The Lab of Environmental Informatics mainly deals with computer-based modeling of environmental variables.
We combine remote sensing data from e.g. satellites, UAVs, LiDAR and hyperspectral sensors with in-situ measurements provided by e.g. field work, research stations or sensor networks. For analysing these data, spatio-temporal models are applied with a focus on machine learning methods and suitable validation strategies. These spatio-temporal models allow paractitioners to adequately apply and develop up-to-date prediction methods, which are not only important within the discipline of geography but also in other interdisciplinary subject areas.
Our main contextual focus is ecology, nature conservation, and climatology. For example, we currently apply and develop new methods for biodiversity monitoring and vegetation mapping.
In addition to a strong methodological and contextual focus, efficient data management is a core theme in our working group. We realize this by specifically developed databases and on-demand processing platforms.