The aim of this course is to introduce advanced techniques in geographical research in such a way that the students get familiarised with fundamental as well as policy-orientated geographical research. Attention is paid to quantitative research methods and principles of modelling. The course illustrates these methods from the point of view of the different subdisciplines in geography. This course does not wish to just teach the methods but also wants to stress that the choice of research methods is not without consequences.
Basic knowledge of regression techniques, PCA and cluster analysis.
Knowledge of physics (mechanics), mathematics (calculus, matrix algebra) at the level of a bachelor in sciencesKnowledge of geomorphology, climatology and meteorology, demographics, soil science and GIS at the bachelor level.
Examples and samples
Toledo / e-platform
- Matlab: introduction to the computer language and the user interface and the most frequently used commands
- Use of m-files (scripts and functions)
- A simple pogram: calculation and visualisation of slope stability: use of functions
- Visualisation: construction of 1D and 2D plots: sensitivity of slope stability to parameter values.
- Use of conditions, discretization, loops, global and local variables and debuugging: calculation of the Stuve diagram
- Use of loops and conditions and the use of string variables: exchange of files between software packages (Idrisi and Matlab)
- Creation of a geodataset in Matlab
- Use of nested loops and conditions: a temperature and carbon model for the soil.
- master numerical modeling techniques and approaches used in geographical research
- master a higher programming language at a level that is sufficient to solve geographical problems independently
- have sufficient insight in possible solution strategies in order to decide indepdently on which one(s) can be used to solve a given problem
- be capable to develop a numerical solution for a geographical problem that results in a functioning, well-structured program
Description of learning activities
- Hands-on: students acquire the necessary experience in programming techniques by solving problems individually while having access to guidance
- home assignments: after the sesssions a small home assignment is given to students allowing them to deepen their understanding and skills by practising
- Take home: a larger programming problem is given as a take home. Students are capable of solving it by combining the various skills they learned during the practical sessions.
- handouts of slides, links to websites, matlab documentation
The evaluation consists of two parts:
- Part 1: oral exam without written preparation on the assignments given during the lectures and the small take home exercises
- Part 2: progamming: the students are given a geographic problem and are expected to write a functioning, well-structured matlab-program in ca. 3 hours.
Both parts account for 50% of the total mark for this course.