Three-dimensional rockfall shape back analysis: methods and implications

Abstract

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.

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

“…Remote sensing (RS)-aided derived in monitoring examples in terrain and surfaces, aeolian geomorphology, fluvial geomorphology and coastal geomorphology landslides and their traits. Mountain types, relief types, relief classes IKONOS OSA 3/M , DHM25 3/R , GTOPO30-DEM 3/R , LiDAR 2/L [330][331][332] Volcano types (volcanic full forms),volcanoes, lava flow fields, hydrothermal alteration, geothermal explorations, heat fluxes, volcanoes hazard monitoring Doves-PlanetScop, Terra/Aqua MODIS 3/M , EO-1 ALI 3/M , Landsat-8 OLI 3/M/TIR , Terra ASTER 3/M/TIR , MSG SEVIRI 3/M/TIR , LiDAR 2/L [333][334][335][336][337] Mountain hazards, mass movement (rock fall probability, boulders, denudation, mass erosion, rock decelerations, rotation changes, slope stability, rock shapes, particle shapes, patterns, structures, faults and fractures, holes and depressions) InSAR 3/R , SAR 3/R , LiDAR 2/L , Digital Orthophoto 1/RGB [338][339][340][341][342][343][344][345][346][347] Landslide chances, landslide evolution Digital Orthophoto 1/RGB [348] Above ground-chances, disturbances Opencast mining, sand mining and extraction, tipping, dumps TanDEM-X 3/R , SRTM DEM 3/R , ALOS PALSAR 3/R , ERS-1 3/R , GeoEye GIS 3/M , WorldView-3 Imager 3/M , IKONOS OSA 3/M , Landsat-5 TM/-7 ETM+/-8 OLI 3/M/TIR , IRS-P6 LISS-III 3/M , High resolution satellite data of Google 3/M , LiDAR 2/L [349][350][351][352][353][354][355] Vegetation traits as proxy of the geochemical parameters HyMAP 2/H [356] Below ground-chances, disturbances Salt mines, fracking ERS-1/-2 3/R , ASAR 3/R , ALOS PALSAR 3/R , Landsat-5 TM/-7 ETM+/-8 OLI 3/M/TIR [113,357] Table 5. Cont.…”

Temporal-Spatial Frequency Rockfall Data from Open-Pit Highwalls Using a Low-Cost Monitoring System

“…Then, the point cloud is transformed (i.e., rigid rotation and translation) into a new local reference system with origin in the centre of gravity and with coordinate axes aligned with the principal axes of inertia, with the z axis defined as the principal axis corresponding to the highest moment of inertia. According to Bonneau et al [64], the use of the side lengths of the bounding box of a point cloud can result in an overestimation of the block volume and inaccurate shape characterisation. Hence, the block volume is calculated by rasterising the point cloud (raster size equal to GSD), considering the points from the reference and new model separately, and using a mapping plane orthogonal to the local z direction.…”

“…The shape classification proposed by Sneed and Folk [65] based on the ratios b/a, c/a and (a-b)/(a-c) is used. Although initially developed for pebbles, it is a very common classification scheme for rockfall fragments [30,64]. The ratios are plotted on a ternary diagram (Figure 7) where blocks can be classified into 10 different shape classes: C (compact), CP (compact-platy), CB (compact-bladed), CE (compact-elongated), P (platy), B (bladed), E (elongated), VP (very platy), VB (very bladed), VE (very elongated).…”

Development of Improved Semi-Automated Processing Algorithms for the Creation of Rockfall Databases

“…As the amount of research in this field has increased, many applications of TLS have been developed including modelling rockfall volumes and fall scarps [1,9,12,13], conducting hazard and risk surveys [1,14,15] and analyzing trends using magnitude-frequency curves [16][17][18][19][20]. Recent studies have used TLS to generate rockfall databases, which can subsequently be used for various types of analyses [18,21,22].…”