WIPM OpenIR
Analyzing the Effect of Fluorescence Characteristics on Leaf Nitrogen Concentration Estimation
Yang, Jian1; Song, Shalei2; Du, Lin1; Shi, Shuo3,4; Gong, Wei3,4; Sun, Jia3; Chen, Biwu3
2018-09-01
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume10Issue:9Pages:15
AbstractLeaf nitrogen concentration (LNC) is a significant indicator of crops growth status, which is related to crop yield and photosynthetic efficiency. Laser-induced fluorescence is a promising technology for LNC estimation and has been widely used in remote sensing. The accuracy of LNC monitoring relies greatly on the selection of fluorescence characteristics and the number of fluorescence characteristics. It would be useful to analyze the performance of fluorescence intensity and ratio characteristics at different wavelengths for LNC estimation. In this study, the fluorescence spectra of paddy rice excited by different excitation light wavelengths (355 nm, 460 nm, and 556 nm) were acquired. The performance of the fluorescence intensity and fluorescence ratio of each band were analyzed in detail based on back-propagation neural network (BPNN) for LNC estimation. At 355 nm and 460 nm excitation wavelengths, the fluorescence characteristics related to LNC were mainly located in the far-red region, and at 556 nm excitation wavelength, the red region being an optimal band. Additionally, the effect of the number of fluorescence characteristics on the accuracy of LNC estimation was analyzed by using principal component analysis combined with BPNN. Results demonstrate that at least two fluorescence spectral features should be selected in the red and far-red regions to estimate LNC and efficiently improve the accuracy of LNC estimation.
Keywordlaser-induced fluorescence leaf nitrogen concentration back-propagation neural network principal component analysis fluorescence characteristics
Funding OrganizationNational Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)
DOI10.3390/rs10091402
WOS KeywordLASER-INDUCED FLUORESCENCE ; CHLOROPHYLL-A FLUORESCENCE ; HYPERSPECTRAL REFLECTANCE ; NEURAL-NETWORK ; GREEN PLANTS ; PADDY RICE ; VEGETATION ; WHEAT ; IDENTIFICATION ; DEFICIENCY
Language英语
Funding ProjectNational Key Research and Development Program of China[2018YFB0504500] ; National Natural Science Foundation[41571370] ; Natural Science Foundation of Hubei Province[2018CFB272] ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University[17R05] ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)[CUG170661]
Funding OrganizationNational Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation ; National Natural Science Foundation ; Natural Science Foundation of Hubei Province ; Natural Science Foundation of Hubei Province ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan)
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000449993800082
PublisherMDPI
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.wipm.ac.cn/handle/112942/13391
Collection中国科学院武汉物理与数学研究所
Corresponding AuthorSong, Shalei
Affiliation1.China Univ Geosci, Fac Informat Engn, Wuhan 430074, Hubei, Peoples R China
2.Chinese Acad Sci, Wuhan Inst Phys & Math, Wuhan 430071, Hubei, Peoples R China
3.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China
4.Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Hubei, Peoples R China
Recommended Citation
GB/T 7714
Yang, Jian,Song, Shalei,Du, Lin,et al. Analyzing the Effect of Fluorescence Characteristics on Leaf Nitrogen Concentration Estimation[J]. REMOTE SENSING,2018,10(9):15.
APA Yang, Jian.,Song, Shalei.,Du, Lin.,Shi, Shuo.,Gong, Wei.,...&Chen, Biwu.(2018).Analyzing the Effect of Fluorescence Characteristics on Leaf Nitrogen Concentration Estimation.REMOTE SENSING,10(9),15.
MLA Yang, Jian,et al."Analyzing the Effect of Fluorescence Characteristics on Leaf Nitrogen Concentration Estimation".REMOTE SENSING 10.9(2018):15.
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