TMS016 / MSA301 Spatial statistics and image analysis Spring 25
This page contains the program of the course: lectures and computer labs. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.
Program
The schedule of the course is in TimeEdit.
The course typically has two lectures and two computer exercises each week. Details for these are given in the schedule below, which will be updated during the course. For each lecture, the chapters covered in the books are listed.
We have the following books and acronyms:
- LN denotes the lecture notes of Rudemo (found here),
- HS denotes the Handbook of spatial statistics, Gelfand, Diggle, Guttorp & Fuentes (found here),
- EL denotes The Elements of Statistical Learning, Hastie, Tibshirani & Friedman (found here),
- GH denotes Image Analysis for the Biological Sciences, Glasbey & Hogan (found here),
- MvL denotes Theory of Spatial Statistics: A Concise Introduction, M.N.M. van Lieshout (found here).
The lectures will be given in Euler.
Projects and examination
The deadlines for the projects can be found at the end of this page under Course summary. The reports should be uploaded in Canvas/Assignments.
In addition to the projects, there will be a final exam on June 4, 14:00-18:00.
Lectures and Exercises
Teachers of the course are Ottmar Cronie (lectures, examiner), ottmar@chalmers.se, and Mathis Rost (lectures, computer exercises), mathisr@chalmers.se. Lecture notes of the lectures can be found in Files/Lecture notes. The information below will be updated and extended on an ongoing basis.
| Time | Room | Lecture | Computer exercise | ||
|---|---|---|---|---|---|
| March 24 | Monday 8:00-9:45 |
Euler | L1 |
Introduction: LN pages 1-24, see also pages 1-8 of GH, Chapter 5. Lecture notes: LN1_2025.pdf Teacher: Ottmar |
|
| Monday 13:15-15:00 |
MVF24 and MVF25 | E1 | Introduction to Matlab and image processing. Please install the toolbox "Image Processing Toolbox". Teacher: Mathis |
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| March 26 | Wednesday 10:00-11:45 |
Euler | L2 |
Markov random fields: LN pages 60-67. Lecture notes: LN2_2025.pdf Teacher: Ottmar |
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| Wednesday 13:15-15:00 |
MVF24 and MVF25 | E2 |
The Ising and Potts model in Matlab.
Teacher: Mathis |
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|
| March 31 | Monday 8:00-9:45 |
Euler | L3 |
Continuous spatial random/stochastic processes/fields: LN pages 69-78. Lecture notes: LN3_2025.pdf Teacher: Ottmar |
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| Monday 13:15-15:00 |
MVF24 and MVF25 | E3 |
Simulation of Gaussian Fields
Teacher: Mathis |
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| April 2 | Wednesday 10:00-11:45 |
Euler | L4 |
OLS, GLS and ML estimation for random fields: LN pages 78-85. Lecture notes: LN4_2025.pdf Teacher: Ottmar
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|
| Wednesday 13:15-15:00 |
MVF24 and MVF25 | E4 |
Covariance estimation and kriging
Teacher: Mathis |
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| April 7 | Monday 8:00-9:45 |
Euler | L5 |
GMRFs: HS pages 172-175, 201-207. Lecture notes: LN5_2025.pdf Teacher: Ottmar |
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| Monday 13:15-15:00 |
MVF24 and MVF25 | E4, E5 |
Continuing with Covariance estimation and kriging.
Teacher: Mathis |
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| April 9 | Wednesday 10:00-11:45 |
Euler | L6 |
Point process analysis (part 1): LN Section 6, MvL Section 4. Lecture notes: LN6_2025.pdf Teacher: Ottmar |
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| Wednesday 13:15-15:00 |
MVF24 and MVF25 | E6 |
Finishing with Covariance estimation and kriging (Lab 4 and 5).
Teacher: Mathis |
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| DEADLINE FOR PLANNING REPORT PROJECT PART 3 |
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| April 23 | Wednesday 10:00-11:45 |
Euler | L7 |
Point process analysis (part 2): LN Section 6, HS Section 21. Lecture notes: LN7_2025.pdf Teacher: Ottmar |
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| Wednesday 13:15-15:00 |
MVF24 and MVF25 | E7 |
Point process analysis. Exploring spatstat, sampling point processes and the K-function
Teacher: Mathis |
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| April 28 | Monday 8:00-9:45 |
Euler | L8 |
Point process analysis (part 3): Second part of LN7_2025.pdf and LN8_2025.pdf Teacher: Ottmar |
|
| Monday 13:15-15:00 |
MVF24 and MVF25 | E8 |
Point process analysis. Exploring spatstat, sampling point processes and the K-function
Teacher: Mathis |
||
| April 30 | Wednesday 10:00-11:45 |
Euler | L9 |
Image classification Teacher: Mathis |
L9_2025.pdf |
| May 5 | Monday 8:00-9:45 |
Euler | L10 | ||
| Monday 13:15-15:00 |
MVF24 and MVF25 | E10 | |||
| May 7 | Wednesday 10:00-11:45 |
Euler | L11 | ||
| Wednesday 13:15-15:00 |
MVF24 and MVF25 | E11 | |||
| May 12 | Monday 8:00-9:45 |
Euler | L12 | ||
| Monday 13:15-15:00 |
MVF24 and MVF25 | E12 | |||
| May 14 | Wednesday 10:00-11:45 | Euler | Guest lecture (Magnus Röding) | ||
| Wednesday 13:15-15:00 |
MVH12 | ||||
| DEADLINE FOR PROJECT PART 1,2 & 3 | |||||
| May 19 | Monday 8:00-9:45 |
Euler |
Project seminars |
||
| Monday 13:15-15:00 |
MVH12 | Project seminars | |||
| May 21 | Wednesday 10:00-11:45 |
Euler | Project seminars | ||
| Wednesday 13:15-15:00 |
MVH12 | Project seminars | |||
Computer labs
The exercises will be done in Matlab, and some knowledge of Matlab is assumed. If you need an introduction, see Learning MATLAB, Tobin A. Driscoll ISBN: 978-0-898716-83-2 (The book is published by SIAM).
Most computer exercises will use functions written specifically for this course. These are collected in the following file: TMS016_Matlab.zip. Download this file and add the path to the folder in matlab: addpath('path_to_folder'). Then run the command tms016path to set the path to the files.
Data used in the exercies are colleded here: TMS016_Data.zip.
Reference literature:
Learning MATLAB, Tobin A. Driscoll ISBN: 978-0-898716-83-2 (The book is published by SIAM).
Course summary:
| Date | Details | Due |
|---|---|---|