Remote Sensing and Environmental Modelling
The understanding of environmental processes and the analysis of interactions between environment, ecosystems and humans is increasingly important in environmental stewardship and the development of sustainable means of human dependency on environmental systems. Environmental modelling is an essential tool that allows scientists, managers and decision makers both to understand reality and to enable future scenarios. Since simulation of spatially distributed phenomena and processes becomes increasingly important, spatial information are needed as input data as well as for calibration and validation purposes – a gap which can be filled by using remote sensing data. The course “Remote Sensing and Environmental Modelling” covers the possibilities and problems of the use of RS in order to model environmental systems. Main subjects are the pre-processing of the RS data, their integration into ecological models as well as the analysis and interpretation of model results.
Learning outcomes: Advanced knowledge of the most important cycles of matter (e.g. water, nitrogen) Sound knowledge of most important computer based modelling theories to enable the transfer of scientific theories to model approaches in practice Advanced skills in integrating RS data to assist spatial distributed model approaches Interpretation skills to analyze model results (e.g. changing discharge due to land use changes) in the context of a given model environment Advanced skills to discuss model results based on both scientific and practical experience.