# Assimilation of Earth Observation Data Over Cropland and Grassland Sites into a Simple GPP Model
## 2 Data
### MODIS NDVI, Reflectances and GPP  
As source of EO data we selected MODIS data as it provides a relatively long archive of observations (i.e., from year 2000) and a good compromise between spatial resolution (i.e., 250 m) and temporal resolution of acquisition (i.e., daily revisit). We retrieved NDVI from the MODIS MOD13Q1 and MYD13Q1 version 6 products using the Google Earth Engine. These are 250 m spatial resolution 16-day NDVI composite from Terra and Aqua satellites produced with an 8-day phase shift. Besides NDVI, the following information was retrieved for each observation: reflectances in the blue, red, NIR, and MIR bands, day of acquisition, sun-sensor-target geometry (SZA, Solar Zenith Angle; VZA, View Zenith Angle, RAA, Relative Azimuth Angle), and Vegetation Index (VI) quality and usefulness. Only reliable observations were retained from further processing, i.e., observations with VI reliability greater than two and VI usefulness greater than seven where excluded. MOD09A1 and MYD09A1 (surface reflectance 8-day composite at 500 m) were also acquired to determine the background contribution to canopy NDVI as explained in Section 3.2. In addition, we retrieved the MODIS GPP 8-day version 6 product (MOD17A2H) at 500 m spatial resolution. MODIS GPP 8-day was scaled to mean daily value (gC m\({}^{-2}\) d\({}^{-1}\)) over the 8-day period. We used the flux tower locations to extract the time series of MODIS data by selecting the pixel where the flux tower coordinates falls within.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable** & **Source** & **Main Specifications** & **Purpose** \\ \hline Global radiation, air temperature, precipitation, reference potential evapotranspiration & \begin{tabular}{c} Downscaled ECMWF \\ ERA-Interim, available \\ from MARSOP \\ repository 1 \\ \end{tabular} & Daily data, 25 km spatial resolution & Model input \\ \hline NDVI & MODIS2 & \begin{tabular}{c} MOD- and MYD-13Q1, \\ 16 day composites, 250 m \\ spatial resolution \\ \end{tabular} & Model re-calibration \\ \hline Surface reflectance & MODIS2 & \begin{tabular}{c} MOD- and MYD-09A, 8 \\ day composites, 500 m \\ spatial resolution \\ \end{tabular} & \begin{tabular}{c} Estimation of canopy \\ background reflectance \\ \end{tabular} \\ \hline GPP & Eddy flux tower 3 & Daily data & GPP validation \\ \hline GPP & MODIS2 & \
\begin{tabular}{c} MOD17A2H, 8 day \\ composites, 500 m \\ spatial resolution \\ \end{tabular} &
\begin{tabular}{c} GPP estimates \\ intercomparison \\ \end{tabular} \\ \hline \hline \end{tabular}  
* [[https://marswiki.jrc.ee.europa.eu/agri4](https://marswiki.jrc.ee.europa.eu/agri4) castwiki/index.php/Welcome_to_WikiMCYFS]([https://marswiki.jrc.ee.europa.eu/agri4](https://marswiki.jrc.ee.europa.eu/agri4) castwiki/index.php/Welcome_to_WikiMCYFS). 2 Data retrieved through the Google Earth Engine. 3 From European Flux Database Cluster and FLUXNET2015.  
\end{table}
Table 1: Data used in the analysis. ECMWF stands for European Centre for Medium-Range Weather Forecasts; MODIS: Moderate Resolution Imaging Spectroradiometer; NVDI: Normalized Difference Vegetation Index; GPP: gross primary production.