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| Titel |
Global GPP based on Plant Functional Types |
| VerfasserIn |
Frank Veroustraete, Manuela Balzarolo |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250137163
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| Publikation (Nr.) |
 EGU/EGU2016-18364.pdf |
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| Zusammenfassung |
| Vegetation variables like Gross Primary productivity (GPP) and the Normalized Difference
Vegetation Index (NDVI) are key variables in vegetation carbon exchange studies. Field
measurements of the NDVI are time consuming due to landscape heterogeneity across time.
Typically a sampling protocol adopted during field campaigns is based on the VALERI
protocol in that case toe estimate LAI. Field campaign GPP or NDVI measurements can be
scaled up to using in-situ FLUXNET radiation raster maps. Regression analysis can then be
applied to construct transfer functions for the determination of GPP raster maps raster
imagery from Normalized Difference Vegetation Index (NDVI) raster maps derived from
in-situ FLUXNET radiation raster maps. Subsequently, in the VALERI approach the
scaling up of raster maps is performed by aggregation of high resolution in-situ
FLUXNET radiation raster maps data into high resolution raster maps and subsequently
aggregating these to 1x1 km MODIS NDVI raster maps by calculating average NDVI
values for the low resolution data. The up-scaled 1x1 km pixels are then used to
validate the MODIS GPP and NVI products. Hence up scaling based on in-situ
FLUXNET radiation measurements are not a luxury for large and heterogeneous sites.
Therefore this paper tackles the problem of up scaling using in-situ FLUXNET radiation
measurements.
Key Words: FLUXNET, GPP, Plant Functional Types, Up-scaling |
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