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.

Laser scanning is routinely being used for the characterization and management of rockfall hazards. A key component of many studies is the ability to use the high-resolution topographic datasets for detailed volume estimates. 2.5-Dimensional (2.5D) approaches exist to estimate the volume of rockfall events; however these approaches require rasterization of the point cloud. These 2.5D volume estimates are therefore sensitive to picking an appropriate cell size to preserve resolution while minimizing interpolation, especially for lower volume rockfall events. To overcome the limitations of working with 2.5D raster datasets, surface reconstruction methods originating from the field of computational geometry can be implemented to assess the volume of rockfalls in 3D. In this technical note, the authors address the methods and implications of how the surface of 3D rockfall objects, derived from sequential terrestrial laser scans (TLS), are reconstructed for volumetric analysis. The Power Crust, Convex Hull and Alpha-shape algorithms are implemented to reconstruct a synthetic rockfall object generated in Houdini, a procedural modeling and animation software package. The reconstruction algorithms are also implemented for a selection of three rockfall cases studies which occurred in the White Canyon, British Columbia, Canada. The authors find that there is a trade-off between accurate surface topology reconstruction and ensuring the mesh is watertight manifold; which is required for accurate volumetric estimates. Power Crust is shown to be the most robust algorithm, however, the iterative Alpha-shape approach introduced in the study is also shown to find a balance between hole-filling and loss of detail.

Abstract. Rockfall is a complex natural process that can present risks to the effective operation of infrastructure in mountainous terrain. Remote sensing tools and techniques are rapidly becoming the state of the practice in the characterization, monitoring and management of these geohazards. The aim of this study is to address the methods and implications of how the dimensions of three-dimensional rockfall objects, derived from sequential terrestrial laser scans (TLSs), are measured. Previous approaches are reviewed, and two new methods are introduced in an attempt to standardize the process. The approaches are applied to a set of synthetic rockfall objects generated in the open-source software package Blender. Fifty rockfall events derived from sequential TLS monitoring in the White Canyon, British Columbia, Canada, are used to demonstrate the application of the proposed algorithms. This study illustrates that the method used to calculate the rockfall dimensions has a significant impact on how the shape of a rockfall object is classified. This has implications for rockfall modelling as the block shape is known to influence rockfall runout.

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Abstract. Remote sensing techniques can be used to gain a more detailed understanding of hazardous rock slopes along railway corridors that would otherwise be inaccessible. Multiple datasets can be used to identify changes over time, creating an inventory of events to produce magnitude–frequency relationships for rockfalls sourced on the slope. This study presents a method for using the remotely sensed data to develop inputs to rockfall simulations, including rockfall source locations and slope material parameters, which can be used to determine the likelihood of a rockfall impacting the railway tracks given its source zone location and volume. The results of the simulations can be related to the rockfall inventory to develop modified magnitude–frequency curves presenting a more realistic estimate of the hazard. These methods were developed using the RockyFor3D software and lidar and photogrammetry data collected over several years at White Canyon, British Columbia, Canada, where the Canadian National (CN) Rail main line runs along the base of the slope. Rockfalls sourced closer to the tracks were more likely to be deposited on the track or in the ditch, and of these, rockfalls between 0.1 and 10 m3 were the most likely to be deposited. Smaller blocks did not travel far enough to reach the bottom of the slope and larger blocks were deposited past the tracks. Applying the results of the simulations to a database of over 2000 rockfall events, a modified magnitude–frequency can be created, allowing the frequency of rockfalls deposited on the railway tracks or in ditches to be determined. Suggestions are made for future development of the methods including refinement of input parameters and extension to other modelling packages.