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

Open the course unit brochure on Sisu
Study level:
Advanced studies
Grading scale:
0-5
Language:
English, Finnish
Responsible organisation:
Department of Biological and Environmental Science
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028

Tweet text

An advanced course related to spatial analyses and geoinformatics.

Description

An advanced course related to geographic information analyses, spatial statistics, and interpretation of remote sensing data. Main topics include estimation of erosion and nutrient runoff to waterways, characterisation of point patterns, spatial autocorrelation, spatial interpolation, and analyses and interpretation of remote sensing data sets. Programs to be used in practice are ArcGIS/QGIS and R. The students should be familiar with some GIS program rather well before attending the course.

Learning outcomes

After completing the course the student should be able to

  • Process and convert several types of geographic data sets with a GIS program into suitable formats needed for spatial analysis methods.
  • Convert airborne laser scanning data into different digital elevation models.
  • Perform hydrological modelling and estimate erosion and nutrient runoff risks.
  • Visualize and interpret the contents of aerial or satellite images with pixel-based and segment-based classification methods.
  • Characterize the nature of observed point patterns.
  • Estimate spatial autocorrelation.
  • Use several spatial interpolation methods, including cokriging.
  • Use GIS programs well enough to solve some data-analysis tasks given during the course.

Description of prerequisites

BENA4033/BENA4053 Basics of Geoinformatics, or similar prior knowledge of GIS data and programs.

Recommended prerequisites

Study materials

Lectures and exercises will be stored in Moodle and/or in a course-related network folder.

Literature

  • 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
  • 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

Description:
A seminar presentation, some exercises, and an exam need to be passed. The presentation and the exam will be evaluated with scale 0-5.
Evaluation criteria:
Exam 50%, seminar presentation 50%.
Time of teaching:
Period 2
Select all marked parts
Parts of the completion methods
x

Teaching (3 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English, Finnish

Teaching