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

Supplement

https://doi.org/10.5194/gmd-17-997-2024-supplement

Data sets

AgriCarbon-EO Winter wheat Net Ecosystem Exchange and Biomass over South-west France at 10 m resolution Taeken Wijmer et al. https://doi.org/10.5281/zenodo.7534280

Registre Parcellaire Graphique – 2017 ASP https://doi.org/10.34724/CASD.425.3139.V2

Registre Parcellaire Graphique – 2018 ASP https://doi.org/10.34724/CASD.425.3140.V1

egistre Parcellaire Graphique – 2019 ASP https://doi.org/10.34724/CASD.425.3709.V1

Model code and software

jgomezdans/prosail: Pip package bug fix release (2.0.3) Luis Mario Domenzain et al. https://doi.org/10.5281/zenodo.2574925

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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.
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