Modelling Gross Primary Production of a Mediterranean grassland using Sentinel-2 NDVI and meteorological field information 

Mediterranean grasslands are essential for the development of rural areas in Mediterranean countries since they provide different ecosystem, social and economic services. Specifically, in Spain, pastures occupy more than 55% of the Spanish surface. The Gross Primary Production (GPP) of this ecosystem is subjected to a natural large spatial and temporal variability due to the influence of the Mediterranean climate. Remote sensing is accepted as the most powerful tool to study grasslands at different spatial and temporal scales. High frequency satellite data, such as Sentinel-2, offer new possibilities to study grasslands with high spatial (10 m) and temporal resolution (5 days). Hence, the overall objective of this research is to estimate GPP models for a Mediterranean grassland in central Spain using Sentinel-2 Normalized Difference Vegetation Index (NDVI), complemented with meteorological information at the field scale from January 2018 to August 2020. The GPP models are Light Use Efficiency models and will be validated by the GPP obtained from an eddy-covariance flux tower located in the study site, which belongs to the regional Guadarrama Meteorological Network (GUMNET). The results shows that the footprint estimation of the flux tower is influenced by mesoscale thermally-driven flows (mountain breezes) due to the presence of the Guadarrama Mountains, located quite close to the station. In addition, pasture phenology is linked to the dynamics of Soil Water Content (SWC), being water the main limiting factor during the growing cycle while temperature is only a limiting factor during winter. Thus, the inclusion of the SWC and minimum temperature in the model provides a better adjustment of the model. With this work we show how the estimated models are adequate to monitor the GPP of this Mediterranean grassland and we present the advantages and limitations found.