AHK-4D - High-resolution and high-frequency monitoring of the rock glacier Äußeres Hochebenkar (AHK) in Austria
The aim of this project is to develop a methodology to quantify the magnitudes and frequencies of individual surface change processes of a rock glacier over several years. We do this by analyzing three dimensional (3D) surface change based on high-resolution, high-frequency and multisource LiDAR data. The derived information will enable us to develop methods to automatically characterize and disaggregate multiple processes and mechanisms that contribute to surface change signals derived from less frequent monitoring (e.g. yearly). Such methods can enhance our general understanding of the spatial and temporal variability of rock glacier deformation and the interaction of rock glaciers with connected environmental systems.
Observed changes to rock glacier surfaces reflect the interaction of multiple processes of deformation. These include permafrost creep, permafrost slide, zonal thinning or thickening, advection of surface microtopography, 3D straining, general mass changes (heaving or settlement) and horizontal shearing and rotation. These processes feature different spatial characteristics, magnitudes and timescales of occurrence that are not yet fully understood.
Only by monitoring 3D surface change at high spatial (centimeter point spacing)- and high temporal (sub-monthly)-resolution, can the different geomorphic processes be characterized and their contribution to surface change on rock glaciers quantified. Such data serve as a basis for the development of methods that make use of the temporal information of short-interval (< sub-monthly) time-series data. This can help to characterize and disaggregate multiple processes by their spatio-temporal dynamics. This also includes the tracking of individual boulder movements from point clouds.
In addition to this, the simulation and development of suitable LiDAR data acquisition strategies is an important consideration of the project. Virtual laser scanning can not only help to efficiently acquire data sets within given limitations (e.g. spatial and temporal resolution, accuracy, spatial completeness) based on available resources. It can also be used to develop and test methods for 3D surface change analysis on rock glaciers.
Study Site and Data
A measurement network will be installed at the active rock glacier Äußeres Hochebenkar - AHK (Ötztal valley, Austria) in order to acquire high spatial- and high temporal (e.g. bi-weekly)- resolution and multisource (terrestrial and UAV-borne LiDAR) topographic LiDAR data.
These data will be complemented by time-lapse cameras and subsurface electrical resistivity tomography measurements for comparison.
Äußeres Hochebenkar rock glacier from the opposite side of the valley (Photo: Rudolf Sailer).
The project is a joint research project between the the 3DGeo Research Group and Geomorphology and Soil Geography Research Group (Institute of Geography, Heidelberg University) and the Institute of Geography of the University of Innsbruck.
The Äußeres Hochebenkar (AHK) rock glacier has a long record of research dating back to 1938.
In a recent study (Zahs et al. 2019), a method for accurate 3D point cloud based quantification and analysis of geomorphological activity on rock glaciers has been presented. Findings of this study demonstrate the value of short-interval (< monthly) monitoring to relate 3D surface change signals to individual processes of deformation. Further work within the 3DGeo group has assessed the contribution of surface change over a three-week time interval to the annual surface change budget of a rock glacier using multitemporal topographic LiDAR.
The Äußeres Hochebenkar rock glacier will also be examined in a related research project (Geomorph4D), with the aim of exploring the importance of rockfalls and talus accumulation at the headwall of rock glaciers, and to examine this within the context of changing climate conditions, and therefore stresses, within paraglacial environments. Therefore, an approach will be developed which is capable of measuring and characterizing multiple types of surface change across a point cloud scene, with a view to automatically extracting their contribution to the overall sediment budget (i.e. the supply, transport, and storage of sediment within the area of interest).
Recent applications of a broader spectrum of LiDAR dimensionality by the inclusion of the physical time dimension from repeated lidar acquisitions has been reviewed in Eitel et al. 2016. For example has the importance of 4D monitoring for the improved understanding of other geomorphic processes been shown by Williams et al. (2018). In this study, the development of a methodology to monitor rock falls at hourly intervals enabled the detection of small events, which would otherwise be censored through superimposition or coalescence of neighbouring events. The ability to characterize a full range of event volumes was shown to provide unique insights into the mechanisms of rockfalls and their controls. Moreover, the project Auto3Dscapes focuses on the development of a computational method for autonomous 3D Earth observation which interlinks the decoupled processes of surveying and data processing by integrating observed Earth surface dynamics as feedback. This approach enables immediate automatic adaptation of the 3D observation strategy (acquisition and analysis) to account for the specific spatiotemporal properties that have been obtained from the accumulating time series datasets. In Anders et al. (2019), it has been investigated how the temporal interval influences volume change observed on a sandy beach regarding the temporal detail of the change process and the total volume budget, on which accretion and erosion counteract.
- Geomorph4D: Characterising multi-process geomorphic change.
- Auto3DScapes: Autonomous 3D Earth observation.
- HELIOS: Heidelberg LiDAR Operations Simulator.
- GEODYNAMO4D: Tracing geographic dynamics on 4D Point Clouds.
Open Access Datasets
Multi-temporal terrestrial laser scanning datasets at the AHK rock glacier are openly provided on PANGAEA:
Pfeiffer, J., Höfle, B., Hämmerle, M., Zahs, V., Rutzinger, M., Scaioni, M., Lindenbergh, R., Oude Elberink, S., Pirotti, F., Bremer, M., Wujanz, D. & Zieher, T. (2019): Terrestrial laser scanning data of the Äußeres Hochebenkar rock glacier close to Obergurgl, Austria acquired during the Innsbruck Summer School of Alpine Research. PANGAEA. DOI: https://doi.pangaea.de/10.1594/PANGAEA.902042 .
- Ulrich, V., Williams, J.G., Zahs, V., Anders, K., Hecht, S., Höfle, B. (2020): Disaggregating surface change mechanisms of a rock glacier using terrestrial laser scanning point clouds acquired at different time scales. Earth Surface Dynamics Discussion. https://doi.org/10.5194/esurf-2020-55, in review.
- Zahs, V., Hämmerle, M., Anders, K., Hecht, S., Rutzinger, M., Sailer, R., Williams, J.G., Höfle, B. (2019): Multi-temporal 3D point cloud-based quantification and analysis of geomorphological activity at an alpine rock glacier using airborne and terrestrial LiDAR. Permafrost and Periglacial Processes. Vol. 30 (3), pp. 222-238. https://doi.org/10.1002/ppp.2004.