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Research article - Peer-reviewed, 2021

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

Cai, Zhanzhang; Junttila, Sofia; Holst, Jutta; Jin, Hongxiao; Ardo, Jonas; Ibrom, Andreas; Peichl, Matthias; Molder, Meelis; Jonsson, Per; Rinne, Janne; Karamihalaki, Maria; Eklundh, Lars


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 (R-2 = 0.84 for Sentinel-2; R-2 = 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.


gross primary productivity; Sentinel-2 MSI; EVI2; MODIS; Nordic region

Published in

Remote Sensing
2021, volume: 13, number: 3, article number: 469
Publisher: MDPI

Authors' information

Cai, Zhanzhang
Lund University
Junttila, Sofia
Lund University
Holst, Jutta
Lund University
Jin, Hongxiao
Lund University
Ardo, Jonas
Lund University
Ibrom, Andreas
Technical University of Denmark
Swedish University of Agricultural Sciences, Department of Forest Ecology and Management
Molder, Meelis
Lund University
Jonsson, Per
Malmo University
Rinne, Janne
Lund University
Karamihalaki, Maria
Lund University
Eklundh, Lars
Lund University

UKÄ Subject classification

Remote Sensing

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