Leonard Hammer handed in his B.Sc. thesis on “explaining spatial patterns of stork movements using remote sensing data”. He used stork data from the Lake Constance region and applied species distribution models on different behavioral states (nesting, feeding etc.) using Landsat TimeScan data. This data set provides temporal metrics for the last years, such as max, min and variance of the NDVI. Moreover, he tested different model performances and scaling effects and found partly that lower resolution data resulted in more sounds results. He was supervised by R. Remelgado and Dr. Martin Wegmann
New publication: Mapping animal paths using drones and deep learning
We're pleased to share our latest open-access research on automatically detecting animal paths in Africa's Kruger National Park using drone imagery and deep learning. Published in Ecological Informatics, our study demonstrates how deep learning can be employed to...
