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Towards operational remote sensing of forest carbon balance across Northern Europe

Author:
  • Pontus Olofsson
  • Fredrik Lagergren
  • Anders Lindroth
  • Johan Lindström
  • Leif Klemedtsson
  • Lars Eklundh
Publishing year: 2007
Language: English
Pages: 3143-3193
Publication/Series: Biogeosciences Discussions
Volume: 4
Issue: 5
Document type: Journal article
Publisher: EGU / Copernican Publications

Abstract english

Onthly averages of ecosystem respiration (ER), gross primary production (GPP) and net ecosystem exchange (NEE) over Scandinavian forest sites were estimated using regression models driven by air temperature (AT), absorbed photosynthetically active radiation (APAR) and vegetation indices. The models were constructed and evaluated using satellite data from Terra/MODIS and measured data collected at seven flux tower sites in northern Europe. Data used for model construction was excluded from the evaluation. Relationships between ground measured variables and the independent variables were investigated.



It was found that the enhanced vegetation index (EVI) at 250 m resolution was highly noisy for the coniferous sites, and hence, 1 km EVI was used for the analysis. Linear relationships between EVI and the biophysical variables were found for both coniferous and deciduous data: correlation coefficients ranged from 0.91 to 0.79, and 0.85 to 0.67, respectively. Due to saturation, there were no linear relationships between normalized difference vegetation index (NDVI) and the ground measured parameters found at any site. APAR correlated better with the parameters in question than the vegetation indices. Modeled GPP and ER were in good agreement with measured values, with more than 90% of the variation in measured GPP and ER being explained by the coniferous models. The site-specific respiration rate at 10°C (R10) was needed for describing the ER variation between sites. Even though monthly NEE was modeled with less accuracy than GPP, 61% and 75% (dec. and con., respectively) of the variation in the measured time series was explained by the model. These results are important for moving towards operational remote sensing of forest carbon balance across Northern Europe.

Keywords

  • Physical Geography
  • Probability Theory and Statistics
  • NPP
  • MODIS
  • carbon balance
  • respiration
  • NEE
  • remote sensing
  • NDVI

Other

Published
  • remote sensing-lup-obsolete
  • ISSN: 1810-6277
E-mail: lars [dot] eklundh [at] nateko [dot] lu [dot] se

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Dept of Physical Geography and Ecosystem Science

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Dept of Physical Geography and Ecosystem Science

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Department of Physical Geography and Ecosystem Science
Lund University
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