Assessment of Landslide-Induced Displacement and Deformation of Above-Ground Objects Using Uav-Borne and Airborne Laser Scanning Data

Abstract

<p><strong>Abstract.</strong> Multi-temporal 3D point clouds acquired with a laser scanner can be efficiently used for an area-wide assessment of landslide-induced surface changes. In the present study, displacements of the Vögelsberg landslide (Tyrol, Austria) are assessed based on available data acquired with airborne laser scanning (ALS) in 2013 and data acquired with an unmanned aerial vehicle (UAV) equipped with a laser scanner (ULS) in 2018. Following the data pre-processing steps including registration and ground filtering, buildings are segmented and extracted from the datasets. The roofs, represented as multi-temporal 3D point clouds are then used to derive displacement vectors with a novel matching tool based on the iterative closest point (ICP) algorithm. The resulting mean annual displacements are compared to the results of a geodetic monitoring based on an automatic tracking total station (ATTS) measuring 53 retroreflective prisms across the study area every hour since May 2016. In general, the results are in agreement concerning the mean annual magnitude (ATTS: 6.4 cm within 2.2 years, 2.9 cm a<sup>−1</sup>; laser scanning data: 13.2 cm within 5.4 years, 2.4 cm a<sup>−1</sup>) and direction of the derived displacements. The analysis of the laser scanning data proved suitable for deriving long-term landslide displacements and can provide additional information about the deformation of single roofs.</p>

Spatio‐temporal assessment of the hydrological drivers of an active deep‐seated gravitational slope deformation: The Vögelsberg landslide in Tyrol (Austria)

“…In several cases DSGSDs are accompanied by secondary, more active subunits preferentially occurring on highly fractured and intensely deformed rock masses on the bulged toe of the DSGSD (Bovis & Evans, 1996;Crosta et al, 2014). Such landslide subunits can show enhanced, fluctuating displacement rates ranging from centimetres to several metres per year (Brückl et al, 2013;Pfeiffer et al, 2018;Zieher et al, 2019). In some cases they accelerate and result in catastrophic slope failures such as rockslides and rock avalanches, endangering human well-being and infrastructure situated on the top of the landslide or within its potential run-out area (Carlà et al, 2017;Ostermann & Sanders, 2017).…”

Machine Learning: New Potential for Local and Regional Deep-Seated Landslide Nowcasting

“…The aforementioned solutions require access to the landslide to mount the sensors or benchmarks. Alternative solutions include ground-based InSAR (GB-InSAR) [82][83][84] and LiDAR surveys ( [85][86][87], reviewed by [88]), that require no access to the landslide itself, but can be operated from anywhere with direct visibility on the landslide. Therefore, the system can be used as emergency intervention too [89].…”

“…Measurements can only begin after installation, after sliding behaviour has been detected. Campaign-based measurements provide a limited temporal resolution, but may be operated without a fixed set-up on site [87].…”

Monitoring Terrain Deformations Caused by Underground Mining Using Uav Data

“…However, this problem was investigated by e.g., Puniach et al (2021). Recently, also light-weight LiDAR sensors utilization for deformation monitoring using UASs have been investigated (Zieher et al, 2019). However, none of the above publications analysed the application of UAV-borne Laser Scanning (ULS) data to deformation monitoring in the underground mining area.…”