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