[Application of ANFIS in in-situ measured hyperspectral data for vegetation chlorophyll content estimation].
Identifieur interne : 003046 ( Main/Exploration ); précédent : 003045; suivant : 003047[Application of ANFIS in in-situ measured hyperspectral data for vegetation chlorophyll content estimation].
Auteurs : Fu-Qi Yao [République populaire de Chine] ; Zhen-Hua Zhang ; Run-Ya Yang ; Jin-Wei Sun ; Hai-Jiang Wang ; Shang-Gang RenSource :
- Guang pu xue yu guang pu fen xi = Guang pu [ 1000-0593 ] ; 2010.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Chlorophyll.
- Models, Theoretical, Plant Leaves, Populus, Regression Analysis, Spectrum Analysis.
Abstract
Hyperspectral reflectance and green degree of Platanus orientalis L. and Populus tomentosa Carr. leaves were measured by the ASD portable spectrometer and the portable chlorophyll meter SPAD-502, respectively. The chlorophyll concentration retrieval models based on 10 common vegetation indexes were established, and the ANN-BP model which used wave bands with larger correlation coefficient as input variables was established for chlorophyll content estimation. Finally, the ANFIS model was established to inverse vegetation chlorophyll content using hyperspectral data. The results showed that normalized difference vegetation index can inverse chlorophyll content better than other vegetation index, and the determination coefficients R2 of models of Platanus orientalis L. and Populus tomentosa Carr. were 0.795 7 and 0.754 6, respectively. The determination coefficients R2 between the predicted and the measured chlorophyll content based on ANN-BP models of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively. ANFIS model which is a good method to be applied to hyperspectral data for estimation of vegetation chlorophyll concentration can greatly improve vegetation chlorophyll concentration estimation accuracy, and the determination coefficients R2 between the predicted and the measured chlorophyll content of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively.
PubMed: 20827981
Affiliations:
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The chlorophyll concentration retrieval models based on 10 common vegetation indexes were established, and the ANN-BP model which used wave bands with larger correlation coefficient as input variables was established for chlorophyll content estimation. Finally, the ANFIS model was established to inverse vegetation chlorophyll content using hyperspectral data. The results showed that normalized difference vegetation index can inverse chlorophyll content better than other vegetation index, and the determination coefficients R2 of models of Platanus orientalis L. and Populus tomentosa Carr. were 0.795 7 and 0.754 6, respectively. The determination coefficients R2 between the predicted and the measured chlorophyll content based on ANN-BP models of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively. ANFIS model which is a good method to be applied to hyperspectral data for estimation of vegetation chlorophyll concentration can greatly improve vegetation chlorophyll concentration estimation accuracy, and the determination coefficients R2 between the predicted and the measured chlorophyll content of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">20827981</PMID><DateCompleted><Year>2015</Year><Month>07</Month><Day>08</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>01</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1000-0593</ISSN><JournalIssue CitedMedium="Print"><Volume>30</Volume><Issue>7</Issue><PubDate><Year>2010</Year><Month>Jul</Month></PubDate></JournalIssue><Title>Guang pu xue yu guang pu fen xi = Guang pu</Title><ISOAbbreviation>Guang Pu Xue Yu Guang Pu Fen Xi</ISOAbbreviation></Journal><ArticleTitle>[Application of ANFIS in in-situ measured hyperspectral data for vegetation chlorophyll content estimation].</ArticleTitle><Pagination><MedlinePgn>1834-8</MedlinePgn></Pagination><Abstract><AbstractText>Hyperspectral reflectance and green degree of Platanus orientalis L. and Populus tomentosa Carr. leaves were measured by the ASD portable spectrometer and the portable chlorophyll meter SPAD-502, respectively. The chlorophyll concentration retrieval models based on 10 common vegetation indexes were established, and the ANN-BP model which used wave bands with larger correlation coefficient as input variables was established for chlorophyll content estimation. Finally, the ANFIS model was established to inverse vegetation chlorophyll content using hyperspectral data. The results showed that normalized difference vegetation index can inverse chlorophyll content better than other vegetation index, and the determination coefficients R2 of models of Platanus orientalis L. and Populus tomentosa Carr. were 0.795 7 and 0.754 6, respectively. The determination coefficients R2 between the predicted and the measured chlorophyll content based on ANN-BP models of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively. ANFIS model which is a good method to be applied to hyperspectral data for estimation of vegetation chlorophyll concentration can greatly improve vegetation chlorophyll concentration estimation accuracy, and the determination coefficients R2 between the predicted and the measured chlorophyll content of Platanus orientalis L. and Populus tomentosa Carr. were 0.935 2 and 0.917 1, respectively.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Yao</LastName><ForeName>Fu-qi</ForeName><Initials>FQ</Initials><AffiliationInfo><Affiliation>College of Geography and Planning, Ludong University, Yantai 264025, China. fuqiyao163@163.com</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Zhen-hua</ForeName><Initials>ZH</Initials></Author><Author ValidYN="Y"><LastName>Yang</LastName><ForeName>Run-ya</ForeName><Initials>RY</Initials></Author><Author ValidYN="Y"><LastName>Sun</LastName><ForeName>Jin-wei</ForeName><Initials>JW</Initials></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Hai-jiang</ForeName><Initials>HJ</Initials></Author><Author ValidYN="Y"><LastName>Ren</LastName><ForeName>Shang-gang</ForeName><Initials>SG</Initials></Author></AuthorList><Language>chi</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>China</Country><MedlineTA>Guang Pu Xue Yu Guang Pu Fen Xi</MedlineTA><NlmUniqueID>9424805</NlmUniqueID><ISSNLinking>1000-0593</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>1406-65-1</RegistryNumber><NameOfSubstance UI="D002734">Chlorophyll</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002734" MajorTopicYN="N">Chlorophyll</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012044" MajorTopicYN="N">Regression Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013057" MajorTopicYN="Y">Spectrum Analysis</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2010</Year><Month>9</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2010</Year><Month>9</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>7</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">20827981</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><noCountry><name sortKey="Ren, Shang Gang" sort="Ren, Shang Gang" uniqKey="Ren S" first="Shang-Gang" last="Ren">Shang-Gang Ren</name><name sortKey="Sun, Jin Wei" sort="Sun, Jin Wei" uniqKey="Sun J" first="Jin-Wei" last="Sun">Jin-Wei Sun</name><name sortKey="Wang, Hai Jiang" sort="Wang, Hai Jiang" uniqKey="Wang H" first="Hai-Jiang" last="Wang">Hai-Jiang Wang</name><name sortKey="Yang, Run Ya" sort="Yang, Run Ya" uniqKey="Yang R" first="Run-Ya" last="Yang">Run-Ya Yang</name><name sortKey="Zhang, Zhen Hua" sort="Zhang, Zhen Hua" uniqKey="Zhang Z" first="Zhen-Hua" last="Zhang">Zhen-Hua Zhang</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Yao, Fu Qi" sort="Yao, Fu Qi" uniqKey="Yao F" first="Fu-Qi" last="Yao">Fu-Qi Yao</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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