Teaching of the Remote Sensing and Spatial Modelling Group
Remote sensing and spatial modelling can be seen as interdisciplinary in landscape ecology and and provides new methods to answer landscape-ecological issues. Our teaching focuses on the following topics:
- Methods of multiscale remote sensing and digital image processing to characterize landscapes and landscape-ecological processes in space and time.
- Methods of machine learning for modelling complex spatial and spatio-temporal ecosystem properties.
- Methods of operational and reproducible remote sensing data processing with open source software, especially "R".
The strongly methodologically oriented teaching is carried out on the basis of current research questions in landscape ecology, so that the methods contribute to new insights in the sub-disciplines.
Our teaching philosophy is strongly geared towards research-oriented learning and should accompany and support students in the development of problem-solving skills. It is important for us to involve students in our research projects, especially during their final theses.