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Advanced Geospatial Data Mining and Visualization
Last Updated: 2026-02-05 16:30:03
Abstract
This course provides knowledge in advanced methods for extracting and visualizing big geospatial data. Through a combination of lectures, hands-on exercises, and real-world case studies, participants will develop practical skills and knowledge for analyzing and visualizing complex spatial datasets.
Objective
Acquire the ability to apply spatial analytical methods to heterogeneous spatial data. Familiarity with advanced interactive geodata visualization techniques.
Content
This course will combine lectures and hands-on exercises. Through multiple case studies, students will learn to apply geospatial data analysis and visualization methods through various practical case studies. The students will also be given prepared tutorials and datasets. The data will be provided to the students within the course. -Lecture 1: Introduction to the course, objectives, dataset, and exam structure -Lecture 2: Theoretical background and examples of correlation analysis, event detection, and anomaly analysis -Lecture 3: Case study 1 – An introduction to the case study. Hands on work on a given task on correlation analysis and visualization. -Lecture 4: Case study 1 - Hands on work on a given task on correlation analysis and visualization. - Lecture 5: Case study 1 - Hands on work on a given task on correlation analysis and visualization. -Lecture 6: Case study 2 - An introduction to the case study. Hands on work on a given task on event detection and visualization. -Lecture 7: Case study 2 - Hands on work on a given task on event detection and visualization. -Lecture 8: Case study 2 - Hands on work on a given task on event detection and visualization. -Lecture 9: Case study 3 - An introduction to the case study. Hands on work on a given task on anomaly detection and visualization. -Lecture 10: Case study 3 - Hands on work on a given task on anomaly detection and visualization. -Lecture 11: Case study 3 - Hands on work on a given task on anomaly detection and visualization. -Lecture 12: Case study 4 - An introduction to the case study. Hands on work on a given task on a combination of analysis and visualizations. -Lecture 13: Case study 4 - Hands on work on a given task on a combination of analysis and visualizations. -Lecture 14: Case study 4 - Hands on work on a given task on a combination of analysis and visualizations.
Resources
Lecture Notes
Lecture slides and related material will be made available in digital form.
Literature
Lecture slides and related material will be made available in digital form.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Advanced Geospatial Data Mining and Visualization |
|
2 h weekly |