Academic Catalog


Course Code: 9110722
METU Credit (Theoretical-Laboratory hours/week): 3(0-0)
ECTS Credit: 8.0
Department: Data Informatics
Language of Instruction: English
Level of Study: Graduate
Course Coordinator:
Offered Semester: Fall and Spring Semesters.

Course Content

This course introduces theories and techniques to store, visualize, and analyze spatio-temporal data. Spatio-temporal data are being collected in large quantities, especially in an urban environment where the location of moving objects (e.g. buses) could be traced with GPS sensors, or the situation in an environment could be monitored using CCTV cameras. Students will experience various software to analyze spatio-temporal data, with an emphasis on application to real-world problems. The course covers a range of topics, including exploratory spatio-temporal data analysis, visualization, regression, clustering, and anomaly detection. Lectures are supported by programming assignments, mainly of which will be implemented in Python. The course is suitable for graduate students who aim to advance their theoretical and practical skills in Geographic Information Systems (GIS), Smart Cities, and other related subjects.