Increasing Spatio-Temporal Resolution for Monitoring Alpine Solifluction Using Terrestrial Laser Scanners and 3D Vector Fields

Abstract

This article investigates the usage of terrestrial laser scanner (TLS) point clouds for monitoring the gradual movements of soil masses due to freeze–thaw activity and water saturation, commonly referred to as solifluction. Solifluction is a geomorphic process which is characteristic for hillslopes in (high-)mountain areas, primarily alpine periglacial areas and the arctic. The movement can reach millimetre-to-centimetre per year velocities, remaining well below the typical displacement mangitudes of other frequently monitored natural objects, such as landslides and glaciers. Hence, a better understanding of solifluction processes requires increased spatial and temporal resolution with relatively high measurement accuracy. To that end, we developed a workflow for TLS point cloud processing, providing a 3D vector field that can capture soil mass displacement due to solifluction with high fidelity. This is based on the common image-processing techniques of feature detection and tracking. The developed workflow is tested on a study area placed in Hohe Tauern range of the Austrian Alps with a prominent assemblage of solifluction lobes. The derived displacements were compared with the established geomonitoring approach with total station and signalized markers and point cloud deformation monitoring approaches. The comparison indicated that the achieved results were in the same accuracy range as the established methods, with an advantage of notably higher spatial resolution. This improvement allowed for new insights considering the solifluction processes.

Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard

“…The snow cover present in the aerial imagery taken in 2020 and data gaps in both point clouds led us to integrate both datasets [32,52]. Usually, within point-cloud-based strategies, the data acquired in at least two epochs are used to determine the geometric changes between them [30,43,44,52]. Here, apart from the accuracy assessment, we compared and combined the data acquired within one year.…”

“…It estimates local positions in two input point clouds by using the surface normal vectors to determine the median point within a cylinder of defined radius [42,43]. For the point-cloud-based strategy, the M3C2 algorithm is chosen as the bestestablished method, especially in earth sciences, when dealing with irregular surfaces [44]. Here, we used the algorithm to compare the data and find areas where differences between both point clouds were significantly larger than the estimated accuracy of the DEMs generated from those point clouds.…”

Review on the Research and Applications of TLS in Ground Surface and Constructions Deformation Monitoring

“…In point cloud distance measurement, for point-based strategies, point cloud is reduced to a subset of salient points, also known as features or key points, which have unique characteristics considering their local neighborhood. This means that they can be found in point clouds of different measurement periods and matched between point clouds without the need to pre-register the point clouds in a common coordinate system and use the neighborhoods in Euclidean space [ 15 ]. Grid-based methods require the creation of models from one or two point clouds, respectively, but are more robust to outliers than C2C, which finds the nearest points based only on Euclidean distance [ 14 , 16 ].…”

Applications of Image-Based Computer Vision for Remote Surveillance of Slope Instability

“…Numerous monitoring approaches, including ground-based radar (e.g., Rosenblad et al, 2015), InSAR (e.g., Ferretti et al, 2007;Ferretti, 2014), Lidar (e.g., Lin et al, 2013;Tortini et al, 2015;Kromer et al, 2017;Williams et al, 2018;Williams et al, 2019;Holst et al, 2021), seismometers (e.g., Suriñach et al, 2005), and more recently computer vision (O'Donovan, 2005;Zach et al, 2007;Wedel et al, 2009;Javier et al, 2013;Sánchez Pérez et al, 2013;Kim et al, 2020;Hermle et al, 2022), have been used to study landslides and slope instability. However, the elevated cost, complexity, and intrinsic technical limitations of these methods frequently necessitates the development of alternative and complementary techniques.…”