scholar 

  • Sturzenegger M, Stead D (2009a) 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, Stead D (2009b) 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, 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 

  • Trevisani S, Cavalli M, Marchi L (2009) Variogram maps from LiDAR data as fingerprints of surface morphology on scree slopes. Nat Hazards Earth Syst Sci 9:129–133

    Article  Google Scholar 

  • Trinks I, Clegg P, McCaffrey K, Jones R, Hobbs R, Holdsworth B (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 3D laser scanning. In; International association for engineering geology and the environment. The Geological Society of London, pp 1–11

  • Vanderwater CJ, Dunne WM, Mauldon M, Drumm EC, Bateman V (2005) Classifying and assessing the geologic contribution to rockfall hazard. Environ Eng Geosci XI(2):141–154

    Article  Google Scholar 

  • Vosselman G, Gorte B, Sithole G, Rabbani T (2004) Recognising structure in laser scanner point clouds. In: International archives of photogrammetry, remote sensing and spatial information sciences vol 46. ISPRS, Freiberg, pp 33–38

  • Yang Y, Farrell JA (2003) Magnetometer and differential carrier phase GPS-aided INS for advanced vehicle control. IEEE Trans Robot Autom 19(2):269–282

    Article  Google Scholar 

  • Zimmer VL, Stock GM, Sitar N (2008) Seismic monitoring of rock falls in Yosemite National Park. American Geophysical Union, San Francisco, abstract #H51F-0897

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Acknowledgments

The authors would like to extend gratitude to Kathy Kalenchuk and Dave Ball from Queen’s University. The authors would like to thank the support of Paul Mrstik, Craig Sheriff and Kresimir Kusevic from Ambercore for mobile terrestrial and helicopter LiDAR data collection and knowledgeable support. The authors would also like to thank Isabel Coderre for her countless hours of editing. As well, the authors would like to thank InnovMetric for the consultations regarding processing geological LiDAR data in PolyWorks. This research has been generously funded since 2006 by the NSERC, GEOIDE and PREA agencies with tactical support from CN and CPRail.

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Lato, M.J., Diederichs, M.S., Hutchinson, D.J. et al. Evaluating roadside rockmasses for rockfall hazards using LiDAR data: optimizing data collection and processing protocols. Nat Hazards 60, 831–864 (2012). https://doi.org/10.1007/s11069-011-9872-y

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  • DOI: https://doi.org/10.1007/s11069-011-9872-y

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