Estimation of Biomass and CO2 Fluxes Of Sunflower by Assimilating Hstr Data in a Simple Crop Model

Although croplands are affected by climate change and contribute to it, their carbon budgets remain little known because of the lack of tools allowing estimating it at a fine resolution. In this study a modeling approach is proposed, assimilating high spatial and temporal resolution (HSTR) remote sensing optical products in a semi-physical crop model called SAFY-CO
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to estimate crop production and the components of the carbon budget. The model correctly reproduces the green area index (GAI $) (\mathrm{R}^{2} =0.98$, rRMSE =8%), the biomass $(\mathrm{R}^{2} =0.95$, rRMSE =16%) and the components of the carbon budget (GPP: $\mathrm{R}^{2} =0.90$; RMSE =1.61 gC$.\mathrm{m}^{-2}. \mathrm{d}^{-1} ; \mathrm{R}_{eco} : \mathrm{R}^{2} =0.87$; RMSE $=0.81$ gC$.\mathrm{m}^{-2}. \mathrm{d}^{-1}$ gC$.\mathrm{m}^{-2}. \mathrm{d}^{-1}$; NEE: $\mathrm{R}^{2} =0.86$; RMSE =0.85 gC$.\mathrm{m}^{-2}. \mathrm{d}^{-1})$. This approach requires a few input parameters and no information about management practices which makes it suitable for large scale application and monitoring, reporting and verification (MRV) approaches.