BIO-3111 Geographical Information Systems (GIS) and Earth Observation - 10 ECTS
Local admission , application code 9371 - - Master`s level singular course.
Admission requires a Bachelor`s degree (180 ECTS) or equivalent qualification, with a major in biology of minimum 80 ECTS.
Recommended prerequisites: Students should have some familiarity with geographic information systems (GIS), basic statistics and general knowledge of practical use of computers.
- The meaning and importance of datum and projections in spatial data
- The physical background for remote sensing emphasizing the properties of electromagnetic radiation
- Principles of global navigation satellite systems (GNSS), its importance in gathering spatial reference data and integration in GIS
- Different remote sensing platforms (Drones/UAV and space borne satellites), active (radar and LIDAR) and passive (visible, infrared, thermal) sensors and application of multi- and hyperspectral data
- Understand the nature of raster data and basis of image processing (restoration, enhancement, transformation)
- Background of image analyzing techniques (time serial and change detection), classification (supervised, unsupervised) and spatial interpolation and regression
Skills/ Learning outcome
- How to find, download, store and implement remote sensing data in GIS
- Application of different image processing techniques to improve the visibility and information content of raster data
- Create informative and visual attractive maps by combining basis topographical data and thematic data layers
- Determine land cover or other earth features by means of different classification methods
- Extract and analyze information by selective query in tabular data and visualize it in maps
- Create new data layers by Boolean query in raster data and combine them in multi-criteria suitability mapping
- Application of spatial multivariate analysis such as principle component analysis (PCA) for noise removal, data redundancy and change detection
- Apply both linear and non-linear regression techniques to analyze spatial relationships and heterogeneity
- Do simple Python scripting in order to understand how to be more efficient and productive within a GIS
- Understand the importance and usefulness of GIS and remote sensing as tools for solving practical environmental problems, presenting thematic data and as a management system for spatial data
- Independent complete a practical GIS project using remote sensing data, image processing and analyzing techniques and present the results and conclusions in a written report
Home examination report grades as Passed/Failed.
Obligatory required coursework:
all PC-lab assignments and five multiple-choice test associated with the lectures must be approved.
There will be a re-sit examination for students that does not pass the previous ordinary home examination.