Credits: 5

Schedule: 11.09.2018 - 18.10.2018

Teacher in charge (valid 01.08.2018-31.07.2020): 

Petri Rönnholm

Teaching Period (valid 01.08.2018-31.07.2020): 

I (autumn term)

Learning Outcomes (valid 01.08.2018-31.07.2020): 

To understand the spatial extensions of conventional statistical, mathematical and computational methods including the concept of spatial autocorrelation. To recognize the special requirements of geodetic, photogrammetric, remote sensing and GIS applications in spatial processing. To apply suitable spatial analysis methods in these applications. To evaluate the quality of geographical data. To be able to program simple algorithms in Matlab and R.

Content (valid 01.08.2018-31.07.2020): 

This course introduces various mathematical, statistical and computational methods in their spatial forms. The contents of the course cover processing, analysis and quality issues of spatial data including measures of autocorrelation, spatial statistics, convolution, spatial interpolation, data classification and clustering methods, geometric problem solving and spatial algorithms, and quality concepts and measures.

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Examination and assignments

Workload (valid 01.08.2018-31.07.2020): 

Lectures (16 h), assignments (60 h), self-study (32 h), preparation for examination + examination (27 h)

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-57.3110 Käytännön kaukokartoitus (6 op) OR Maa-123.3520 Principles of Geostatistics (3 cr) AND Maa-123.3410 Fuzzy Modeling of Geographic Information (4 cr)

Course Homepage (valid 01.08.2018-31.07.2020):

Grading Scale (valid 01.08.2018-31.07.2020): 



Registration and further information