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UAVs for monitoring, investigation, and mitigation design of a rock slope with multiple failure mechanisms—a case study

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Abstract

Slope instabilities adjacent to transportation corridors require timely and precise assessment to determine the risk to road users, particularly when weather changes trigger these instabilities. In southern Alberta, Canada, near the town of Drumheller, a 500-m-long, 60-m-high slope adjacent to Highway 837 has a history of slope instabilities that includes rockfalls, frozen soil falls, and debris flows. The slope failures have blocked the road which increases user and maintenance costs. Due to unsafe conditions and the steepness of the slope (1H:1V inclination), it was only possible to undertake visual assessments of the slope conditions from the road. Advances in unmanned aerial vehicle (UAV) technology have resulted in a quick and safe tool for collecting detailed photographic records of the slope conditions. The combination of UAV data and photogrammetry methods allows engineers to remotely, safely, and quickly perform a precise assessment of the slope instabilities. The paper demonstrates the use of UAV-derived data to evaluate the following: critical instability areas in practice; the magnitude of instability events; the relationship between the drainage network and slope instabilities, and models for rockfall trajectory analyses. The paper also provides a methodology that can be implemented on other slope instabilities to support the decision-making process to define mitigation actions that are practical and minimize associated risks.

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Abbreviations

AT:

Alberta Transportation

C2C:

Closest point method

GCPs:

Ground control points

GSD:

Ground sampling distance

GSI:

Ground Strength Index

INSAR:

Interferometric Synthetic Aperture Radar

M3C2:

Multi-scale model-to-model cloud comparison

RMSE:

Root mean square error

RTK GPS:

Real-time kinematic global navigation satellite systems

SFM:

Structure from motion

SOR:

Statistical Outlier Removal

UAV:

Unmanned aerial vehicle

References

  • Agüera-Vega F, Carvajal-Ramírez F, Martínez-Carricondo P, Sánchez-Hermosilla López J, Mesas-Carrascosa FJ, García-Ferrer A, Pérez-Porras FJ (2018) Reconstruction of extreme topography from UAV structure from motion photogrammetry. Meas J Int Meas Confed 121:127–138. https://doi.org/10.1016/j.measurement.2018.02.062

    Article  Google Scholar 

  • Alberta Transportation (2017) Traffic counts Reference No 106230 2016. http://www.transportation.alberta.ca/map**/. Accessed 17 Oct 2018

  • Allan JA (1921) Geology of Drumheller Coal Field, Alberta. J.W. Jeffery, Kings’s Printer, Edmonton, Canada

  • Allasia P, Baldo M, Giordan D et al (2019) Near real time monitoring systems and periodic surveys using a multi sensors UAV: the case of Ponzano landslide. IAEG/AEG Annu Meet Proceedings, San Fr California, 2018 - Vol 1 1:303–310. https://doi.org/10.1007/978-3-319-93124-1_37

  • Al-Rawabdeh A, Moussa A, Foroutan M et al (2017) Time series UAV image-based point clouds for landslide progression evaluation applications. Sensors (Switzerland):17. https://doi.org/10.3390/s17102378

  • Beregovoi DV, Younes JA, Mustafin MG (2017) Monitoring of quarry slope deformations with the use of satellite positioning technology and unmanned aerial vehicles. Procedia Eng 189:737–743. https://doi.org/10.1016/j.proeng.2017.05.116

    Article  Google Scholar 

  • Borneuf D (1972) Hydrogeology of the Drumheller area, Alberta, report 72–1. Edmonton, Canada

  • Carlà T, Farina P, Intrieri E, Botsialas K, Casagli N (2017a) On the monitoring and early-warning of brittle slope failures in hard rock masses: examples from an open-pit mine. Eng Geol 228:71–81. https://doi.org/10.1016/j.enggeo.2017.08.007

    Article  Google Scholar 

  • Carlà T, Macciotta R, Hendry M, Martin D, Edwards T, Evans T, Farina P, Intrieri E, Casagli N (2017b) Displacement of a landslide retaining wall and application of an enhanced failure forecasting approach. Landslides 15:489–505. https://doi.org/10.1007/s10346-017-0887-7

    Article  Google Scholar 

  • CloudCompare [GNU GPL software] (2.9) (2011) Retrieved from http://www.cloudcompare.org/

  • Cruden D, VanDine DF (2013) Classification, description, causes and indirect effects - Canadian technical guidelines and best practices related to landslides: a national initiative for Loss reduction. In Landslides: Global Risk Preparedness. https://doi.org/10.4095/292505

  • Cucchiaro S, Cavalli M, Vericat D, Crema S, Llena M, Beinat A, Marchi L, Cazorzi F (2018) Monitoring topographic changes through 4D-structure-from-motion photogrammetry: application to a debris-flow channel. Environ Earth Sci 77:1–21. https://doi.org/10.1007/s12665-018-7817-4

    Article  Google Scholar 

  • DroneDeploy Inc. f.k.a. Infatics Inc. (2020) Drone Deploy. San Francisco, U.S.

  • Environmental Systems Research Institute Inc. (2016) ArcGIS Desktop [Software], California, U.S.

  • Esposito G, Salvini R, Matano F, Sacchi M, Danzi M, Somma R, Troise C (2017) Multitemporal monitoring of a coastal landslide through SfM-derived point cloud comparison. Photogramm Rec 32:459–479. https://doi.org/10.1111/phor.12218

    Article  Google Scholar 

  • Fan X, Xu Q, Scaringi G, Dai L, Li W, Dong X, Zhu X, Pei X, Dai K, Havenith HB (2017) Failure mechanism and kinematics of the deadly June 24th 2017 **nmo landslide, Maoxian, Sichuan, China. Landslides 14:2129–2146. https://doi.org/10.1007/s10346-017-0907-7

    Article  Google Scholar 

  • Fey C, Wichmann V (2017) Long-range terrestrial laser scanning for geomorphological change detection in alpine terrain – handling uncertainties. Earth Surf Process Landf 42:789–802. https://doi.org/10.1002/esp.4022

    Article  Google Scholar 

  • Furukawa Y, Ponce J (2009) Accurate camera calibration from Multi-View Stereo and Bundle Adjustment - Furukawa, Team - Unknown.pdf. Int J Comput Vis 84:257–268

    Article  Google Scholar 

  • Giani GP (1992) Rock slope stability analysis. A.A. Balkema, Rotterdam

  • Girardeau-Montaut D, Roux M, Marc R, Thibault G (2005) Change detection on points cloud data acquired with a ground laser scanner. In: Vosselman G, Brenner C (eds) International Society for Photogrammetry and Remote Sensing (ISPRS) Workshop Laser scanning 2005. Enschede, Netherlands

  • Government of Canada (2018) Historical weather data from Drumheller. http://climate.weather.gc.ca/. Accessed 20 Aug 2018

  • Hendry M, Macciotta R, Martin CD, Reich B (2015) Effect of Thompson River elevation on velocity and instability of Ripley Slide. Can Geotech J 52:257–267. https://doi.org/10.1139/cgj-2013-0364

    Article  Google Scholar 

  • Hoek E (2018) Unpublished notes. In: Rocscience. https://www.rocscience.com/help/rocfall/baggage/rn_rt_table.htm. Accessed 27 May 2018

  • Huang H, Song K, Yi W, Long J, Liu Q, Zhang G (2018) Use of multi-source remote sensing images to describe the sudden Shanshucao landslide in the Three Gorges Reservoir, China. Bull Eng Geol Environ 78:1–20. https://doi.org/10.1007/s10064-018-1261-2

    Article  Google Scholar 

  • Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing 54(11):1593–1600

  • Klohn Crippen Berger (2000) Central Region Landslide Assessment SH837:02 River Scour @ km 1.9 Emergency Geotechnical Inspection Report, July 25, 2000

  • Klohn Crippen Berger (2018a) CON0017608 Central Region GRMP – Call-Out Report C018 Hwy 837:02 Call-Out Report Revision 1 July 13, 2018. Red Deer

  • Klohn Crippen Berger (2018b) CON0017608 Central Region GRMP – Call-Out Report C018 Hwy 837:02 Call-Out Report January 19, 2018. Red Deer

  • Kromer RA, Abellán A, Hutchinson DJ, Lato M, Edwards T, Jaboyedoff M (2015) A 4D filtering and calibration technique for small-scale point cloud change detection with a terrestrial laser scanner. Remote Sens 7:13029–13058. https://doi.org/10.3390/rs71013029

    Article  Google Scholar 

  • Kromer R, Lato M, Hutchinson DJ, Gauthier D, Edwards T (2017) Managing rockfall risk through baseline monitoring of precursors using a terrestrial laser scanner. Can Geotech J 54:953–967. https://doi.org/10.1139/cgj-2016-0178

    Article  Google Scholar 

  • Küng O, Strecha C, Beyeler A et al (2012a) The accuracy of automatic photogrammetric techniques on ultra-light UAV imagery. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-1/:125–130. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-125-2011

    Article  Google Scholar 

  • Küng O, Strecha C, Fua P et al (2012b) Simplified building models extraction from ultra-light UAV imagery. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-1/:217–222. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-217-2011

  • Lague D, Brodu N, Leroux J (2013) Accurate 3D comparison of complex topography with terrestrial laser scanner: application to the Rangitikei canyon (N-Z). ISPRS J Photogramm Remote Sens 82:10–26. https://doi.org/10.1016/j.isprsjprs.2013.04.009

    Article  Google Scholar 

  • Lan H, Derek Martin C, Lim CH (2007) RockFall analyst: a GIS extension for three-dimensional and spatially distributed rockfall hazard modeling. Comput Geosci 33:262–279. https://doi.org/10.1016/j.cageo.2006.05.013

    Article  Google Scholar 

  • Lan H, Martin CD, Zhou C, Lim CH (2010) Rockfall hazard analysis using LiDAR and spatial modeling. Geomorphology 118:213–223. https://doi.org/10.1016/j.geomorph.2010.01.002

    Article  Google Scholar 

  • Macciotta R, Martin CD (2019) Preliminary approach for prioritizing resource allocation for rock fall hazard investigations based on susceptibility map** and efficient three-dimensional trajectory modelling. Bull Eng Geol Environ 78:2803–2815. https://doi.org/10.1007/s10064-018-1279-5

    Article  Google Scholar 

  • Macciotta R, Rodriguez J, Hendry M et al (2017) The 10-mile slide north of Lillooet , British Columbia – history , characteristics and monitoring. In: 3rd North American Symposium on Landslides. Roanoke, Virginia

  • Marinos PG, Hoek E (2000) GSI: a geologically friendly tool for rock mass strength estimation. In: Proc. GeoEng2000 Conference, pp 1422–1442

  • Martínez-Carricondo P, Agüera-Vega F, Carvajal-Ramírez F, Mesas-Carrascosa FJ, García-Ferrer A, Pérez-Porras FJ (2018) Assessment of UAV-photogrammetric map** accuracy based on variation of ground control points. Int J Appl Earth Obs Geoinf 72:1–10. https://doi.org/10.1016/j.jag.2018.05.015

    Article  Google Scholar 

  • Mazzanti P, Bozzano F, Brunetti A, Caporossi P, Esposito C, Mugnozza GS (2017) Experimental landslide monitoring site of Poggio Baldi landslide (Santa Sofia, N-Apennine, Italy). In: Advancing culture of living with landslides (Vol 5, pp 259–266). Springer International Publishing, Ljubljana, Slovenia. https://doi.org/10.1007/978-3-319-53487-9_29

  • Petschko H, Bell R, Glade T (2016) Effectiveness of visually analyzing LiDAR DTM derivatives for earth and debris slide inventory map** for statistical susceptibility modeling. Landslides 13:857–872. https://doi.org/10.1007/s10346-015-0622-1

    Article  Google Scholar 

  • Pfeiffer TJ, Bowen TD (1989) Computer simulation of rockfalls. Environ Eng Geosci xxvi(1):135–146. https://doi.org/10.2113/gseegeosci.xxvi.1.135

  • Pix4D S.A. (2018a) Pix4DCapture. Lausanne, Switzerland

  • Pix4D S.A. (2018b) Pix4Dmapper Pro. Lausanne, Switzerland

  • Prior GJ, Hathway B, Glombick PM et al (2013) Bedrock geology of Alberta, AER/AGS map 600, scale 1:1,000,000. To accompany AGS Open File Report 2013–02

  • Riquelme A, Cano M, Tomás R, Abellán A (2017) Identification of rock slope discontinuity sets from laser scanner and photogrammetric point clouds: a comparative analysis. Procedia Eng 191:838–845. https://doi.org/10.1016/j.proeng.2017.05.251

    Article  Google Scholar 

  • Rocscience Inc. (2018) RocFall. Toronto, Canada

  • Rodriguez J, Hendry M (2018) Cost-effective landslide monitoring GPS system: characteristics, implementation and results. In: Geohazards7. Canmore, Alberta

  • Roque D, Perissin D, Falcão AP, Amado C, Lemos JV, Fonseca AM (2018) Analysis of InSAR displacements for the slopes around Odelouca reservoir. Procedia Comput Sci 138:338–345. https://doi.org/10.1016/j.procs.2018.10.048

    Article  Google Scholar 

  • Smethurst JA, Smith A, Uhlemann S, Wooff C, Chambers J, Hughes P, Lenart S, Saroglou H, Springman SM, Löfroth H, Hughes D (2017) Current and future role of instrumentation and monitoring in the performance of transport infrastructure slopes. Q J Eng Geol Hydrogeol 50:271–286. https://doi.org/10.1144/qjegh2016-080

    Article  Google Scholar 

  • Solazzo D, Sankey JB, Sankey TT, Munson SM (2018) Map** and measuring Aeolian sand dunes with photogrammetry and LiDAR from unmanned aerial vehicles (UAV) and multispectral satellite imagery on the Paria Plateau, AZ, USA. Geomorphology 319:174–185. https://doi.org/10.1016/j.geomorph.2018.07.023

    Article  Google Scholar 

  • Sousa JJ, Ruiz AM, Bakoň M, Lazecky M, Hlaváčová I, Patrício G, Delgado JM, Perissin D (2016) Potential of C-band SAR interferometry for dam monitoring. Procedia Comput Sci 100:1103–1114. https://doi.org/10.1016/j.procs.2016.09.258

    Article  Google Scholar 

  • Stalker AM (1973) Memoir 370 surficial geology of the Drumheller area, Alberta. Ottawa, Canada

  • Tarboton DG, Bras RL, Rodriguez-Iturbe I (1991) Tarboton_et_al-1991-Hydrological_Processes. Hydrol Process 5:81–100. https://doi.org/10.1002/hyp.3360050107

    Article  Google Scholar 

  • Vallet J, Panissod F, Strecha C, Tracol M (2011) Photogrammetric performance of an ultra light weight swinglet “UAV.”. Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-1/C22:253–258. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-253-2011

    Article  Google Scholar 

  • Vanneschi C, Eyre M, Francioni M, Coggan J (2017) The use of remote sensing techniques for monitoring and characterization of slope instability. Procedia Eng 191:150–157. https://doi.org/10.1016/j.proeng.2017.05.166

    Article  Google Scholar 

  • Vautherin J, Rutishauser S, Schneider-Zapp K, Choi HF, Chovancova V, Glass A, Strecha C (2016) Photogrammetric accuracy and modeling of rolling shutter cameras. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III–3(3):139–146. https://doi.org/10.5194/isprsannals-III-3-139-2016

  • Westoby MJJ, Brasington J, Glasser NFF et al (2012) ‘Structure-from-motion’ photogrammetry: a low-cost, effective tool for geoscience applications. Geomorphology 179:300–314. https://doi.org/10.1016/j.geomorph.2012.08.021

    Article  Google Scholar 

  • Williams JG, Rosser NJ, Hardy RJ et al (2017) Optimising 4D approaches to surface change detection: improving understanding of Rockfall magnitude-frequency. Earth Surf Dyn Discuss:1–36. https://doi.org/10.5194/esurf-2017-43

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Acknowledgments

This research was made possible by the (Canadian) Railway Ground Hazard Research Program, which is funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), Canadian Pacific Railway (CR), Canadian National Railway Company (CN); and Transport Canada.

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Rodriguez, J., Macciotta, R., Hendry, M.T. et al. UAVs for monitoring, investigation, and mitigation design of a rock slope with multiple failure mechanisms—a case study. Landslides 17, 2027–2040 (2020). https://doi.org/10.1007/s10346-020-01416-4

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