Jakob Schwalb-Willmann just started his M.Sc. thesis titled “A deep learning movement prediction model using environmental data to identify movement anomalies”. He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based model that predicts movements from movement history alongside environmental covariates in order to detect movement anomalies. He will establish simulated, controlled environments that allow precise adjustments of the model inputs to test the model’s feedbacks and its variability. It can be considered as a precursor study for the model’s deployment on real data and to only experimentally apply it on such due to the given constraints (time and content) of his M.Sc. thesis.
Field work equipment arrived with Earth Observation design
Our field work jackets and backpacks arrived with Earth Observation design. Now we can conduct our UAV campaigns and are easily recognizable as researcher of the University of Wuerzburg. We are looking forward to some time in the field sampling various landcover...
