This paper presents a hybrid ensemble classifier combined synthetic minority oversampling
technique (SMOTE), random search (RS) hyper-parameters optimization algorithm and …

Rockfall inventories are essential to quantify a rockfall activity and characterize the hazard.
Terrestrial laser scanning and advancements in processing algorithms have resulted in …

Roof bolts such as rock bolts and cable bolts provide structural support in underground
mines. Frequent assessment of these support structures is critical to maintain roof stability …

Terrestrial LiDAR (light detection and ranging) has been used to quantify micro-topographic
changes using high-density 3D point clouds in which extracting the ground surface is …

Photogrammetry is increasingly being used to characterize rock slope hazards in
mountainous environments. With growth in the amount of point cloud data being collected …

Machine learning (ML) models are extensively used in spatial predictive modeling, including
landslide susceptibility prediction. The performance statistics of these models are vital for …

Terrestrial lidar data is a powerful resource for monitoring geohazards such as rockfall and
landslides. However, vegetated landslides with horizontal shear surfaces remain difficult to …

Rockfall detection is a crucial procedure in the field of geology, which helps to reduce the
associated risks. Currently, geologists identify rockfall events almost manually utilizing point …

Automatically identifying mine and tunnel infrastructure elements, such as rock bolts, from
point cloud data improves deformation and quality control analyses and could ultimately …

Due to the large scale and complex terrain of some outcrops, it is difficult to carry out
comprehensive and detailed stratum identification using traditional geological methods. The …