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| Titel: |
Upscaling of gross ecosystem production to the landscape scale using multi-temporal Landsat images, eddy covariance measurements and a footprint model |
| Auteur: |
B. Chen Q. Ge D. Fu G. Liu G. Yu X. Sun S. Wang H. Wang |
| Verschenen in: |
Biogeosciences discussions |
| Paginering: | Jaargang 6 (2009) nr. 6 pagina's 11317-11345 |
| Jaar: |
2009 |
| Inhoud: |
In order to use the global available eddy-covariance (EC) flux dataset and remote sensing measurements to provide estimates of gross primary production (GPP) at landscape (10<sup>1–10<sup>2km<sup>2), regional (10<sup>3–10<sup>6km<sup>2) and global land surface scales, we developed a satellite-based GPP algorithm using Landsat data and an upscaling framework. The satellite-based GPP algorithm uses two improved vegetation indices (Enhanced Vegetation Index – EVI, Land Surface Water Index – LSWI). The upscalling framework involves flux footprint climatology modeling and data-model fusion. This approach was first applied to an evergreen coniferous stand in South China subtropical monsoon climatic zone. The EC measurements at Qian Yinzhou tower site (26° 44'48'' N, 115° 04'13'' E), which belongs to the Chinaflux network, and the Landsat images for this region in 2004 were used in this study. The seasonal dynamics of GPP predicted by the satellite-based algorithm agreed well with observed GPP in 2004 at this site. These results demonstrate the potential of combining of the satellite-based algorithm, flux footprint modeling and data-fusion, for scaling-up of GPP at the CO2 flux tower sites, a key component for the study of the carbon cycle at regional and global scales. |
| Uitgever: |
Copernicus GmbH (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 142 van 146 gevonden artikelen
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