ENVS1125 Geoinformatics, spatial statistics and remote sensing (3 cr)
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.
Study methods
Lectures 8 x 2 h, computer exercises 8 x 4 h, seminar, exercise work.
Content
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.
Literature:
| ISBN-number | Author, year of publication, title, publisher |
|---|---|
| 978-0-470-72144-5 | Longley P., Goodchild M., Maquire D. & Rhind D. 2011. Geographic Information Systems and Science, 3rd Edition. Wiley. (selected parts) |
| 978-0-470-01491-2 | Illian J., Penttinen A., Stoyan H. & Stoyan D. 2008. Statistical Analysis and Modelling of Spatial Point Patterns. Wiley. (selected parts) |
| 978-1-119-11461-1 | Cressie N. 2015. Statistics for Spatial Data. Revised Edition. Wiley. (Chapters 1-3) |
| 978-1-4614-7617-7 | Bivand R., Pebesma E. & Gomez-Rubio V. 2013. Applied Spatial Data Analysis with R, Second Edition. Springer. (Chapters 1-5, 7-10) |
| ISSN: 1799-313X | Holopainen M. et al. 2015. Geoinformatiikka luonnonvarojen hallinnassa. Helsingin yliopiston mets盲tieteiden laitoksen julkaisuja 7. (in Finnish, selected parts) |
| 978-0-1340-5816-0 | Jensen J.R. 2015. Introductory Digital Image Processing: A Remote Sensing Perspective, 4th Edition. Prentice Hall. (selected parts) |
Assessment criteria
Exercise work report 50%, seminar presentation 40%, activity in exercises 10%.
Prerequisites
BENA4033 Basics of Geoinformatics, or similar prior knowledge of GIS data and programs.