Practical Applications of Geospatial InformationLaajuus (5 cr)

Objective

After completing the course, the student is able to collect data from different sources on their own initiative, combine them and create appropriate analyses to study real challenges. In addition, the student masters the cooperation between spatial data software and programming, and in addition to the existing tools, is able to perform spatial data analysis operations in a manner tailored to the specific research object.

Content

- Application of spatial analysis to real-world problems
- Combining multiple data sources in spatial databases
- Using Python programming in conjunction with spatial data software
- Utilizing analysis principles to create new operating models

Qualifications

Spatial analysis. An applied course in information technology is useful, but not necessary.

Assessment criteria, satisfactory (1)

Students are able to apply the principles of spatial data analysis, and produce reasoned solutions in the selection of data type and analysis methods.

Assessment criteria, good (3)

Students are able to combine data from different sources and target spatial data analyses to them in the necessary way, both with the help of spatial data software and spatial databases. The student has the skills to act as part of a working group on spatial data, and distributes both spatial data sets and methods targeted at it into a generally functional form.

Assessment criteria, excellent (5)

Assessment criterion of the course, 4-5: The student has a broad understanding of the principles of spatial data analysis, and is able to apply them on a wide scale without problems. The student is able to use Python programming as needed to support analyses, and is able to integrate the generated code into the spatial data software.