6 papers
From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps
Ghjulia Sialelli, Robin Young, Yuchang Jiang +9
Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by advances in machine learning (…
Towards an open registry of Earth observation instruments
David Montero, César Aybar, Miguel D. Mahecha +1
Earth observation (EO) is essential to understanding the Earth system, enabling the transformation of planetary properties into measurable variables that can be analysed, compared,…
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…
Transformers vs. Recurrent Models for Estimating Forest Gross Primary Production
David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6
Monitoring the spatiotemporal dynamics of forest CO uptake (Gross Primary Production, GPP), remains a central challenge in terrestrial ecosystem research. While Eddy Covariance…
OpenSR-SRGAN: A Flexible Super-Resolution Framework for Multispectral Earth Observation Data
Simon Donike, Cesar Aybar, Julio Contreras +1
We present OpenSR-SRGAN, an open and modular framework for single-image super-resolution in Earth Observation. The software provides a unified implementation of SRGAN-style models…
Video Compression for Spatiotemporal Earth System Data
Oscar J. Pellicer-Valero, Cesar Aybar, Gustau Camps Valls
Large-scale Earth system datasets, from high-resolution remote sensing imagery to spatiotemporal climate model outputs, exhibit characteristics analogous to those of standard video…