Thomas Zieher

Sensor Data Integration for Landslide Monitoring—the LEMONADE Concept

The project LEMONADE (LandslidE MOnitoriNg And Data intEgration) aims to combine different techniques investigating their benefits and drawbacks. We present the different techniques used to monitor the active Corvara landslide located in the Italian Dolomites. Satellite remote sensing products allow covering the whole landslide providing 1D displacement measurements while proximal and terrestrial techniques can provide 3D information. In this paper, preliminary results considering each individual method applied are discussed and a first estimation of landslide displacements for the period considered is given.

Digital Terrain Model Resolution and its Influence on Estimating the Extent of Rockfall Areas

As rockfall can cause a great deal of damage, it is essential to know its spatial propagation. Rockfall models are sensitive to the resolution of input data, i.e. the Digital Terrain Model (DTM) used. Nowadays, high resolution elevation data are available area-wide from airborne laser scanning (ALS). However, rockfall models are designed for analysis on a certain scale, which means that high resolution input might not necessarily improve model results (e.g. for regional scale studies). Our aim is to estimate the reach of rockfall by analysing different input resolutions of an ALS DTM. The presented empirically–based model, implemented in Python 2.7, is a modified version of the zenital method including an iterative random walk trajectory model, which is designed for rockfall hazard assessment at the regional scale. Trajectories and rockfall probability maps are generated for selected DTM input resolutions. The comparison shows that high resolution DTMs do consider local topography better and thus lead to more realistic results than low resolution DTMs.

Are real-world shallow landslides reproducible by physically-based models? Four test cases in the Laternser valley, Vorarlberg (Austria)

In contrast to the complex nature of slope failures, physically-based slope stability models rely on simplified representations of landslide geometry. Depending on the modelling approach, landslide geometry is reduced to a slope-parallel layer of infinite length and width (e.g., the infinite slope stability model), a concatenation of rigid bodies (e.g., Janbu’s model), or a 3D representation of the slope failure (e.g., Hovland’s model). In this paper, the applicability of four slope stability models is tested at four shallow landslide sites where information on soil material and landslide geometry is available. Soil samples were collected in the field for conducting respective laboratory tests. Landslide geometry was extracted from pre- and post-event digital terrain models derived from airborne laser scanning. Results for fully saturated conditions suggest that a more complex representation of landslide geometry leads to increasingly stable conditions as predicted by the respective models. Using the maximum landslide depth and the median slope angle of the sliding surfaces, the infinite slope stability model correctly predicts slope failures for all test sites. Applying a 2D model for the slope failures, only two test sites are predicted to fail while the two other remain stable. Based on 3D models, none of the slope failures are predicted correctly. The differing results may be explained by the stabilizing effects of cohesion in shallower parts of the landslides. These parts are better represented in models which include a more detailed landslide geometry. Hence, comparing the results of the applied models, the infinite slope stability model generally yields a lower factor of safety due to the overestimation of landslide depth and volume. This simple approach is considered feasible for computing a regional overview of slope stability. For the local scale, more detailed studies including comprehensive material sampling and testing as well as regolith depth measurements are necessary.

Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma−1, corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement.