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

Cai, Zhanzhang (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
Junttila, Sofia (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
Holst, Jutta (author)
Lund University,Lunds universitet,ICOS Sweden,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Institutionen för naturgeografi och ekosystemvetenskap,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science
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Jin, Hongxiao (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science,Technical University of Denmark
Ardö, Jonas (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
Ibrom, Andreas (author)
Technical University of Denmark
Peichl, Matthias (author)
Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Institutionen för skogens ekologi och skötsel,Department of Forest Ecology and Management,Swedish University of Agricultural Sciences, Umeå
Mölder, Meelis (author)
Lund University,Lunds universitet,ICOS Sweden,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Institutionen för naturgeografi och ekosystemvetenskap,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science
Jönsson, Per (author)
Malmö University,Malmö universitet,Institutionen för materialvetenskap och tillämpad matematik (MTM)
Rinne, Janne (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
Karamihalaki, Maria (author)
Lund University,Lunds universitet,Institutionen för naturgeografi och ekosystemvetenskap,Naturvetenskapliga fakulteten,Dept of Physical Geography and Ecosystem Science,Faculty of Science
Eklundh, Lars (author)
Lund University,Lunds universitet,MERGE: ModElling the Regional and Global Earth system,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Institutionen för naturgeografi och ekosystemvetenskap,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science
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 (creator_code:org_t)
 
2021-01-29
2021
English.
In: Remote Sensing. - : MDPI. - 2072-4292. ; 13:3
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Fjärranalysteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Remote Sensing (hsv//eng)

Keyword

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

Publication and Content Type

ref (subject category)
art (subject category)

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