Coupling Remote Sensing with Spatial 3-PG Model for Gross Primary Productivity Estimation in Deciduous Broadleaf Forest: Hokkaido, Japan
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概要
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Gross primary productivity (GPP) is total amount of carbon absorption by canopy. This indicator can help us to understand the carbon cycle process. This study proposed the method to estimate GPP by integrating remotely sensed data to the ecological modelling, focused on 3-PG model. First, the parameter in 3-PG model is done the parameterization for deciduous broadleaf forest based on in situ measurement from flux tower. Then, MODIS 10 days composite data is calculated in terms of vegetation index to compare with LAI data. Regarding on LAI-VI relationship, 3-PG model is extended to Spatial 3-PG model, then GPP is estimated. The result shows that estimated GPP has good agreement to observed GPP as well. [This abstract is not included in the PDF]
著者
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TAKEUCHI Wataru
Institute of Industrial Science, University of Tokyo
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Takeuchi Wataru
Institute Of Industrial Science University Of Tokyo
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Endo Takahiro
Institute Of Industrial Science The University Of Tokyo
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POTITHEP Supannika
Japan Agency for Marine-Earth Science and Technology
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SAWADA Haruo
Institute of Industrial Science, The University of Tokyo
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YASUOKA Yoshifumi
National Institute for Environmental Studies
関連論文
- Coupling Remote Sensing with Spatial 3-PG Model for Gross Primary Productivity Estimation in Deciduous Broadleaf Forest: Hokkaido, Japan
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