IGSNRR OpenIR
Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images
Xin, Fengfei1; Xiao, Xiangming1,2; Zhao, Bin1; Miyata, Akira3; Baldocchi, Dennis4; Knox, Sara4; Kang, Minseok5; Shim, Kyo-moon6; Min, Sunghyun6; Chen, Bangqian1,7; Li, Xiangping1; Wang, Jie2,8; Dong, Jinwei2; Biradar, Chandrashekhar9
2017-03-01
Source PublicationREMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
Volume190Pages:42-55
Corresponding AuthorXiao, Xiangming(xiangming.xiao@ou.edu)
AbstractAccurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem exchange (NEE) of CO2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPP(Ec)) and ecosystem respiration. In this study, we first used the GPP(Ec) data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPP(Ec), which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPP(VPM)). The 14 site-years of simulations show that the seasonal dynamics of GPP(VPM) successfully tracked the seasonal dynamics of GPPEc (R-2 > 0.88 or higher). The cross-site comparison also shows that GPP(VPM) agreed reasonably well with the variations of GPP(Ec) across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world. (C) 2016 Elsevier Inc. All rights reserved.
KeywordMulti-site CO2 fluxes Vegetation Photosynthesis Model Chlorophyll Light use efficiency
DOI10.1016/j.rse.2016.11.025
WOS KeywordLIGHT-USE-EFFICIENCY ; EVERGREEN NEEDLELEAF FOREST ; DECIDUOUS BROADLEAF FOREST ; ECOSYSTEM CARBON EXCHANGE ; NET PRIMARY PRODUCTION ; WHEAT ROTATION SYSTEM ; CLIMATE DATA ; SEASONAL-VARIATION ; INNER-MONGOLIA ; TIME-SERIES
Indexed BySCI
Language英语
Funding ProjectNASA[NNG05GH80G] ; NASA[NNX11AJ35G] ; NASA[NNX010AE103G] ; NIH NIAID[1R01A1101028-01A1] ; International Center for Agriculture in Dry Areas (ICARDA) ; California Department of Water Resources[4600008849] ; National Science Foundation[EF-1241960] ; United States Department of Agriculture (NIFA grant)[2011-67003-30371] ; United States Department of Energy[7079856] ; Korea RDA Research program[PJ122P301] ; Korea Meteorological Administration Weather Information Service Engine (WISE) project[KM1PA-2012-0001]
Funding OrganizationNASA ; NIH NIAID ; International Center for Agriculture in Dry Areas (ICARDA) ; California Department of Water Resources ; National Science Foundation ; United States Department of Agriculture (NIFA grant) ; United States Department of Energy ; Korea RDA Research program ; Korea Meteorological Administration Weather Information Service Engine (WISE) project
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000394399300004
PublisherELSEVIER SCIENCE INC
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64850
Collection中国科学院地理科学与资源研究所
Corresponding AuthorXiao, Xiangming
Affiliation1.Fudan Univ, Inst Biodivers Sci, Key Lab Biodivers Sci & Ecol Engn, Minist Educ, Shanghai 200433, Peoples R China
2.Univ Oklahoma, Ctr Spatial Anal, Dept Microbiol & Plant Biol, Norman, OK 73019 USA
3.NARO, Inst Agroenvironm Sci, Div Climate Change, Tsukuba, Ibaraki 3058604, Japan
4.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA
5.Natl Ctr Agro Meteorol, Seoul 08826, South Korea
6.Rural Dev Adm, Natl Inst Agr Sci, Wonju 55365, South Korea
7.CATAS, RRI, Haikou 571737, Hainan Province, Peoples R China
8.Chinese Acad Sci, Inst Geog Sci & Nat Resource Res, Beijing 100101, Peoples R China
9.Int Ctr Agr Res Dry Areas, Amman 11195, Jordan
Recommended Citation
GB/T 7714
Xin, Fengfei,Xiao, Xiangming,Zhao, Bin,et al. Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images[J]. REMOTE SENSING OF ENVIRONMENT,2017,190:42-55.
APA Xin, Fengfei.,Xiao, Xiangming.,Zhao, Bin.,Miyata, Akira.,Baldocchi, Dennis.,...&Biradar, Chandrashekhar.(2017).Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images.REMOTE SENSING OF ENVIRONMENT,190,42-55.
MLA Xin, Fengfei,et al."Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images".REMOTE SENSING OF ENVIRONMENT 190(2017):42-55.
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