Lectures

Lecturers: Petri Rönnholm (responsible teacher), Jussi Nikander and Sami El-Mahgary

Due the forthcoming renovation of the master’s programme, this course is given the last time in Autumn 2023. Notice this when you make your study plans.

Lectures are recorded and published after the physical lecture. Physical lectures are in the hall K326 (Otakaari 4) on Tuesdays and in the hall U7 PWC (U135a, Otakaari 1) in Thursdays. Notice that you need to have an access token activated to access the hall K326 (https://www.aalto.fi/en/services/how-to-get-an-access-token-and-access-rights).

 

L1. Thu 7.9., 10-12, Introduction (Petri)

L2. Tue 12.9., 10-12, Convolution and interpolation with regular data (Petri)

L3. Thu 14.9., 10-12, Correlation and spatial autocorrelation (Petri)

L4. Tue 19.9., 10-12, Statistics, spatial statistics and least-squares method (Petri)

L5. Thu 21.9., 10-12, Clustering and classification (Petri)

L6. Tue 26.9., 10-12, Spatial quality and uncertainty (Petri) 

L7. Thu 28.9., 10-12, Spatial data structures (Jussi)

L8. Tue 3.10., 10-12, Computational geometry (Jussi)

L9. Thu 5.10., 10-12, Spatial decision making tools (Petri)

L10.  Storing and handling spatial data (Sami), Pre-recorded video lecture, no contact teaching


Examination: Thu 19.10., 9-12. This “lecture examination” will be a remote examination in MyCourses (you can utilize all lecture materials during the examination). Other possibilities to pass the examination later (14.12.2023 and 1.2.2024) are traditional physical “evening examinations” (in Otakaari 1 at 16.30–19.30, the hall is announced in the lobby on the examination day) with a pen and paper, in which no materials can be accesses.

 

Assignments:

All assignments have an email support (bai-bai.bairoh@aalto.fi). Do not hesitate to ask for help if you face problems. Remember to attach your full code when asking for help by email.

Assignment 1. Creation of orthophotos with Matlab (programming), DL 26.9. (Relates to lectures 1 and 2. Average workload estimate 11 h)

    Fri 22.9., 10:15-12:00, hall U257 (Windows computers), Otakaari 1, Support session for the assignment 1 (you can use email support as well)

Assignment 2. Spatial statistic in R (scripting), DL 3.10. (Relates to lectures 3 and 4. Average workload estimate 6 h), email support

Assignment 3. Implementation of k-nn and kmeans classification algorithms (in R, programming), DL 15.10.  (Relates to lecture 5. Average workload estimate 20 h, allocate enough time for this assignment), email support

All assignments are mandatory, and need to be passed before you can get the final grade of the course. 

It is okay to make programming assignments together with other students, but ensure that you learn Matlab and R programming since you will need these skills also in other courses in the Master’s programme in Geoinformatics.

Two bonus points to the exam is given for those who submit all (acceptable) reports in time (only if the exam is passed: 15/30 points)


Last modified: Tuesday, 29 August 2023, 3:54 PM