Remote Sensing and Geovisualization of Rock Slopes and Landslides

Over the past two decades, advances in remote sensing methods and technology have enabled larger and more sophisticated datasets to be collected. Due to these advances, the need to effectively and efficiently communicate and visualize data is becoming increasingly important. We demonstrate that the use of mixed- (MR) and virtual reality (VR) systems has provided very promising results, allowing the visualization of complex datasets with unprecedented levels of detail and user experience. However, as of today, such visualization techniques have been largely used for communication purposes, and limited applications have been developed to allow for data processing and collection, particularly within the engineering–geology field. In this paper, we demonstrate the potential use of MR and VR not only for the visualization of multi-sensor remote sensing data but also for the collection and analysis of geological data. In this paper, we present a conceptual workflow showing the approach used for the processing of remote sensing datasets and the subsequent visualization using MR and VR headsets. We demonstrate the use of computer applications built in-house to visualize datasets and numerical modelling results, and to perform rock core logging (XRCoreShack) and rock mass characterization (EasyMineXR). While important limitations still exist in terms of hardware capabilities, portability, and accessibility, the expected technological advances and cost reduction will ensure this technology forms a standard mapping and data analysis tool for future engineers and geoscientists

Engineering geological characterization of the 2014 Jure Nepal Landslide: An Integrated Field, Remote Sensing-Virtual/Mixed Reality Approach

Characterization of unstable rock slopes can pose a high level of risk toward the geoscientist/engineer in the field due to inaccessibility and safety issues. During recent decades, rapidly developing remote sensing (RS) techniques, including Terrestrial Laser Scanning (TLS), Terrestrial Digital Photogrammetry (TDP), and Unmanned Aerial Vehicle Structure-from-Motion (UAV-SfM) are being progressively employed for landslide investigation and risk assessment. These methods allow acquisition of three-dimensional (3D) data sets from previously inaccessible terrain with sub-centimeter accuracy. This research describes an innovative approach to investigate the preliminary engineering geological characterization of a large (~5.5 Mm3), destructive landslide that occurred on August 2nd, 2014 near Jure in Sindhupalchok, ~70 km northeast of Kathmandu, Nepal. Various methods have been employed including traditional field surveys, RS techniques and preliminary 2D/3D numerical modelling with the objective of understanding conditioning factors, slope failure mechanisms, and identifying/mitigating future hazards at the site. With four years of RS data, analysis of strength degradation and progressive weakening of the rock mass is investigated by linking process of erosion and deposition using 3D change detection algorithms. The slope is still potentially in an unstable state, undergoing progressive rockfalls/slides with the most recent major event (~20,000 m3) in August 2017. Results throughout this thesis, including 2D/3D rock engineering mapping and modelling have been integrated into an interactive 3D Virtual/Mixed Reality (VR/MR) Jure Landslide geodatabase model, enabling an immersive and enhanced engineering 3D geovisualization experience. A comparative 2D/3D, and VR/MR rockfall simulations has been undertaken and developed within an augmented reality Microsoft HoloLens. Moreover, this thesis concludes on how VR/MR techniques can be employed to conduct discontinuity mapping on virtual outcrops and provide a game-changing way that geoscientists can communicate landslide investigation and risk assessment in all stages of rock engineering