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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Advances in Unstable Slope Instrumentation and Monitoring. Washington, DC: The National Academies Press. doi: 10.17226/25897.
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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Advances in Unstable Slope Instrumentation and Monitoring. Washington, DC: The National Academies Press. doi: 10.17226/25897.
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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Advances in Unstable Slope Instrumentation and Monitoring. Washington, DC: The National Academies Press. doi: 10.17226/25897.
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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Advances in Unstable Slope Instrumentation and Monitoring. Washington, DC: The National Academies Press. doi: 10.17226/25897.
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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Advances in Unstable Slope Instrumentation and Monitoring. Washington, DC: The National Academies Press. doi: 10.17226/25897.
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35 References Abdulwahid, W. M., & Pradhan, B. (2017). Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR). Landslides, 14(3), 1057–1076. Abellan A., Oppikofer T., Jaboyedoff M., Rosser N., Lim M., Lato M. (2013). Terrestrial Laser Scanning of rock slope instabilities. Earth Surface Processes and Landforms; doi: 10.1002/esp.3493 Anderson, S. (2013). Remote Sensing Applications for Landslides, Slopes and Embankments. Geotechnical Special Publication. 2204–2223. Barendse, M. B. “Field evaluation of a MEMS-based, real-time deformation monitoring system.” Geotechnical Instrumentation News (March 2008) pp. 41–44. Barla, M., & Antolini, F. (2016). An integrated methodology for landslides’ early warning systems. Landslides, 13(2), 215–228. Bonì, R., Bordoni, M., Colombo, A., Lanteri, L., & Meisina, C. (2018). Landslide state of activity maps by combining multi-temporal A-DInSAR (LAMBDA). Remote Sensing of Environment, 217, 172–190. Bonneau, D.A. and Hutchinson, D.J. (2017). Applications of Remote Sensing for Characterizing Debris Channel Processes. Landslides: Putting Experience, Knowledge and Emerging Technologies into Practice. Proceedings of the 3rd North American Symposium on Landslides (Roanoke, USA, 4–8 June 2017). Pages 748–759. Bordoni, M., Bonì, R., Colombo, A., Lanteri, L., & Meisina, C. (2018). A methodology for ground motion area detection (GMA-D) using A-DInSAR time series in landslide investigations. Catena, 163, 89–110. Bouali, E. H., Oommen, T., & Escobar-Wolf, R. (2019). Evidence of Instability in Previously-Mapped Landslides as Measured Using GPS, Optical, and SAR Data between 2007 and 2017: A Case Study in the Portuguese Bend Landslide Complex, California. Remote Sensing, 11(8), 937. Bründl, M., H. E. Romang, N. Bischof, and C. M. Rheinberger (2009). “The Risk Concept and its Application in Natural Hazard Risk Management in Switzerland.” Natural Hazards and Earth System Sciences, Vol. 9, No. 801. European Geosciences Union: Copernicus Publications, Göttingen, Germany, pp. 801–13. Cannon, R., Snider, F., Gagnon, J. H., Pate, K., and Ball, A. (2017). Use of LiDAR, Laser Scanning, Geologic Modeling for Landslide and Rockfall Assessments at Boundary Dam, Metaline, Washington, p. 985–994. In Landslides: putting experience, knowledge and emerging technologies into practice, Proceedings of the 3rd North American Symposium on Landslides. Cardenal, J., Mata, E., Perez-Garcia, J. L., Delgado, J., Andez, M., Gonzalez, A., & Diaz-de-Teran, J. R. (2008). Close range digital photogrammetry techniques applied to landslide monitoring. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(Part B8). Casagli, N., Frodella, W., Morelli, S., Tofani, V., Ciampalini, A., Intrieri, E., & Lu, P. (2017). Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning. Geoenvironmental Disasters, 4(1), 9. Coe, J. A., Ellis, W. L., Godt, J. W., Savage, W. Z., Savage, J. E., Michael, J. A., & Debray, S. (2003). Seasonal movement of the Slumgullion landslide determined from Global Positioning System surveys and field instrumentation, July 1998–March 2002. Engineering Geology, 68(1–2), 67–101. Colesanti, C., & Wasowski, J. (2006). Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry. Engineering Geology, 88(3–4), 173–199. Contreras, I. A., Grosser, A. T., and Ver Strate, R. H. (2008). The use of the fully-grouted method for piezometer installation. Geotechnical News, 26(2), pgs. 30–37. Corominas, J., Moya, J., Lloret, A., Gili, J. A., Angeli, M. G., Pasuto, A., & Silvano, S. (2000). Measurement of landslide displacements using a wire extensometer. Engineering Geology, 55(3), 149–166. Christiansen, C., Gauthier, D., & Oester N. (2016). 3D Monitoring of Rockfall Sources in Colorado. In Proceedings of the 67th Highway Geology Symposium, Colorado Springs, Colorado, 11–14 July 2016, pp. 431–445.

36 Advances in Unstable Slope Instrumentation and Monitoring Darrow, M.M., and Jensen, D.D. (2012). Evaluation of MEMS-based In-place Inclinometers in Cold Regions, Alaska University Transportation Center and Alaska Department of Transportation, FHWA-RD-AK-12-28. Dasenbrock, D. (2010). Automated Landslide and Instrumentation Programs on US Route 2, Proceedings of the University of Minnesota 58th Annual Geotechnical Engineering Conference, St. Paul, 26 February 2010, pp. 165–185. Delacourt, C. Allemand, P.; Berthier, E.; Raucoules, D.; Casson, B.; Grandjean, P.; and Varel, E. (2007). Remote- sensing techniques for analysing landslide kinematics: a review. Bulletin de la Société Géologique de France, 178(2), 89–100. Derron, M. H.; Jaboyedoff, M.; Pedrazzini, A.; Michoud, C.; and Villemin, T. (2013). Remote Sensing and Monitoring Techniques for the Characterization of Rock Mass Deformation and Change Detection. Rockfall Engineering, 39–65. 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Farina, P., Casagli, N., & Ferretti, A. (2007, June). Radar-interpretation of InSAR measurements for landslide investigations in civil protection practices. In First North American Landslide Conference (pp. 272–283). Ferretti, A., Monti-Guarnieri, A., Prati, C., Rocca, F., & Massonet, D. (2007). InSAR principles-guidelines for SAR interferometry processing and interpretation (Vol. 19). Francioni, M.; Simone, M.; Stead, D.; Sciarra, N.; Mataloni, G.; Calamita, F. (2019). A New Fast and Low-Cost Photogrammetry Method for the Engineering Characterization of Rock Slopes. Remote Sens. 11, 1267. Francioni, M.; Salvini, R.; Stead, D.; Coggan, J. J. (2018). Improvements in the integration of remote sensing and rock slope modelling. Nat. Hazards, 90, 975–1004. Gauthier, D., Hutchinson, J., Lato, M., Edwards, T., Bunce, D., and Wood, D. F. (2015). On the precision, accuracy, and utility of oblique aerial photogrammetry (OAP) for rock slope monitoring and assessment. 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Geotechnical instrumentation and monitoring technologies have been used to inform safety, operational, and treatment decisions for unstable slopes.

The TRB National Cooperative Highway Research Program's NCHRP Synthesis 554: Advances in Unstable Slope Instrumentation and Monitoring documents and synthesizes the state of practice for implementation and use of advancements in unstable slope instrumentation and monitoring by state departments of transportation over approximately the last decade.

The types of instrumentation and monitoring technologies range from devices installed on or in slopes to remote-sensing methods from ground, aerial, or satellite-based systems.

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