After successful completion of this course, the student should be able to:
- Understand how point clouds are generated from GNSS, IMU, and range finder measurements and relative sensor registration.
- Assess the applicability of airborne laser scanning for various tasks, like surface reconstruction and 3D modelling.
- Design survey plans to acquire point clouds taking into account the accuracy and point density requirements.
- Evaluate the quality of laser scanning datasets.
- Determine and apply optimal point cloud processing methods to extract surface descriptions for geometric modelling and point cloud classification.
- Interpret and analyse point cloud processing results
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Airborne laser scanning is a modern technology to acquire and monitor the geometry of the Earth's surface and objects above the surface like buildings, trees and road infrastructure. This course provides an overview on the state of the art of these techniques, potential applications as well as methods to extract geo-information from the recorded point clouds.
Topics addressed are
- Principles of airborne laser scanning
- Sensor and point cloud properties, accuracy potential, error sources and correction methods, quality analysis
- Comparison to other data acquisition techniques
- Overview on various applications.
- General point clouds processing: visualisation, segmentation, classification
- Digital terrain models: extraction of terrain points and break lines.
- Detection and modelling: 3D building reconstruction, extraction of vegetation characteristics, change detection with multi-temporal and single epoch data for map updating.
Assessment
Written exam (80%), individual assignment (20%)
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