Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Default user image.

Zhanzhang Cai

Postdoc

Default user image.

Modelling daily gross primary productivity with sentinel-2 data in the nordic region–comparison with data from modis

Författare

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

Summary, in English

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.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap
  • ICOS Sweden
  • MERGE: ModElling the Regional and Global Earth system

Publiceringsår

2021

Språk

Engelska

Publikation/Tidskrift/Serie

Remote Sensing

Volym

13

Issue

3

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Physical Geography

Nyckelord

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

Aktiv

Published

Projekt

  • Upscaling carbon fluxes to a landscape

ISBN/ISSN/Övrigt

  • ISSN: 2072-4292