5.00 credits
30.0 h + 30.0 h
Q2
Teacher(s)
Deleersnijder Eric; Vanwambeke Sophie;
Language
English
Prerequisites
Elementary calculus and statistics
Main themes
At the end of this course, the students will be able to:
· Identify and characterize a model and understand the mathematics of a process-based model;
· Translate a physical, environmental and/or spatial process into mathematical language;
· Grasp all steps of a modelling process, from the statement of a question to the validation of results;
· Start engaging with professionals of environmental modelling and management in various settings.
Contribution to the acquisition and evaluation of the following learning outcomes of the programme in geography (general and climatology):
· AA 1.1, AA 1.2, AA 1.4, AA 1.6, and particularly AA.1.7 and AA 1.8
· AA 3.3, AA 3.4
· AA 4.1, AA 4.2
· AA 5.5
· AA 6.1, 6.2
Most importantly, these learning outcomes are central to this course:
· AA 4.3, AA 4.4, AA 4.5
· Identify and characterize a model and understand the mathematics of a process-based model;
· Translate a physical, environmental and/or spatial process into mathematical language;
· Grasp all steps of a modelling process, from the statement of a question to the validation of results;
· Start engaging with professionals of environmental modelling and management in various settings.
Contribution to the acquisition and evaluation of the following learning outcomes of the programme in geography (general and climatology):
· AA 1.1, AA 1.2, AA 1.4, AA 1.6, and particularly AA.1.7 and AA 1.8
· AA 3.3, AA 3.4
· AA 4.1, AA 4.2
· AA 5.5
· AA 6.1, 6.2
Most importantly, these learning outcomes are central to this course:
· AA 4.3, AA 4.4, AA 4.5
Content
The course includes two parts. The first half focuses on differential models. The second half looks into spatial modelling and modelling practice. The course starts by a general introduction on modelling.
The following topics are dealt with:
· How to model? The various steps of modelling;
· Typology of models;
· Differential models: linear ordinary differential problems (e.g. first order decay);
· Differential models: non-linear ordinary differential problems (e.g. population modelling, prey-predator populations, epidemiological model);
· Differential models: space-time dependency;
· Spatial models: making space explicit, self-organising systems (e.g. epidemic diffusion, erosion processes);
· Spatial models: interacting, spatially-explicit objects: agent-based models (e.g. land use change)
How to model? Model validation.
The following topics are dealt with:
· How to model? The various steps of modelling;
· Typology of models;
· Differential models: linear ordinary differential problems (e.g. first order decay);
· Differential models: non-linear ordinary differential problems (e.g. population modelling, prey-predator populations, epidemiological model);
· Differential models: space-time dependency;
· Spatial models: making space explicit, self-organising systems (e.g. epidemic diffusion, erosion processes);
· Spatial models: interacting, spatially-explicit objects: agent-based models (e.g. land use change)
How to model? Model validation.
Teaching methods
Classroom lectures and practical sessions, involving active learning methods.
All lectures are in English. The course material and practical notes are in English and French.
All lectures are in English. The course material and practical notes are in English and French.
Evaluation methods
The course is evaluated continuously through various assignments associated to practicals and a written/oral exam. The continuous evaluation is worth 60% of the final marks and the exam 40%.
Other information
Prerequisites LGEO1342 - Geographical Information Systems (or similar); LGEO1341 - Statistical modelling (or similar); Mathematics (or similar)
Online resources
Slides, lecture notes and additional reading material on Moodle.
Faculty or entity
GEOG
