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

Remote Sensing

Andreas Ibrom¹  Matthias Peichl²  Per Jönsson³  Lars Eklundh⁴  Jutta Holst⁴  Jonas Ardö⁴  Meelis Mölder⁴  Sofia Junttila⁴  Janne Rinne⁴  Maria Karamihalaki⁴  Hongxiao Jin⁴  Zhanzhang Cai⁴ 

[1] Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet 115, 2800 Lyngby, Denmark;Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Skogsmarksgränd, SE-901 83 Umeå, Sweden;Department of Materials Science and Applied Mathematics, Malmö University, SE-205 06 Malmö, Sweden;Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, SE-223 62 Lund, Sweden;

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

DOI  :  10.3390/rs13030469

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown