Abstract
Rockfall inventories are essential to quantify a rockfall activity and characterize the hazard. Terrestrial laser scanning and advancements in processing algorithms have resulted in three-dimensional (3D) semi-automatic extraction of rockfall events, permitting detailed observations of evolving rock masses. Currently, multiscale model-to-model cloud comparison (M3C2) is the most widely used distance computation method used in the geosciences to evaluate 3D changing features, considering the time-sequential spatial information contained in point clouds. M3C2 operates by computing distances using points that are captured within a projected search cylinder, which is locally oriented. In this work, we evaluated the effect of M3C2 projection diameter on the extraction of 3D rockfalls and the resulting implications on rockfall volume and shape. Six rockfall inventories were developed for a highly active rock slope, each utilizing a different projection diameter which ranged from two to ten times the point spacing. The results indicate that the greatest amount of change is extracted using an M3C2 projection diameter equal to, or slightly larger than, the point spacing, depending on the variation in point spacing. When the M3C2 projection diameter becomes larger than the changing area on the rock slope, the change cannot be identified and extracted. Inventory summaries and illustrations depict the influence of spatial averaging on the semi-automated rockfall extraction, and suggestions are made for selecting the optimal projection diameter. Recommendations are made to improve the methods used to semi-automatically extract rockfall from sequential point clouds.
Highlights
As the projection diameter increases, the total number of extracted rockfall events decreases. This decrease is attributed to a higher degree of spatial averaging occurring with larger projection diameters, which makes smaller changing features less prominent, and less likely to be clustered into individual rockfall events
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Terrestrial laser scanning (TLS) platforms have resulted in detailed monitoring and documentation of rockfall activity at a new level of accuracy and detail
Summary
Rockfalls further challenge the safe operation of transportation corridors because it is difficult to prioritize the allocation of resources to be utilized to mitigate rockfall hazard across long transportation routes [3]. This task is challenging in Canada, where there is over 45,000 km of rail track [4] which is susceptible to various geohazards. As part of a quantitative hazard assessment, developing frequency-magnitude relationships from an inventory of events has become a common procedure [6]. Cumulative frequency-magnitude relationships are derived by accessing inventories of known rockfall events, spatial and temporal censoring of events can result in an inaccurate measurement of the hazard [3]. Additional factors which can contribute to rockfall censoring include difficulties associated with observing rockfall source zones from infrastructure-level vantage points, heavy alteration of a rock mass preventing observation of fresh surfaces (an indicator of recent rockfall), and propagation of rockfall material well beyond the area of interest which, subsequently, eliminates evidence of a rockfall occurring
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