Application and limitations of ground-based laser scanning in rock slope characterization

Author(s):  
M Sturzenegger ◽  
M Yan ◽  
D Stead ◽  
D Elmo
Keyword(s):  
2006 ◽  
Vol 34 ◽  
pp. 63-72
Author(s):  
A. Strouth ◽  
E. Eberhardt ◽  
O. Hungr

A "Total Slope Analysis" methodology, that combines several numerical techniques, is adopted to investigate an unstable rock slope in Washington State, USA. For this specific study, the distinct-element code UDEC is used to assess the stability and potential failure volume of the rockslide. Once the potential rockslide volume has been estimated and failure mechanism assessed, the runout path, distance and velocity are assessed using the dynamic or rheological flow model DAN3D. Site investigation and data reconnaissance plays an important role for both stages in the "Total Slope Analysis", including outcrop mapping, aerial photograph interpretation, scanline joint surveys and 3-D laser scanning. The results of the "Total Slope Analysis" can be directly applied to assessment and mitigation of the landslide hazard, greatly aiding engineering judgment by providing key qualitative and quantitative insights into the risk analysis.


2013 ◽  
Vol 39 (1) ◽  
pp. 80-97 ◽  
Author(s):  
Antonio Abellán ◽  
Thierry Oppikofer ◽  
Michel Jaboyedoff ◽  
Nicholas J. Rosser ◽  
Michael Lim ◽  
...  

2021 ◽  
Vol 50 (8) ◽  
pp. 2179-2191
Author(s):  
Zainab Mohamed ◽  
Abd Ghani Rafek ◽  
Mingwei Zhang ◽  
Yanlong Chen ◽  
Thian Lai Goh ◽  
...  

The United Nations Development Program agenda 2030 has charted out seventeen Sustainable Development Goals (SDG) whereby Malaysia as a member has strategically set the platform for growth. From the seventeen agendas, the SDG 9 (built resilient, promote inclusive and sustainable industrialization and foster innovation) and SDG 11 (make cities and human settlements inclusive, resilient, and sustainable) requires a paradigm shift from conventional engineering approach for environmentally induced disasters. Leveraging multidisciplinary ability and information and communications technology (ICT) in the landslide disaster studies had enabled regional-scale information acquirement for hazards identification, exposure, and risk assessment to meet the goals. The investigated limestone hill, Batu Caves is located within the suburban city of Kuala Lumpur. The land use around the hill is extensive and the area is highly populated with encroachment to the toe of the limestone hill. The purpose of the risk study was to assess the limestone hill’s stability and hazards and the exposure that may lead to the vulnerability of the residences and commercial activities at and around the hill. Therefore, an engineering risk assessment study was carried out to determine rock fall hazard potential. The Terrestrial Laser Scanning survey was utilized to obtain the hillside’s cross section. Discontinuity mapping was conducted to identify rock block size and rock slope was analyzed using rock mass classification system to determine rock slope quality. The rockfall analysis was conducted to identify rock rollout distance and produce rock fall hazard maps. The Slope Mass Rating for the slope BC1A, Parcel 1, Batu Caves was determined as 61, and is classified as a partially stable. The maximum rollout distance at this slope was 11 m. This illustrates the practical output of this study that can be applied for mitigation and future development of the area.


2021 ◽  
Vol 13 (8) ◽  
pp. 1479
Author(s):  
Heather Schovanec ◽  
Gabriel Walton ◽  
Ryan Kromer ◽  
Adam Malsam

While terrestrial laser scanning and photogrammetry provide high quality point cloud data that can be used for rock slope monitoring, their increased use has overwhelmed current data analysis methodologies. Accordingly, point cloud processing workflows have previously been developed to automate many processes, including point cloud alignment, generation of change maps and clustering. However, for more specialized rock slope analyses (e.g., generating a rockfall database), the creation of more specialized processing routines and algorithms is necessary. More specialized algorithms include the reconstruction of rockfall volumes from clusters and points and automatic classification of those volumes are both processing steps required to automate the generation of a rockfall database. We propose a workflow that can automate all steps of the point cloud processing workflow. In this study, we detail adaptions to commonly used algorithms for rockfall monitoring use cases, such as Multiscale Model to Model Cloud Comparison (M3C2). This workflow details the entire processing pipeline for rockfall database generation using terrestrial laser scanning.


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