Modern Methods of Rock Mass Characterisation and Rockfall Monitoring: A Review

Blahůt, Jan; Racek, Ondřej

doi:10.1007/978-3-031-23859-8_1

Cited by 2 publications

(1 citation statement)

References 264 publications

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“…These incidents underscore the necessity for effective management and prevention strategies for rockfall. Further exploration on these topics can be found in studies from Geoenvironmental Disasters and Social Sciences [5,6], with innovative approaches to rockfall monitoring and early warning systems detailed in a Scientific Reports article [7][8][9] and strategies for mitigation, especially in Colorado's mountainous terrain, provided by the Colorado Geological Survey [10,11].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters

Lin,

Chiu,

Chen

et al. 2024

J. Imaging

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Taiwan, frequently affected by extreme weather causing phenomena such as earthquakes and typhoons, faces a high incidence of rockfall disasters due to its largely mountainous terrain. These disasters have led to numerous casualties, government compensation cases, and significant transportation safety impacts. According to the National Science and Technology Center for Disaster Reduction records from 2010 to 2022, 421 out of 866 soil and rock disasters occurred in eastern Taiwan, causing traffic disruptions due to rockfalls. Since traditional sensors of disaster detectors only record changes after a rockfall, there is no system in place to detect rockfalls as they occur. To combat this, a rockfall detection and tracking system using deep learning and image processing technology was developed. This system includes a real-time image tracking and recognition system that integrates YOLO and image processing technology. It was trained on a self-collected dataset of 2490 high-resolution RGB images. The system’s performance was evaluated on 30 videos featuring various rockfall scenarios. It achieved a mean Average Precision (mAP50) of 0.845 and mAP50-95 of 0.41, with a processing time of 125 ms. Tested on advanced hardware, the system proves effective in quickly tracking and identifying hazardous rockfalls, offering a significant advancement in disaster management and prevention.

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Section: Introductionmentioning

confidence: 99%

Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters

Lin,

Chiu,

Chen

et al. 2024

J. Imaging

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Multitemporal Monitoring of Rocky Walls Using Robotic Total Station Surveying and Persistent Scatterer Interferometry

Beltramone,

Rindinella,

Vanneschi

et al. 2024

Remote Sensing

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Rockfall phenomena are considered highly dangerous due to their rapid evolution and difficult prediction without applying preventive monitoring and mitigation actions. This research investigates a hazardous site in the Municipality of Vecchiano (Province of Pisa, Italy), characterized by vertical rock walls prone to instability due to heavy fracturing and karst phenomena. The presence of anthropical structures and a public road at the bottom of the slopes increases the vulnerability of the site and the site’s risk. To create a comprehensive geological model of the area, Unmanned Aircraft System (UAS) photogrammetric surveys were conducted to create a 3D model useful in photointerpretation. In accessible and safe areas for personnel, engineering–geological surveys were carried out to characterize the rock mass and to define the portion of rock walls to be monitored. Results from nine multitemporal Robotic Total Station (RTS) measurement campaigns show that no monitoring prisms recorded significant displacement trends, both on the horizontal and vertical plane and in differential slope distance. Additionally, satellite Persistent Scatterer Interferometry (PSI) analysis indicates that the slopes were stable over the two years of study. The integration of these analysis techniques has proven to be an efficient solution for assessing slope stability in this specific rockfall-prone area.

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Modern Methods of Rock Mass Characterisation and Rockfall Monitoring: A Review

Cited by 2 publications

References 264 publications

Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters

Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters

Multitemporal Monitoring of Rocky Walls Using Robotic Total Station Surveying and Persistent Scatterer Interferometry

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