3D/4D Geographic Point Cloud Time Series Analysis
Surface dynamics within a local landscape occur on a large range of spatiotemporal scales. The analysis of surface activities and structural dynamics in 4D point cloud data has therefore become an integral part of Earth observation. These data contain detailed 3D information of the topography with time as additional dimension.
Objectives (placeholder)
After completing this module you will be able to:
tbd.
Structure
- Principles of 3D/4D geographic point clouds
- Programming for point cloud analysis with Python
- Principles and basic algorithms of 3D change detection and analysis
- Time series analysis of 3D point clouds
- Machine / Deep learning-based 3D/4D point cloud analysis
Case studies: * Geomorphic monitoring of an Alpine rock glacier * 4D observation of coastal processes at a sandy beach
Prerequisites to perform this module
The following skills and background knowledge are required for this module.
Follow the links for more information on specific prerequisites and recommendations on external material for preparation.
Software
For this module, you will need the software listed below. If you did not install the software before starting the course, follow the links to the individual software or tools, for help in setting them up.
- CloudCompare for point cloud visualization and editing
- QGIS for visualization and editing of results (e.g., Digital Terrain Models)
- Python for programming of point cloud analysis
Use Cases and Data
In the research-oriented case studies, this module uses 3D/4D point cloud data for geomorphic change analysis at a rock glacier and the use case of 4D observation of coastal processes at a sandy beach.
Next unit
Start the module by proceeding to the first theme on Principles of 3D/4D geographic point clouds