4 papers
Deep Learning Super Resolution for Satellite Cloud Mask Downscaling
Angelos Georgakis, Valentina Kanaki, Giorgos Giannopoulos +4
A vast amount of optical satellite data is being transmitted to Earth-based servers every day, and more than half of this data is affected by haze or clouds. Additionally, this dat…
HighFM: Towards a Foundation Model for Learning Representations from High-Frequency Earth Observation Data
Stella Girtsou, Konstantinos Alexis, Giorgos Giannopoulos +1
The increasing frequency and severity of climate related disasters have intensified the need for real time monitoring, early warning, and informed decision-making. Earth Observatio…
Global 3D Reconstruction of Clouds & Tropical Cyclones
Shirin Ermis, Cesar Aybar, Lilli Freischem +7
Accurate forecasting of tropical cyclones (TCs) remains challenging due to limited satellite observations probing TC structure and difficulties in resolving cloud properties involv…
3D Cloud reconstruction through geospatially-aware Masked Autoencoders
Stella Girtsou, Emiliano Diaz Salas-Porras, Lilli Freischem +7
Clouds play a key role in Earth's radiation balance with complex effects that introduce large uncertainties into climate models. Real-time 3D cloud data is essential for improving…