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20242026
most citedEarth System Data Cubes: Avenues for advancing Earth system research

28 citations · 52 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.LG2024★ 1 cited

Explainable Earth Surface Forecasting under Extreme Events

Oscar J. Pellicer-Valero, Miguel-Ángel Fernández-Torres, Chaonan Ji +2

With climate change-related extreme events on the rise, high dimensional Earth observation data presents a unique opportunity for forecasting and understanding impacts on ecosystem…

cs.CV2024★ 28 cited

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…

math.DS2024★ 1 cited

Nonlinear spectral analysis extracts harmonics from land-atmosphere fluxes

Leonard Schulz, Jürgen Vollmer, Miguel D. Mahecha +1

Understanding the dynamics of the land-atmosphere exchange of CO is key to advance our predictive capacities of the coupled climate-carbon feedback system. In essence, the net…

cs.LG2024★ 2 cited

DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes

Chaonan Ji, Tonio Fincke, Vitus Benson +12

With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show prom…

cs.CV2024★ 5 cited

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…

cs.DB2024★ 5 cited

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…

cs.LG2024★ 10 cited

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…