Schedule: 10.01.2019 - 11.04.2019
Teacher in charge (valid 01.08.2018-31.07.2020):
Teaching Period (valid 01.08.2018-31.07.2020):
III-IV (spring term)
Learning Outcomes (valid 01.08.2018-31.07.2020):
After the course, you can identify the contributions of recent research in spatial data mining and geospatial simulation. You can carry out spatial knowledge discovery by using both computational and visual data mining methods to spatial problems. You can discuss the strengths and limitations of the methods.
Content (valid 01.08.2018-31.07.2020):
Spatial data mining methods for various types of spatial data sets: points, polygon networks, gridded data and networks. Advanced spatial classification and clustering methods, spatial association rules, graph data mining including moving objects data sets. Introduction to geospatial simulation and fuzzy modeling. Assignments, examination.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Examination, assignments and project work.
Workload (valid 01.08.2018-31.07.2020):
Learning sessions (24), assignments (20), project work (50), self-work and preparation for exam (38), exam (3)
Study Material (valid 01.08.2018-31.07.2020):
Lecture notes and additional literature
Substitutes for Courses (valid 01.08.2018-31.07.2020):
Maa-123.3585 Spatial Data Mining
Course Homepage (valid 01.08.2018-31.07.2020):
Prerequisites (valid 01.08.2018-31.07.2020):
GIS-E1030 Introduction to Spatial Methods, GIS-E1060 Spatial Analytics and GIS-E1070 Theories and techniques in GIS.
Grading Scale (valid 01.08.2018-31.07.2020):
Registration for Courses (valid 01.08.2018-31.07.2020):
Details on the schedule (applies in this implementation):
The course will be implemented in two periods. During the period III there are lectures (see the schedule) and few classroom exercises. The exam will be organized in the end of the period III. During period IV a project work will be made. The project is made in 3 persons teams according to the given guidelines (willbe published later). During the period IV there are no lectures, only few check points of the project work. In the project work each group will choose a topic, carry out analysis of the potential use of spatial methods in deicsion support and finally implement a selected set of analyses. The project work will be documented and presented as wel as assessed as part of the final grade. Details of the assessment and the project work will be given when the course starts.