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Terrestrial laser scanning of rock slope instabilities
Author(s) -
Abellán Antonio,
Oppikofer Thierry,
Jaboyedoff Michel,
Rosser Nicholas J.,
Lim Michael,
Lato Matthew J.
Publication year - 2014
Publication title -
earth surface processes and landforms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 127
eISSN - 1096-9837
pISSN - 0197-9337
DOI - 10.1002/esp.3493
Subject(s) - rockfall , geology , point cloud , terrain , classification of discontinuities , laser scanning , deformation monitoring , key (lock) , remote sensing , landslide , deformation (meteorology) , mining engineering , computer science , geotechnical engineering , artificial intelligence , laser , cartography , geography , mathematical analysis , oceanography , physics , mathematics , computer security , optics
This manuscript presents a review on the application of a remote sensing technique (terrestrial laser scanning, TLS) to a well‐known topic (rock slope characterization and monitoring). Although the number of publications on the use of TLS in rock slope studies has rapidly increased in the last 5–10 years, little effort has been made to review the key developments, establish a code of best practice and unify future research approaches. The acquisition of dense 3D terrain information with high accuracy, high data acquisition speed and increasingly efficient post‐processing workflows is helping to better quantify key parameters of rock slope instabilities across spatial and temporal scales ranging from cubic decimetres to millions of cubic metres and from hours to years, respectively. Key insights into the use of TLS in rock slope investigations include: (a) the capability of remotely obtaining the orientation of slope discontinuities, which constitutes a great step forward in rock mechanics; (b) the possibility to monitor rock slopes which allows not only the accurate quantification of rockfall rates across wide areas but also the spatio‐temporal modelling of rock slope deformation with an unprecedented level of detail. Studying rock slopes using TLS presents a series of key challenges, from accounting for the fractal character of rock surface to detecting the precursory deformation that may help in the future prediction of rock failures. Further investigation on the development of new algorithms for point cloud filtering, segmentation, feature extraction, deformation tracking and change detection will significantly improve our understanding on how rock slopes behave and evolve. Perspectives include the use of new 3D sensing devices and the adaptation of techniques and methods recently developed in other disciplines as robotics and 3D computer‐vision to rock slope instabilities research. Copyright © 2013 John Wiley & Sons, Ltd.