28 citations · 48 across the 9 of their papers we have counts for
11 papers
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation
Carmen Oliver Huidobro, Mikolaj Czerkawski, Kevin Monsalvez-Pozo +3
Pretraining generalist Earth observation foundation models requires data that combine several sensors, varied temporal sampling and, increasingly, text, yet open datasets rarely pr…
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,…
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…
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…
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…
Earth System Data Cubes: Avenues for advancing Earth system research
David Montero, Guido Kraemer, Anca Anghelea +15
Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spa…
Facilitating Advanced Sentinel-2 Analysis Through a Simplified Computation of Nadir BRDF Adjusted Reflectance
David Montero, Miguel D. Mahecha, César Aybar +2
The Sentinel-2 (S2) mission from the European Space Agency's Copernicus program provides essential data for Earth surface analysis. Its Level-2A products deliver high-to-medium res…
On-Demand Earth System Data Cubes
David Montero, César Aybar, Chaonan Ji +4
Advancements in Earth system science have seen a surge in diverse datasets. Earth System Data Cubes (ESDCs) have been introduced to efficiently handle this influx of high-dimension…
Recurrent Neural Networks for Modelling Gross Primary Production
David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6
Accurate quantification of Gross Primary Production (GPP) is crucial for understanding terrestrial carbon dynamics. It represents the largest atmosphere-to-land CO flux, especi…