## 1 Introduction
In this research, we hypothesize that this approach, along with the information from high-frequency satellites, could be adequate for estimating \(GPP\) in Mediterranean grasslands. High-frequency satellites, such as Sentinel-2, have opened the door to the study of ecosystems with a high spatial and temporal resolution [28; 29]. Although extensive research exists about estimating GPP in grasslands with moderate-resolution sensors, such asMODIS [30; 31; 32], the estimation of \(GPP\) in this ecosystem using Sentinel-2 images is relatively new. In this sense, [PERSON] et al. [33] highlighted the potential of the Sentinel-2 satellite to monitor biophysical parameters in a dynamic subalpine grassland ecosystem. More recently, [PERSON] et al. [34] reviewed the status of phenological research using Sentinel-2 data in different ecosystems. They showed that Sentinel-2 data is useful for capturing the spatial and temporal variations in grasslands due to management practices and climate. Besides, [PERSON] et al. [35] studied the aboveground biomass of two pastures in central Oklahoma using Sentinel-1, Sentinel-2, and Landsat images, and they showed that the combination of these data improved biomass estimation to improve management in this ecosystem. Similarly, [PERSON] [36] developed the Dominant Species-Physiognomy-Ecological (DSPE) classification system for differentiating plant ecological communities using high-spatial-resolution Sentinel-2 images, demonstrating the effectiveness of Sentinel-2 in ecological studies at a regional scale. However, only a few works have estimated GPP using Sentinel-2 data in Mediterranean environments. [PERSON] et al. [37] evaluated the use of Sentinel-2 data to estimate the growing stock volume of a Mediterranean forest, obtaining better results than those obtained by Landsat imagery. [PERSON] et al. [38] achieved good estimations of GPP of Mediterranean grasslands with hyperspectral measurements, which were resampled to reproduce the spectral bands of both Sentinel-2 and Landsat 8. In addition, [PERSON] et al. [39] used Sentinel-2 and MODIS data for estimating Net Primary Production (NPP) at different scales of a holm oak Mediterranean forest, obtaining promising results. Recently, [PERSON] et al. [40] upscaled the GPP of a flux tower located in a Mediterranean wetland using Sentinel-2 data. They showed that their GPP model predictions improved those obtained from using the MODIS product. However, they used only one year, and further research is needed to estimate GPP through longer periods. In this sense, this study proposed using Sentinel-2 data to estimate the GPP of a Mediterranean grassland for three growing seasons. GPP derived from remote sensing data must be evaluated at the field scale using eddy covariance (EC) measurements from flux towers. EC technique has allowed quantifying more accurately the flux of CO2 between the atmosphere and ecosystems (Net Ecosystem exchange, \(NEE\)) and deriving \(GPP\) and Reco through different techniques at different spatial-temporal scales [41; 42; 43], as Equation (3) shows:  
\[NEE=Reco-GPP \tag{3}\]  
The overall objective of this research is to estimate an ecosystem light use efficiency GPP model for a Mediterranean grassland using Sentinel-2 NDVI and meteorological field information. The specific objectives are the following:  
1. To validate the remote sensing model with measurements from an EC flux tower in terms of quantity and seasonal and interannual dynamics. 2. To compare the model at different spatial and temporal resolutions using Sentinel-2 and MODIS data.