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.


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: 25.10.2022 - 08.12.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Jussi Nikander

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English


  • valid for whole curriculum period:

    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 for whole curriculum period:

    Assignments and exam

  • valid for whole curriculum period:

    Lectures (24), assignments (50), self-study (30), preparation for examination and examination (30)


Substitutes for Courses
SDG: Sustainable Development Goals

    11 Sustainable Cities and Communities

    15 Life on Land


Further Information
  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Autumn II
    2023-2024 Autumn II

    Enrollment :

    Registration for the courses via Sisu (