Validation of MODIS-GPP product at 10 flux sites in northern China

被引:71
作者
Wang, Xufeng [1 ,2 ]
Ma, Mingguo [1 ]
Li, Xin [1 ]
Song, Yi [1 ,2 ]
Tan, Junlei [1 ]
Huang, Guanghui [1 ]
Zhang, Zhihui [1 ,2 ]
Zhao, Tianbao [3 ]
Feng, Jinming [3 ]
Ma, Zhuguo [3 ]
Wei, Wei [4 ]
Bai, Yanfen [1 ,2 ]
机构
[1] Chinese Acad Sci, Cold & Arid Reg Remote Sensing Observat Syst Expt, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China
[2] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys, Key Lab Reg Climate Environm Res Temperate E Asia, Beijing 100049, Peoples R China
[4] NW Normal Univ, Coll Geog & Environm Sci, Lanzhou 730070, Peoples R China
基金
中国国家自然科学基金;
关键词
GROSS PRIMARY PRODUCTION; TERRESTRIAL GROSS; ECOSYSTEM; EXCHANGE; CROPLAND; SUPPORT;
D O I
10.1080/01431161.2012.715774
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Gross primary production (GPP) is an important variable in studies of the carbon cycle and climate change. The Moderate Resolution Imaging Spectroradiometer (MODIS)-GPP product (MOD17) provides global GPP data for terrestrial ecosystems; however, it is not well validated in China. In this study, an eddy covariance (EC) system observed GPP at 10 sites in northern China and was used to validate MOD17. The results indicated that MOD17 presents a strong bias in the study region due to the meteorological data, MODIS FPAR (fraction of absorbed photosynthetically active radiation) (MOD15), and the model parameters in the MODIS-GPP algorithm, Biome Parameters Look Up Table (BPLUT). Maximum light-use efficiency (epsilon(0)) had the strongest impact on the predicted GPP of the MODIS-GPP algorithm. After using the inputs observed in situ and improving parameters in the MODIS-GPP algorithm, the model could explain 85% of the EC-observed GPP of the sites, whereas the MODIS-GPP algorithm without in situ inputs and parameters only explained 26% of EC-observed GPP.
引用
收藏
页码:587 / 599
页数:13
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