|Paper title||UAV Survey Methods for Geohazard Investigation, Modelling, and Monitoring|
|Form of presentation||Poster|
Effective data collection and monitoring solutions for geohazard applications can be technically and logistically challenging, due to instrumentation requirements, accessibility, and health and safety considerations. Uncrewed Aerial Vehicles (UAV), which overcome many of the aforementioned challenges, have become valuable data collection tools for geoscientists and engineers, providing new and advantageous perspectives for imaging. UAV may be deployed to gather data following natural disasters, to map geomorphological changes, or to monitor developing geohazards. UAV-enabled data collection methods are increasingly used for investigating, modelling, and monitoring of geohazards and have been adopted by geo-professionals in practice. Geoscientific research that utilizes UAV sensing methods include examples where the data collected can also be used to reconstruct scaled, georeferenced, and multi-temporal 3D models to perform advanced spatio-temporal analyses.
In a series of Norwegian case studies presented by the authors, UAV-based remote sensing methods, including well-established techniques, such as Structure-from-Motion photogrammetry, were utilized to generate high-resolution, three-dimensional surface models in remote, steep, or otherwise inaccessible terrain. In a first case study, a full-scale experimental avalanche was monitored with UAV technology. Photogrammetric reconstructions of approximately 500 airborne images, which relied on a combination of real-time-kinematic (RTK) positioning and a limited number of ground control points, were used to estimate total mobilized snow volume, while orthomosaics provided high-resolution overviews of the avalanche path before and after the event. Additional UAV surveys were performed over the same area in a baseline condition, i.e. without any snow cover, to derive a snow cover map of the path and surrounding valley. Geospatial and statistical analyses were performed to assess the quality of the UAV-derived products and to provide comparison for coarser resolution Airborne Laser Scanning (ALS) data.
In another case study, a rock wall failure occurred along a major highway shutting down two lanes of traffic for an extended period of time, while the road authority inspected and repaired the wall. UAV survey imagery, combined with multi-temporal, ground-based images, were used to reconstruct a high-resolution digital surface model before and after the failure. The model was used to estimate the volume of rock and for joint stability assessments of the wall surrounding the failure. In another study, a multiband near-infrared camera was used to survey a heavy metal contaminated shooting range from the air. The images were fused with point cloud data and analysed using spectral indices and unsupervised classification algorithms to derive a high-resolution vegetative cover map. In yet another example, rainfall-induced debris flows were mapped, and erosion volume was assessed using UAV-derived data. Finally, the authors will report on preliminary findings from GEOSFAIR – Geohazard Survey from Air, a national Innovation Project for the Public Sector, led by the Norwegian Public Roads Administration. One of the aims of the GEOSFAIR project is to test emerging sensors, such as UAV-borne LiDAR, near- and longwave-infrared imagers, and ground-penetrating radar sensors, for roadside UAV operations and snow avalanche warning services.