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GIS module of the Masters Course on Tropical Animal Health and Production (MSTAH)
| Acronym: | EPIGIS |
| Project type: | Capacity Building |
| Time frame: | 2001 - todate |
| Funding agency: | ITM |
| Geographic keyword: Latin America | Africa | |
| General keyword: Decision support | GIS | Training | |
| Specific keyword: Spatial epidemiology |
GIS module of the Masters Course on Tropical Animal Health and Production (MSTAH) at the Institute for Tropical Medicine, Antwerp, Belgium.
This three week intensive GIS course is taught every year alternately in French and in English to target the different regions of Africa, Asia and South-America. The course fits within the Master of Science of Tropical Animal Health (MSTAH) program of the Institute of Tropical Medicine, Antwerp, Belgium.
At the end of the course the MSc students acquired a basic theoretical knowledge of vector and raster based GIS and are capable of performing common spatial analysis techniques using epidemiological field data sets. After the course "Ã la carte" assistance is provided to selected students needing more advanced GIS and spatial analysis knowledge in the framework of their PhD thesis.
During the course the following theoretical topics are covered:
Definition of a geographical information system and its applicability within veterinary sciences and spatial epidemiology
Projection systems
Differences and complementarities between vector-based and raster GIS
Database structure and attribute tables
Common spatial analysis techniques: spatial database querying, buffers, map overlay and other vector data geoprocessing techniques, map algebra and map transformation, map classification, network analysis, distance analysis, modeling
The course is especially focused on the practical training of the students and half of the time the students practice on individual computers using real case GIS-analysis examples within veterinary epidemiology. Currently ArcView3.2 is used as the reference tuition software package. During those practicals the students learn:
How to create standard maps
How to integrate their own field data with existing data sources
How to check for errors and for data quality
Where to find public domain data covering their country (digital terrain models, administrative boundaries, road network, hydrology network, land cover map, …)
How to use extensions for spatial analyses (such as map calculations, buffering, distance mapping, …)
How to visualize and present their analyses
As an example two documents with course exercises are given here: (1) logistic regression and (2) additional raster exercises.
Legend to the figures:
Figure 1: