Lars Eklundh
Professor
Towards operational remote sensing of forest carbon balance across Northern Europe
Författare
Summary, in English
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.
Avdelning/ar
- Dept of Physical Geography and Ecosystem Science
- Matematisk statistik
Publiceringsår
2007
Språk
Engelska
Sidor
3143-3193
Publikation/Tidskrift/Serie
Biogeosciences Discussions
Volym
4
Avvikelse
5
Dokumenttyp
Artikel i vetenskaplig tidskrift
Förlag
European Geosciences Union
Ämne
- Physical Geography
- Probability Theory and Statistics
Nyckelord
- NPP
- MODIS
- carbon balance
- respiration
- NEE
- remote sensing
- NDVI
Aktiv
Published
ISBN/ISSN/Övrigt
- ISSN: 1810-6277