LiDAR Remote Sensing and Applications
The aim of this module is to deepen the understanding of Laser Remote Sensing techniques. The module provides an overview of today’s common sensors used for the Light Detection And Ranging (LiDAR) Remote Sensing along with the practical use case scenarios revolving around use of Point Cloud data and its handling for feature extraction. Both aspects, theory and practice will provide a good ground for standalone handling of the collected LiDAR data and further development based on the common elements (data fusion, cross platform adaptation). The module begins with a basic overview of the sensory platform and theoretical background on LiDAR. This will be followed by an in depth analysis of specific research applications (Satellite, airborne, terrestrial and bathymetric). Practical lessons will cater the need for hands on analysis of LiDAR obtained Point Cloud data. The initial lessons will provide basic principles of loading the data and exploration of the existing features. This will be upgraded with practical analysis of pre-classified point cloud data with derivation of DEM models and basic feature extraction based on class coding. Final part of the practical work will focus on advanced aspects of working with non-classified point cloud data in order to produce DEM models and extract specific features (vegetation masking, building extraction). This course will also use practical elements obtained from the Object-Based analysis (OBIA) methodology domain. A special focus will be given to the topic of storing and using LiDAR data with databases.
- Understanding the technology behind LiDAR as an active sensor and what makes it different from the other existing Remote Sensing approaches
- Developing thorough understanding of the complex process from collecting the LiDAR data to generation of the final modeled outputs
- Gaining an insight into the structure of a Point Cloud and obtaining hands-on experience in dealing with such data
Dr. Ivan Tomljenovic
Doctoral college GIScience
We would like to inform you that this is an exclusively english language module, hence any kind of communication with the module instructor should be in English. A discussion forum is maintained in Blackboard in order to support efficient module instruction. You are requested to submit all your questions related to this module to this forum only. The instructor will check all incoming comments on a regular basis. He will answer your questions or provide you with pointers for solving your problems. The module is delivered in form of an instructed self-study that is based on explorative learning process and process. Theoretical concepts are complemented with practice oriented examples demonstrated with help of multimedia elements. Upon completion of the module students are requested to evaluate the module, which is a part of our quality assurance policy and practice.
Software and LiteratureTrimbles eCognition Developer, FugroViewer
Assessment and GradingThe assessment is based on your completed assignments. They must be submitted in written format (.PDF/.DOC) to the Dropbox within the required time period. If assignments are submitted late, the instructor is not obligated to grade them. It will be listed as such on your transcript.
|Start:||3 times a year|
|Registration deadline:||two weeks before start|
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