
Method for estimating rockfall failure probability using photogrammetry
Author(s) -
Lauri Uotinen,
Mateusz Janiszewski,
Raj Kishore Mishra,
H Munukka,
M Szydlowska,
Daniele Martinelli,
Paolo Dabove
Publication year - 2021
Publication title -
iop conference series earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/833/1/012063
Subject(s) - rockfall , photogrammetry , geology , point cloud , landslide , kinematics , geotechnical engineering , mining engineering , remote sensing , computer science , artificial intelligence , physics , classical mechanics
Passageways cut through rock might be subjected to rockfalls. If a falling rock reaches the road area, the consequences can be disastrous. The traditional rockfall risk assessment method and risk mitigation are based on on-site investigations performed by a geologist or a rock engineer. The parameters resulting from the investigation, such as discontinuities, orientations and spacings, potential rockfall initiation locations, slope geometry, and ditch profile, are either measured or estimated. We propose a photogrammetry-based method for estimating the probability of failure for rockfall. Several photographs of the rock-cut are taken, and a 3D geometry is computed using photogrammetry. This model already allows remote visual inspection of the site. The information about joint planes can be discovered semiautomatically from the point cloud. Next, the probability of rockfall reaching the road area is computed using probabilistic kinematic analysis on the geometry extracted using photogrammetry. The results can be used to define the rockfall probability for each rock-cut. Furthermore, the results can be used to determine the appropriate rockfall risk mitigation actions for each rock-cut.
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