Point clouds and machine learning applications in rock slope modelling

Dr. Ioannis Farmakis

The analysis of 3D point cloud data has been a valuable practice in rock slope modelling, with increasing development and acceptance starting in the early 2000’s. We use point clouds as a reference for geometric rock mass characterization, as terrain models for physical simulations and monitoring, and as a digital asset for remote visual inspections, amongst other applications. However, their analysis is often limited to daunting manual processing for the extraction of meaningful information. If we consider point clouds as digital reality assets, a whole new field of intelligent applications becomes available with the integration of machine learning. The talk presents the potential of 3D computer vision applications in the monitoring and modelling of rock slope hazards through examples. It addresses questions related to data structures and representation and proves the superiority of fully 3D processing of digital rock slope models for the extraction of valuable information related to rock slope management. Finally, it tackles the integration of supervised learning in automating rockfall monitoring with point cloud classification neural networks and present a novel approach to slope-scale rockfall susceptibility modelling (RSM) as a point cloud semantic segmentation (PCSS) problem.

Dr. Ioannis Farmakis Research Associate, University of Newcastle (Australia) & National Technical University of Athens (Greece)

Dr. Ioannis Farmakis is an independent consultant and a research fellow of The University of Newcastle, Australia and the National Technical University of Athens, Greece. He obtained his bachelor’s degree from the School of Sciences of the Aristotle University of Thessaloniki, Greece and since 2018 he has been a MSc degree holder in Applied and Environmental Geology graduated from the same institution. In September 2023, he completed his doctorate studies at Queen’s University, Canada, specializing in the use of 3D point clouds and machine learning for geo-engineering applications and software development. Dr. Farmakis currently does research in the field of digital rock slope monitoring investigating rockfall phenomena in high resolution using remote sensing, computer vision, and geoinformatics.

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