2024-2025 / GEOG0057-1

Spatial analysis

Duration

30h Th, 30h Pr

Number of credits

 Master MSc. in Data Science, professional focus5 crédits 
 Master MSc. in Data Science and Engineering, professional focus5 crédits 
 Master in geography, global change, research focus5 crédits 
 Master in geography : general, teaching focus5 crédits 
 Master in geography, general, professional focus in urban and regional planning5 crédits 
 Master in geography: geomatics, professional focus in geodata expert5 crédits 
 Master in geography: geomatics, professional focus in land surveyor5 crédits 
 Master in urban planning and territorial development, professional focus in post-industrial and rurban territories5 crédits 

Lecturer

François Jonard

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course covers the following concepts : 

- Point patterns

- Surface data (spatial autocorrelation, neighborhood and spatial weighting, global and local spatial autocorrelation indices, significance test, ...)

- Spatial interactions and networks (connectivity, graph theory)

- Continuous data (semivariogram, spatial prediction, spatial interpolation, kriging)

- Modeling of geographical phenomena (ecological and atomistic fallacy, spatial regression, geographically weighted regression)


The practical lessons aim to apply spatial analysis methods in the R programming environment.

Learning outcomes of the learning unit

This course aims to guide students through a scientific approach to analysing spatial data.

The objective is to exploit the diversity of geographic data, to understand and implement spatial analysis methods to confirm or reject hypotheses, to reveal patterns in space and explore possible causes, and to model underlying processes.

Prerequisite knowledge and skills

Basic GIS concepts (geoprocessing, cartographic representation).

Students who do not have a basic understanding of GIS are encouraged to take the Introduction to GIS course at the beginning of the semester. 

 

Planned learning activities and teaching methods

Theoretical and pratical lectures.

 

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Additional information:

Theoretical and pratical lectures are face-to-face (every week).

A seminar is to be carried out independently by group of typically two or three students. Students have to present and critique in front of the class a recent scientific paper in the field of spatial analysis.
 

 

 

Course materials and recommended or required readings

Slides of the theoretical and pratical lectures are available on eCampus. Links to additional material (books or papers) are also provided at the end of each set of slides.

Exam(s) in session

Any session

- In-person

written exam


Further information:

The evaluation is based on the project (25% -if the exam on the theoretical part is passed) and a written exam (75%).

Each project will require to submit a report. Eeach group will have to present and defend his project in front of the class. The project is compulsory, students who have not realised and presented the project will not be allowed to take the exam.

The goal of the exam will be to assess the understanding of theoretical lectures. Students will have to answer questions covering the whole course material.

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Prof. François Jonard, francois.jonard@uliege.be



 

 

 

Association of one or more MOOCs