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Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China
Wei, Jin1,2,3; Tang, Xuguang1,2,3,4; Gu, Qing1,2,3; Wang, Min1,2,3; Ma, Mingguo1,2,3; Han, Xujun1,2,3
2019-07-02
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume11Issue:14Pages:14
Corresponding AuthorTang, Xuguang(xgtang@swu.edu.cn)
AbstractThe remote sensing of solar-induced chlorophyll fluorescence (SIF) has attracted considerable attention as a new monitor of vegetation photosynthesis. Previous studies have revealed the close correlation between SIF and terrestrial gross primary productivity (GPP), and have used SIF to estimate vegetation GPP. This study investigated the relationship between the Orbiting Carbon Observatory-2 (OCO-2) SIF products at two retrieval bands (SIF757, SIF771) and the autumn crop production in China during the summer of 2015 on different timescales. Subsequently, we evaluated the performance to estimate the autumn crop production of 2016 by using the optimal model developed in 2015. In addition, the OCO-2 SIF was compared with the moderate resolution imaging spectroradiometer (MODIS) vegetation indices (VIs) (normalized difference vegetation index, NDVI; enhanced vegetation index, EVI) for predicting the crop production. All the remotely sensed products exhibited the strongest correlation with autumn crop production in July. The OCO-2 SIF757 estimated autumn crop production best (R-2 = 0.678, p < 0.01; RMSE = 748.901 ten kilotons; MAE = 567.629 ten kilotons). SIF monitored the crop dynamics better than VIs, although the performances of VIs were similar to SIF. The estimation accuracy was limited by the spatial resolution and discreteness of the OCO-2 SIF products. Our findings demonstrate that SIF is a feasible approach for the crop production estimation and is not inferior to VIs, and suggest that accurate autumn crop production forecasts while using the SIF-based model can be obtained one to two months before the harvest. Furthermore, the proposed method can be widely applied with the development of satellite-based SIF observation technology.
Keywordsolar-induced chlorophyll fluorescence OCO-2 EVI NDVI crop production
DOI10.3390/rs11141715
WOS KeywordSENSED VEGETATION INDEXES ; GROSS PRIMARY PRODUCTION ; USE EFFICIENCY ; YIELD PREDICTION ; PLANT STRESS ; PHOTOSYNTHESIS ; RETRIEVAL ; CORN ; LIMITATIONS ; RESOLUTION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41771361] ; National Natural Science Foundation of China[41771453] ; National Natural Science Foundation of China[41830648] ; Chongqing Basic and Frontier Research Program[cstc2018jcyjAX0056] ; Southwest University Research Funding[SWU117035]
Funding OrganizationNational Natural Science Foundation of China ; Chongqing Basic and Frontier Research Program ; Southwest University Research Funding
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000480527800085
PublisherMDPI
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/68790
Collection中国科学院地理科学与资源研究所
Corresponding AuthorTang, Xuguang
Affiliation1.Southwest Univ, State Cultivat Base Ecoagr Southwest Mt Land, Chongqing 400715, Peoples R China
2.Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China
3.Southwest Univ, Sch Geog Sci, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Chongqing 400715, Peoples R China
4.Chinese Acad Sci, Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Wei, Jin,Tang, Xuguang,Gu, Qing,et al. Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China[J]. REMOTE SENSING,2019,11(14):14.
APA Wei, Jin,Tang, Xuguang,Gu, Qing,Wang, Min,Ma, Mingguo,&Han, Xujun.(2019).Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China.REMOTE SENSING,11(14),14.
MLA Wei, Jin,et al."Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China".REMOTE SENSING 11.14(2019):14.
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