Towards sustainable development of natural environments based on continuous remote sensing monitoring
Continuous remote sensing monitoring of natural environments is important for increasing our understanding of landscape dynamics in the context of human-environment interactions, and for providing information needed for their conservation or management.
The analysis of physical processes, for example in sensitive mountainous and forest ecosystems, benefits from multidisciplinary research using time series of remote sensing data of different spatial and temporal scales, and the combination of multi-modal data sources, such as LiDAR point clouds, optical imagery, and thermal data.
These datasets enable to investigate a variety of processes underlying natural landscape dynamics, such as those related to damages and recovery of forests, changes of vegetation in high-mountain regions, or geomorphic activity of alpine rock glaciers.
Geomorphic activity of an alpine rock glacier is captured with repeated UAV-borne surveys.
The objective of the project is to acquire multi-modal remote sensing data adding to our existing time series at different study sites. Time series of remote sensing data will be used to develop innovative methods for monitoring and analyses of processes connected to changes of valuable mountainous environments (tundra, glaciers) and forest ecosystems in protected areas. UAV/aerial LiDAR point clouds, optical and thermal data will be combined with satellite and in-situ observations. The data will provide the basis for method development, including machine/deep learning algorithms, that will be applied in research fields of geography, plant biology and environmental sciences.
Establishing this joint comprehensive dataset will strengthen research collaboration among the project partners and supports research-based education by exchange visits of PhD and master students and by integrating new methods and software tools in research-oriented e-learning (project E-TRAINEE), developed by the project partners.
This collaboration project is funded in the framework of the 4EU+ programme of the European Union with Markéta Potůčková (Department of Applied Geoinformatics and Cartography, Charles University Prague) as PI of the project and Heidelberg University, University of Innsbruck and University of Warsaw as project partners. It follows the alliance built up through the E-TRAINEE strategic partnership project in the framework of the Erasmus+ programme of the European Union and the 4EU+ collaboration project 3D Landcover Monitoring.
The 3DGeo research group additionally supports this project through the acquisition of terrestrial laser scanning data at the continued monitoring site of an alpine rock glacier (project AHK-4D) for evaluation of the new UAV-borne acquisitions in this project.
- Zahs, V., Winiwarter, L., Anders, K., Bremer, M. Rutzinger, M. Potůčková, M., Höfle, B. (2022): Evaluation of UAV-borne photogrammetry and UAV-borne laser scanning for 3D topographic change analysis of an active rock glacier. EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022. DOI: 10.5194/egusphere-egu22-2513.
- Zahs, V., Winiwarter, L., Anders, K., Williams, J.G., Rutzinger, M. & Höfle, B. (2022): Correspondence-driven plane-based M3C2 for lower uncertainty in 3D topographic change quantification. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 183, pp. 541-559. DOI: 10.1016/j.isprsjprs.2021.11.018.
- Anders, K., Winiwarter, L., Mara, H., Lindenbergh, R., Vos, S. E., Höfle B. (2021). Fully automatic spatiotemporal segmentation of 3D LiDAR time series for the extraction of natural surface changes. ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 173, pp. 297-308. DOI: 10.1016/j.isprsjprs.2021.01.015.
- Ulrich, V., Williams, J.G., Zahs, V., Anders, K., Hecht, S., Höfle, B. (2021): Measurement of rock glacier surface change over different timescales using terrestrial laser scanning point clouds. Earth Surface Dynamics. Vol. 9, pp. 19-28. DOI: 10.5194/esurf-9-19-2021.
- Williams, J.G., Anders, K., Winiwarter, L., Zahs, V., Höfle, B. (2021): Multi-directional change detection between point clouds. ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 172, pp. 95-113. DOI: 10.1016/j.isprsjprs.2020.12.002.
- Winiwarter, L., Esmorís Pena, A., Weiser, H., Anders, K., Martínez Sanchez, J., Searle, M., Höfle, B. (2021): Virtual laser scanning with HELIOS++: A novel take on ray tracing-based simulation of topographic 3D laser scanning.[cs.CV]
- 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. DOI: 10.1002/ppp.2004.