article Agroclim: FAIR Workflows for the Crop Wild Relatives Digital Twin
Providing a FAIR-enabled digital twin for crop wild relatives, the project empowers researchers to identify resilient plant traits, addressing climate challenges and advancing sustainable agriculture.
Addressing the challenge of cyanobacterial blooms, SMHI integrates AI with Sentinel-3 satellite data to develop early warning systems for the Baltic Sea.
Architect a comprehensive and precise analysis based on the <a href="https://destination-earth.eu/glossary/destine-data/">DestinE Data</a> Lake to inform conservation efforts of the Danube Delta, one of Europe’s most biodiverse regions
Developing a modeling framework to support the monitoring of the pollutants in large urban areas and produce short-term forecasts for mitigating the health risks.
Providing a scalable machine-learning solution, the project enhances electricity demand prediction to support resilient and sustainable energy networks in a changing climate.