Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 3
Articles | Volume 17, issue 3
https://doi.org/10.5194/gmd-17-997-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-997-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 3
Model description paper
 | 
07 Feb 2024
Model description paper |  | 07 Feb 2024

AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach

Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia

Viewed

Total article views: 2,784 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,103 609 72 2,784 54 40 68
  • HTML: 2,103
  • PDF: 609
  • XML: 72
  • Total: 2,784
  • Supplement: 54
  • BibTeX: 40
  • EndNote: 68
Views and downloads (calculated since 22 Feb 2023)
Cumulative views and downloads (calculated since 22 Feb 2023)

Viewed (geographical distribution)

Total article views: 2,784 (including HTML, PDF, and XML) Thereof 2,655 with geography defined and 129 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Nov 2024
Download
Short summary
Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Read more