The following topics will be addressed in the theoretical part of this course:
- introduction to GIS: what are GIS and what are they used for? Examples of applications in economy, demography, land and nature management, public utility and mobility are discussed.
- translation of the real world to analog and digital representations: discrete objects versus continuous fields and raster versus vector, generalisation and uncertainties in each step
- spatial variation, autocorrelation and interpolation
- reference systems and projection models
- data models (raster, vector, TIN, network): structure, possibilities for data compression and topology creation
- data file organisation: from flat file to object-relational database management system, indexation
- data acquisition: primary (remote sensing & GPS) and secondary data acquisition (digitise & vectorise), error tracking & editing
- spatial analyses: queries, measurements & transformations.
During the theoretical classes, you will give a short lecture yourself to your peer students (peer teaching) on 'remote sensing', an important method for primairy gegraphical data acquisition (eg, through satellite images, aerial photography and UAVs). To make this lecture (20-30') you will be provided with scans of a lecture book after the first theoretical class. Subjects will be devided among the students in the first or second class. You will be evaluated by your peers and the tutor based on assessment criteria previously discussed and set-up together with your peers. Be aware that your knowledge and insight in the content of these lessons will be evaluated.
During the practical part of the course, the student will independently solve a spatially explicit problem, starting with simple assignments with plenty of support provided by the assitant up to summarizing excercises with no extra info on the methodology to use. In an introductary course the basic operations and modules in the software package Idrisi (Clark Labs) are explained: openening maps and databases, using the symbol workshop, retrieve metadata, digitization, vetorisation etc. After that, you will learn by doing measurements, calculations, extractions, combinations, reclasses and queries.