Projects

Artificial Intelligence (AI) is already part of our lives and is extensively entering the space sector to offer value-added Earth Observation (EO) products and services. Copernicus data and other georeferenced data sources are often highly heterogeneous, distributed, and semantically fragmented. Large...

A climate resilient society requires reliable monitoring and forecasting information of the climate trends, patterns anddisturbances, both at global and regional scales. Through CONsistent representation of temporal variations of boundary Forcings in reanalysES and Seasonal forecasts, CONFESS will contribute to the emerging societal need for an enhanced Copernicus Climate...

The main scope of the project is to empower the potential of EO Systems by creating an innovative commercial information delivery to optimize sustainable vine cultivation via decision support systems (DSS) on phenology, irrigation, fertilizer, disease and business operations management. Satellites imagery will be combined with other data sources such as in-field measurements, models and best...

Roughly 30% of Nationally Determined Contributions (NDCs) under the Paris Agreement (PA) include land-based mitigation measures, however, there significant uncertainties remain regarding their effectiveness for delivering negative emissions. Aside from the expected inability of all current NDCs to deliver on the goal to below 2 oC goal, the uncertainty caused by this...

At the time of writing of this proposal, most European countries have imposed lockdowns to combat the spread of the COVID-19 pandemic, which have forced many industries, businesses and transport networks to either close down or drastically reduce their activity. Such economic interruption, which is unprecedented in many ways, is resulting in a sudden drop of atmospheric...

The DeepLIM study has two technical goals:

• understanding, developing and exploiting the use of Generative Artificial Intelligence to improve and augment datasets acquired via observation campaigns, or generated by computationally intensive models.
• improving the state of the art models that are in use to perform Inversion Modelling with the use of Deep...