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Modeling Winter Wheat Leaf Area Index and Canopy Water Content With Three Different Approaches Using Sentinel-2 Multispectral Instrument Data
Pan, Haizhu1,2; Chen, Zhongxin1,2; Ren, Jianqiang1,2; Li, He3; Wu, Shangrong1,2
2019-02-01
Source PublicationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
Volume12Issue:2Pages:482-492
Corresponding AuthorChen, Zhongxin(chenzhongxin@caas.cn)
AbstractLeaf area index (LAI) and canopy water content (CWC) are important variables for monitoring crop growth and drought, which can be estimated from remotely sensed data. The goal of this study was to evaluate the suitability of the Sentinel-2 multispectral instrument (S2 MSI) data for winter wheat LAI and CWC estimation with three different inversion approaches in the main farming region in North China. During the winter wheat key growth stages in 2017, 22 fields, each with five independent samples, the total number of sample plot is 110, were designed for experimental measurements. In this study, the LAI and CWC were retrieved separately using empirical models through different spectral indices, neural network (NN) algorithms, and lookup table (LUT) methods based on the PROSAIL model. The accuracies of the estimated LAI and CWC were assessed through in situ measurements. The results show that the LUT inversion approach was more suitable for LAI and CWC estimation than the spectral index-based empirical model or the NN algorithm. With the LUT approach, LAI was obtained with a root mean square error (RMSE) of 0.43m(2).m(-2) and a relative RMSE (RRMSE) of 11% using seven S2MSI bands, and CWC was obtained with an RMSE of 0.41 kg.m(-2), and an RRMSE of 32% using five S2 MSI bands. In all the three methods, S2MSI was sensitive to LAI variation and able to reach higher accuracies when red edge bands were used. However, CWC inversion was still a challenge using S2 MSI data.
KeywordCanopy water content (CWC) leaf area index (LAI) lookup table (LUT) neural network (NN) North China vegetation indices Sentinel-2 winter wheat
DOI10.1109/JSTARS.2018.2855564
WOS KeywordHYPERSPECTRAL VEGETATION INDEXES ; FUEL MOISTURE-CONTENT ; RED-EDGE BANDS ; BIOPHYSICAL VARIABLES ; REMOTE ESTIMATION ; GREEN LAI ; CHLOROPHYLL ; CROP ; REFLECTANCE ; INVERSION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[NSFC-6166113606] ; National Natural Science Foundation of China[41471364] ; China Ministry of Agriculture Introduction of International Advanced Agricultural Science and Technology Program (948 Program) project[2016-X38] ; China Scholar Council[201703250080]
Funding OrganizationNational Natural Science Foundation of China ; China Ministry of Agriculture Introduction of International Advanced Agricultural Science and Technology Program (948 Program) project ; China Scholar Council
WOS Research AreaEngineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEngineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000460663600009
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49208
Collection中国科学院地理科学与资源研究所
Corresponding AuthorChen, Zhongxin
Affiliation1.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China
2.Minist Agr, Key Lab Agr Remote Sensing, Beijing 100081, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Pan, Haizhu,Chen, Zhongxin,Ren, Jianqiang,et al. Modeling Winter Wheat Leaf Area Index and Canopy Water Content With Three Different Approaches Using Sentinel-2 Multispectral Instrument Data[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2019,12(2):482-492.
APA Pan, Haizhu,Chen, Zhongxin,Ren, Jianqiang,Li, He,&Wu, Shangrong.(2019).Modeling Winter Wheat Leaf Area Index and Canopy Water Content With Three Different Approaches Using Sentinel-2 Multispectral Instrument Data.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,12(2),482-492.
MLA Pan, Haizhu,et al."Modeling Winter Wheat Leaf Area Index and Canopy Water Content With Three Different Approaches Using Sentinel-2 Multispectral Instrument Data".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 12.2(2019):482-492.
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