Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
The student can identify the main spatial data modelling methods and understand how they are implemented. The student understands the basic principles of spatial data structures and algorithms. The student can apply modelling techniques and algorithms to spatial problems. The student can evaluate the suitability of solutions.
Credits: 5
Schedule: 27.10.2020 - 08.12.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Jussi Nikander
Teacher in charge (applies in this implementation): Jussi Nikander
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: Finnish, Swedish, English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
Spatial data modeling methods, data management and maintenance. Spatial algorithms, data structures, and indexing methods. Programming and GIS, as well as programming environments for GIS tools.
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
Lectures, assignments and exam
Workload
Valid 01.08.2020-31.07.2022:
Lectures (20), assignments (50), self-study (35), preparation for examination and examination (30)
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
Lecture notes and additional literature
Prerequisites
Valid 01.08.2020-31.07.2022:
GIS-E1030 Introduction to Spatial Methods
SDG: Sustainable Development Goals
11 Sustainable Cities and Communities
15 Life on Land