Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h + 30.0 h
Q2
Teacher(s)
Deleersnijder Eric; Remacle Jean-François (compensates Deleersnijder Eric); Vanwambeke Sophie;
Language
English
Prerequisites
Elementary calculus and statistics
Aims
At the end of this learning unit, the student is able to : | |
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The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
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
Homeworks and practical reports; written exam.
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 (https://moodleucl.uclouvain.be/?lang=en)
Faculty or entity
GEOG
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Chemistry and Bioindustries
Master [120] in Geography : General
Master [120] in Agricultural Bioengineering
Master [120] in Environmental Bioengineering
Master [120] in Agriculture and Bio-industries
Master [60] in Geography : General
Master [120] in Forests and Natural Areas Engineering