Modelling Daily Gross Primary Productivity with Sentinel-2 Data in the Nordic Region–Comparison with Data from MODIS

The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing variation in a heterogeneous landscapes. This study investigates potential 10 m reflectance from Multispectral Instrument to improve accuracy GPP across Nordic vegetation types, compared with 250 and 500 Moderate Resolution Imaging Spectroradiometer (MODIS). We applied linear regression models inputs two-band enhanced index (EVI2) derived MODIS reflectance, respectively, together various environmental drivers estimate daily eight eddy covariance (EC) flux tower sites. Compared EC measurements, accuracies modelled were generally high (R2 = 0.84 for Sentinel-2; R2 0.83 MODIS), differences between minimal. demonstrates general consistency estimates based on two satellite sensor systems regional scale. On other hand, model did not using higher spatial-resolution data. More analyses different formulations, more tests remotely sensed indices biophysical parameters, wider range geographical locations times will be required achieve improved estimations