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

Zhanzhang Cai,Janne Rinne,Matthias Peichl,Per Jönsson,Jonas Ardö,Lars Eklundh,Sofia Junttila,Maria Karamihalaki,Jutta Holst,Meelis Mölder,Hongxiao Jin,Andreas Ibrom

doi:10.3390/rs13030469

Abstract

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

Highlights

Atmospheric carbon dioxide (CO2 ) from anthropogenic emissions is one of the key drivers of climate change [1]
We examined the effect of the spatial resolution of daily two-band enhanced vegetation index (EVI2, 10m from Sentinel-2 MultiSpectral Instrument (MSI), 250m and 500m from Moderate Resolution Imaging Spectroradiometer (MODIS))
Sentinel-2 opens the possibility of very detailed gross primary productivity (GPP) estimation across the northern landscape, which is of benefit for climate mitigation and adaptation work

Summary

Introduction

Atmospheric carbon dioxide (CO2 ) from anthropogenic emissions is one of the key drivers of climate change [1]. The techniques used to quantify land–atmosphere carbon exchanges are essential for the understanding of the global carbon cycle [2]. Northern land ecosystems play an important role in the global carbon cycle due to the high amount of carbon stored in boreal ecosystems [3] and the increasing seasonal CO2 exchange [4]. Gross Primary Productivity (GPP) can be estimated [5]. These measurements lack the spatial coverage needed for the characterization of CO2 fluxes at larger regional extents (103 –106 km2 ), and to represent different age classes and species diversity [6]. An efficient way to estimate GPP across larger areas is to use observations from Earth observation satellites.

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Results

Discussion

Conclusion