Accurately recognizing landslide deformation regions is important for understanding the
mechanisms of landslides and predicting landslide disasters. Using slopes in Dayu County …

Measuring the spatial distribution of discontinuities in tunnel faces obscured by shotcrete
and excavation profiles remains challenging. This paper introduces a novel method for …

Rockfall processes are now commonly studied through monitoring campaigns using repeat
lidar scanning. Accordingly, several recent studies have evaluated how the temporal …

Reality capture technologies such as Structure-from-Motion (SfM) photogrammetry have
become a state-of-the-art practice within landslide research workflows in recent years. Such …

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 …

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

Abstract Supervised Machine Learning (ML) can be used to automatically interpret remote
sensing data in engineering geology, with applications for rockfall and landslide …

Reality capture technologies, also known as close-range sensing, have been increasingly
popular within the field of engineering geology and particularly rock slope management …

Nowadays, artificial neural networks (ANN) are models widely used in many areas; one of
these is the classification of urban areas. This work aims to discuss a new framework for the …

[Objective] Due to the complex structure and features, traditional classification models for
tree branches and leaf point clouds typically face several problems, including poor stability …