ENVS1125 Geoinformatics, spatial statistics and remote sensing (3 cr)

Study level:
Advanced studies
Grading scale:
English, Finnish
Responsible organisation:
Department of Biological and Environmental Science
Curriculum periods:
2017-2018, 2018-2019, 2019-2020



An advanced course related to geographic information analyses, spatial statistics, and interpretation of remote sensing data. Main topics include estimation of erosion and runoff to waterways, characterization of point patterns, spatial autocorrelation, spatial modeling, spatial interpolation, and analyses and interpretation of remote sensing data sets. Programs to be used in practice are ArcGIS and R. At least ArcGIS should be familiar to students before attending the course.

Completion methods

Lectures 8 x 2 h, computer exercises 8 x 4 h, seminar, exercise work.

Assessment details

Exercise work report 50%, seminar presentation 40%, activity in exercises 10%.

Learning outcomes

After passing the course the student knows how to read and visualize several types of geographic data sets, how to convert geographic data sets into other formats, and how to transfer data sets between the ArcGIS and R programs. The student also knows how to perform hydrological modeling and runoff risk analyses, how to visualize and interpret the contents of remote sensing data sets, how to characterize point patterns, and how to analyze spatial data sets with statistical methods in practice with the programs used in this course.

Description of prerequisites

BENA4033 Basics of Geoinformatics, or similar prior knowledge of GIS data and programs.


  • Holopainen M. et al. 2015. Geoinformatiikka luonnonvarojen hallinnassa. Helsingin yliopiston metsätieteiden laitoksen julkaisuja 7. (in Finnish, selected parts); ISBN: ISSN: 1799-313X
  • Cressie N. 2015. Statistics for Spatial Data. Revised Edition. Wiley. (Chapters 1-3); ISBN: 978-1-119-11461-1
  • Longley P., Goodchild M., Maquire D. & Rhind D. 2011. Geographic Information Systems and Science, 3rd Edition. Wiley. (selected parts); ISBN: 978-0-470-72144-5
  • Illian J., Penttinen A., Stoyan H. & Stoyan D. 2008. Statistical Analysis and Modelling of Spatial Point Patterns. Wiley. (selected parts); ISBN: 978-0-470-01491-2
  • Bivand R., Pebesma E. & Gomez-Rubio V. 2013. Applied Spatial Data Analysis with R, Second Edition. Springer. (Chapters 1-5, 7-10); ISBN: 978-1-4614-7617-7
  • Jensen J.R. 2015. Introductory Digital Image Processing: A Remote Sensing Perspective, 4th Edition. Prentice Hall. (selected parts); ISBN: 978-0-1340-5816-0

Completion methods

Method 1

Select all marked parts
Parts of the completion methods

Teaching (3 cr)

Participation in teaching
Grading scale:
English, Finnish