Lectures

(The implementation of lectures will be either a live online session or a pre-recorded video lecture. Further information will be updated here later) 

L1. Tue 8.9., 10-12, Introduction (Petri), webinar, zoom-link is under Materials section

L2. Thu 10.9., 10-12, Convolution and interpolation with regular data (Petri), Pre-recorded video lecture

L3. Tue 15.9., 10-12, Correlation and spatial autocorrelation (Petri), Pre-recorded video lecture

L4. Thu 17.9., 10-12, Statistics and spatial statistics (Petri), Pre-recorded video lecture

L5. Tue 22.9., 10-12, Clustering and classification (Petri), Pre-recorded video lecture

L6. Thu 24.9., 10-12, Spatial data structures (Petri), Pre-recorded video lecture

L7. Tue 29.9., 10-12, Computational geometry (Petri), Pre-recorded video lecture

L8. Thu 1.10., 10-12, Spatial decision making tools (Petri), Pre-recorded video lecture

L9. Tue 6.10., 10-12, Spatial quality and uncertainty (Petri) , Pre-recorded video lecture

L10. Thu 8.10., 10-12, Storing and handling spatial data (Sami), Pre-recorded video lecture


Assignments:

(All assignments need to be accepted before you get the final grade of the course. Returning an assignment after DL decreases the final grade by one number. However, the maximum drop is 2 and a grade cannot go below 1)

Creation of orthophotos with Matlab (programming), DL 25.9.

Spatial statistic in R (scripting), DL 2.10.

Basics of geoinformatics with a pen and paper, DL 14.10.

Implementation of k-nn and kmeans classification algorithms (in R, programming), DL 23.10.

(Both Matlab and R programming are needed also in other courses in the Master’s programme in Geoinformatics)


Quizzes and learning diary:

From each lecture there will be quizzes. In addition, you will update learning diary during the course.

There will be no final examination, but the grade is given from Quizzes and learning diary.

Last modified: Friday, 18 September 2020, 12:57 PM