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. The first supervisor is Dr. Martin Wegmann.
EAGLE course by Dr. Celia Baumhoer on Polar and Glacier Earth Observation
Our EAGLE students had this week the opportunity to attend an intensive course led by Dr. Celia Baumhoer, an expert in Earth observation of polar and glacier ecosystems. The course, which covered both the Antarctic and Arctic regions, as well as glaciers in the Alps,...
