DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts
Abstract With climate extremes’ rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets...
Saved in:
| Main Authors: | Chaonan Ji, Tonio Fincke, Vitus Benson, Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Fabian Gans, Guido Kraemer, Francesco Martinuzzi, David Montero, Karin Mora, Oscar J. Pellicer-Valero, Claire Robin, Maximilian Söchting, Mélanie Weynants, Miguel D. Mahecha |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04447-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Interactive Earth system data cube visualization in Jupyter notebooks
by: Maximilian Söchting, et al.
Published: (2025-04-01) -
Calibration and uncertainty quantification for deep learning-based drought detection
by: Mengxue Zhang, et al.
Published: (2025-06-01) -
Out of the Cube: Augmented Rubik's Cube
by: Oriel Bergig, et al.
Published: (2011-01-01) -
Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection
by: J. Pérez-Aracil, et al.
Published: (2025-09-01) -
Large language models for causal hypothesis generation in science
by: Kai-Hendrik Cohrs, et al.
Published: (2025-01-01)