Identifying rock slope failure precursors using LiDAR for transportation corridor hazard management

Kromer, Ryan; Hutchinson, D. Jean; Lato, Matthew J.; Gauthier, David A.; Edwards, T C

doi:10.1016/j.enggeo.2015.05.012

Cited by 109 publications

(78 citation statements)

References 42 publications

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“…Given the development of spatially contiguous rockfall scars that has been observed in this setting (Fig. 11) and in other studies (Rosser et al, 2007Stock et al, 2012;Kromer et al, 2015a;Rohmer and Dewez, 2015;Royán et al, 2015), the creation of magnitude-frequency distributions from near-continuous monitoring has the potential to generate improved understanding of the underlying mechanisms of rockfall failure.…”

Section: Implications For Rockfall Magnitude-frequencymentioning

confidence: 99%

“…In practice, defining this timescale a priori is challenging and requires the ability to monitor the rock face over a sustained period in (near) real time. For rockfalls, high-resolution monitoring also shows evolution of failures through time, with event sequences and patterns related to the incremental growth of scars (Rosser et al, 2007Stock et al, 2012;Kromer et al, 2015a;Rohmer and Dewez, 2015;Royán et al, 2015). Barlow et al (2012) showed that a monitoring interval of 19 months underestimated the frequency distribution of small rockfall events, which coalesced into or were superimposed by larger rockfalls.…”

Section: Temporal Resolution Of Monitoringmentioning

confidence: 99%

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Optimising 4-D surface change detection: an approach for capturing rockfall magnitude–frequency

et al. 2018

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Abstract. We present a monitoring technique tailored to analysing change from near-continuously collected, high-resolution 3-D data. Our aim is to fully characterise geomorphological change typified by an event magnitude-frequency relationship that adheres to an inverse power law or similar. While recent advances in monitoring have enabled changes in volume across more than 7 orders of magnitude to be captured, event frequency is commonly assumed to be interchangeable with the time-averaged event numbers between successive surveys. Where events coincide, or coalesce, or where the mechanisms driving change are not spatially independent, apparent event frequency must be partially determined by survey interval.The data reported have been obtained from a permanently installed terrestrial laser scanner, which permits an increased frequency of surveys. Surveying from a single position raises challenges, given the single viewpoint onto a complex surface and the need for computational efficiency associated with handling a large time series of 3-D data. A workflow is presented that optimises the detection of change by filtering and aligning scans to improve repeatability. An adaptation of the M3C2 algorithm is used to detect 3-D change to overcome data inconsistencies between scans. Individual rockfall geometries are then extracted and the associated volumetric errors modelled. The utility of this approach is demonstrated using a dataset of ∼ 9 × 10 3 surveys acquired at ∼ 1 h intervals over 10 months. The magnitude-frequency distribution of rockfall volumes generated is shown to be sensitive to monitoring frequency. Using a 1 h interval between surveys, rather than 30 days, the volume contribution from small (< 0.1 m 3 ) rockfalls increases from 67 to 98 % of the total, and the number of individual rockfalls observed increases by over 3 orders of magnitude. High-frequency monitoring therefore holds considerable implications for magnitude-frequency derivatives, such as hazard return intervals and erosion rates. As such, while high-frequency monitoring has potential to describe short-term controls on geomorphological change and more realistic magnitude-frequency relationships, the assessment of longer-term erosion rates may be more suited to less-frequent data collection with lower accumulative errors.

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Section: Implications For Rockfall Magnitude-frequencymentioning

confidence: 99%

Section: Temporal Resolution Of Monitoringmentioning

confidence: 99%

Optimising 4-D surface change detection: an approach for capturing rockfall magnitude–frequency

et al. 2018

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“…Techniques such as the LiDAR equipment, digital photogrammetry and radar interferometry provide not only the analysis temporal patterns of the precursors before a large slope failure but also the spatial one, thus allowing the definition of the size of the unstable volumes (Oppikofer et al 2008;Ferrero et al 2011;Stock et al 2012;Royán et al 2014Royán et al , 2015. Periodic surveys using TSL have shown an increase of the rate of small-size rockfall events prior to the failure of large masses, which are mostly concentrated in the detachment zone (Rosser et al 2007;Royán et al 2014;Kromer et al 2015). The above observations are accompanied with an increase in the displacements of the moving mass away from a background level.…”

Section: Rockfall Predictionmentioning

confidence: 99%

Rockfall Occurrence and Fragmentation

Corominas

Mavrouli

Ruiz-Carulla

2017

Advancing Culture of Living With Landslides

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Rockfalls are very rapid and damaging slope instability processes that affect mountainous regions, coastal cliffs and slope cuts. This contribution focuses on fragmental rockfalls in which the moving particles, particularly the largest ones, propagate following independent paths with little interaction among them. The prediction of the occurrence and frequency of the rockfalls has benefited by the rapid development of the techniques for the detection and the remote acquisition of the rock mass surface features such as the 3D laser scanner and the digital photogrammetry. These techniques are also used to monitor the deformation experienced by the rock mass before failure. The quantitative analysis of the fragmental rockfalls is a useful approach to assess risk and for the design of both stabilization and protection measures. The analysis of rockfalls must consider not only the frequency and magnitude of the potential events but also the fragmentation of the detached rock mass. The latter is a crucial issue as it affects the number, size and the velocity of the individual rock blocks. Several case studies of the application of the remote acquisition techniques for determining the size and frequency of rockfall events and their fragmentation are presented. The extrapolation of the magnitude-frequency relationships is discussed as well as the role of the geological factors for constraining the size of the largest detachable mass from a cliff. Finally, the performance of a fractal fragmentation model for rockfalls is also discussed.

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“…In complex terrain, it is unreasonable to expect change to occur in a single dimension or along a common direction. An example of a complex rock slope is White Canyon, in Western Canada, where both movement of talus and rock slope deformation are occurring in multiple directions and the slope is geomorphologically complex [11].…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…In the hazard community, analysis of point cloud representations of topography have been used to study rock slope failures [1][2][3][4], large scale landslides [5][6][7], changes in permafrost terrain [8,9] and have been applied for assessment and monitoring of geohazards along transportation corridors [10,11], for example. In the geosciences and geomorphology, studies utilizing point clouds have included the study of fault zone deformation [12], mapping lithology [13], quantification of surface change in complex debris flow and river topography [14,15], the study of mass balance in glaciers [16] and the study of small-scale processes in arctic catchments [17], to name a few.…”

Section: Introductionmentioning

confidence: 99%

A 4D Filtering and Calibration Technique for Small-Scale Point Cloud Change Detection with a Terrestrial Laser Scanner

et al. 2015

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This study presents a point cloud de-noising and calibration approach that takes advantage of point redundancy in both space and time (4D). The purpose is to detect displacements using terrestrial laser scanner data at the sub-mm scale or smaller, similar to radar systems, for the study of very small natural changes, i.e., pre-failure deformation in rock slopes, small-scale failures or talus flux. The algorithm calculates distances using a multi-scale normal distance approach and uses a set of calibration point clouds to remove systematic errors. The median is used to filter distance values for a neighbourhood in space and time to reduce random type errors. The use of space and time neighbours does need to be optimized to the signal being studied, in order to avoid smoothing in either spatial or temporal domains. This is demonstrated in the application of the algorithm to synthetic and experimental case examples. Optimum combinations of space and time neighbours in practical applications can lead to an improvement of an order or two of magnitude in the level of detection for change, which will greatly improve our ability to detect small changes OPEN ACCESS Remote Sens. 2015, 7 13030 in many disciplines, such as rock slope pre-failure deformation, deformation in civil infrastructure and small-scale geomorphological change.

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Identifying rock slope failure precursors using LiDAR for transportation corridor hazard management

Cited by 109 publications

References 42 publications

Optimising 4-D surface change detection: an approach for capturing rockfall magnitude–frequency

Optimising 4-D surface change detection: an approach for capturing rockfall magnitude–frequency

Rockfall Occurrence and Fragmentation

A 4D Filtering and Calibration Technique for Small-Scale Point Cloud Change Detection with a Terrestrial Laser Scanner

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