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| Titel |
Assessing forest productivity (NPP/GPP) estimates from remote sensing, flux measurement and field observations |
| VerfasserIn |
Hrvoje Marjanović, Mislav Anic, Maša Zorana Ostrogović Sever, Anikó Kern |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250111547
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| Publikation (Nr.) |
 EGU/EGU2015-11678.pdf |
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| Zusammenfassung |
| Monitoring forest productivity and understanding effects of key environmental drivers becomes essential for forest management. This is a challenging task, particularly due to great costs related to it. In our work we compared the available annual productivity (GPP and NPP) assessments from the MODIS sensor with assessments from: a) eddy covariance and soil respiration measurements; and b) bi-weekly field measurements of increment of 640 trees in 24 plots set in a 100m x 100m grid. The research is conducted in lowland forest dominated by pedunculate oak. The comparison was made on a five year dataset of measurements, spanning from 2008 to 2012.
The research provides the first evaluation on the quality of MODIS GPP and NPP estimates for Central-European lowland forests. Results indicate that GPP/NPP from MODIS MOD17 dataset (version 55, Numerical Terradynamic Simulation Group, University of Montana) are in good agreement with the NPP/GPP estimates from field measurements. |
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