Uncovering the Mechanisms of Migratory Bird Navigation with Big Data Analytics.

Project description

Migratory birds are capable of amazing feats of navigation, yet our understanding of how they do this remains fairly rudimentary. We explore how birds use Earth’s magnetic field for navigation in a novel data science approach to ecology. For this, we will connect bird tracking data from over 60 studies with geomagnetic data from satellites and terrestrial networks, to, for the first time, find out about the actual geomagnetic conditions that the birds experienced during their journeys. These joint data will be explored with data mining and results validated with navigation simulations in real geomagnetic data, collected in robotic drone surveys.

To get more information about this project visit this link: https://udemsar.com/research/

My role

I worked as postdoctoral researcher to support the developing of a new method that integrates animal movement trajectories with remote sensing data from Swarm mission (European Space Agency - ESA) data. We materialize the data fusion method in a script-tool called MagGeo to help researchers link Earth’s magnetic field data with GPS trajectories of tracked animals. The tool was developed in Python. This is the first tool of this kind, and we hope it can help ecologists better understand how wildlife response to short-term variations on the geomagnetic field.

If you want more infomation about MagGeo please visit this link: https://maggeo.github.io/MagGeo/