The NetCDA project team is looking forward to welcoming the project partners from all over Germany for a Kick-Off Meeting on Thursday, May 16, 2024.
On May 15 a small group of participants will already get together with project lead Dr. Michael Thiel and project coordinator Alexandra Bell to work on guidelines for further successful cooperation between German and WASCAL partners.
You may also follow our website for some further insights: netcda.org.
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The team of our "Super-Test-Site Würzburg" consortium (University of Würzburg, the Karlsruhe Institute of Technology, the Friedrich-Alexander-University Erlangen-Nürnberg, Leibniz-Institute for Länderkunde in Leipzig and the German Aerospace Center)...
On Friday, November 21st, a MainPro project meeting was held to exchange ideas with our cooperating small and medium-sized enterprises (SMEs). Within our MainPro project, we aim to identify the changes caused by climate change in the Main Valley and its surroundings...
On Thursday, 20 November, more than 30 experts from the Earth Observation Research Cluster (EORC) at the University of Würzburg and the Earth Observation Center (EOC) at the German Aerospace Center (DLR) in Oberpfaffenhofen gathered at the EORC for a full-day internal...
We are very pleased to announce the successful acquisition of the third-party funded BMFTR project HABITRACK. The proposal was led on the EORC side by Ariane Droin and Hannes Taubenböck, together with strong partners from research, medicine, and public health:...
Wir freuen uns sehr, die erfolgreiche Einwerbung des BMFTR Drittmittelprojekts HABITRACK bekanntzugeben. Geleitet wurde der Antrag von EORC Seite aus von Ariane Droin und Hannes Taubenböck, gemeinsam mit starken Partnern aus Forschung, Medizin und öffentlichem...
Two days ago, our PostDoc Dr. Jakob Schwalb-Willmann visited the Institute for Geoinformatics at University of Münster to give a talk at IFGI’s GI Forum titled “Can animals be used to classify land use? Employing movement-tracked animals as environmental informants using deep learning”.
