Global carbon flux dataset generated by fusing remote sensing and multiple flux networks observation
Abstract We developed a global carbon flux dataset, GloFlux, using a machine learning model that integrates in situ observations from FLUXNET, AmeriFlux, ICOS, JapanFlux2024, and HBRFlux with satellite remote sensing and meteorological data. The dataset covers 2000–2023, has a 0.1∘ × 0. 1∘ spatial r...
Saved in:
| Main Authors: | Qiwang Yuan, Xufeng Wang, Tao Che, Jun Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05672-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Progress and challenges in remotely sensed terrestrial carbon fluxes
by: Tao Wang, et al.
Published: (2025-01-01) -
Remote sensing and ecosystem modeling to simulate terrestrial carbon fluxes
by: Sergio Sánchez-Ruiz
Published: (2019-06-01) -
Generating Spatially Robust Carbon Budgets From Flux Tower Observations
by: Anne Griebel, et al.
Published: (2020-02-01) -
The effects of teleconnections on carbon fluxes of global terrestrial ecosystems
by: Zaichun Zhu, et al.
Published: (2017-04-01) -
Validation of Remotely Sensed Evapotranspiration Products Using Optical–Microwave Scintillometer Flux Measurements Over the Heterogeneous Surfaces
by: Zhiguo Ren, et al.
Published: (2025-01-01)