Spectral models for estimating water content in Eucalyptus leaves

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorSuzano SA.-
Autor(es): dc.creatorStrabeli, Taila Fernanda-
Autor(es): dc.creatorFiorio, Peterson Ricardo-
Autor(es): dc.creatorRé, Natália Correr-
Autor(es): dc.creatorAlvares, Clayton Alcarde-
Autor(es): dc.creatordos Santos Luciano, Ana Claudia-
Autor(es): dc.creatorNakai, Érica Silva-
Data de aceite: dc.date.accessioned2025-08-21T15:14:16Z-
Data de disponibilização: dc.date.available2025-08-21T15:14:16Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2022-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.18671/scifor.v50.49-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/246905-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/246905-
Descrição: dc.descriptionThe relative water content (RWC) and equivalent water thickness (EWT) are parameters that provide a diversity of information about the plant’s hydric condition. Hyper-spectral remote sensing is a fast and non-destructive technique capable of generating data that allow the quantification of vegetation’s hydric condition. This study seeked to establish the existing relations among the water parameters (RWC and EWT) with the leaf spectral response of different species and hybrids of Eucalyptus. For the determination of the relative water content (CRA) it was necessary to determine the fresh weight (FW), the saturated weight (SW) and the dry weight (DW) and later carry out the spectral readings of each Eucalyptus leaf with the Fieldspec hyper-spectral sensor. Eight spectral indices were tested for the prediction of water parameters: Water Index (WI), Moisture Stress Index (MSI), Normalized Difference Water Index (NDWI), Normalized Difference Infrared Index (NDII), Simple Ratio 701 and 820 (SR701,820), Simple Ratio 1300 and 1450 (SR1300,1450), (R850-R2218)/(R850-R1928) and (R850-R1788)/(R850-R1928) in which the SR1300,1450 index was found R2= 0.72 when correlated with CRA and an R2=0.81 when correlated with EEA. The spectral data were correlated to the water parameters and it was found that the RWC at 1881 nm presented a maximum negative coefficient of correlation of r=-0,89 whereas the EWT presented a maximum negative coefficient of correlation of r=-0,79 at 2165 nm. Four methods of selecting hyperspectral variables were tested to generate a mathematical model through linear regression. For the RWC parameter the stepwise variable selection method generated the higher R2=0,86 with a RMSE = 13,85%, considering that just six predicting variables were left in this method. While the variable selection method by spectral regions was the most precise to predict the EWT parameter with an R2=0,87 and an RMSE=0,0012g/cm2. It is possible to predict CARA and ELA, for the generation of Eucalyptus by means of mathematical models derived from hyperspectral data.-
Descrição: dc.descriptionEscola Superior de Agricultura “Luiz de Queiroz” – ESALQ Universidade de São Paulo – USP, SP-
Descrição: dc.descriptionFaculdade de Ciências Agronômicas – FCA Universidade Estadual Paulista “Júlio de Mesquita Filho” – UNESP, SP-
Descrição: dc.descriptionSuzano SA., SP-
Descrição: dc.descriptionFaculdade de Ciências Agronômicas – FCA Universidade Estadual Paulista “Júlio de Mesquita Filho” – UNESP, SP-
Idioma: dc.languagept_BR-
Relação: dc.relationScientia Forestalis/Forest Sciences-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectEquivalent water thickness-
Palavras-chave: dc.subjectHyperspectral remote sensing-
Palavras-chave: dc.subjectSpectral indices-
Título: dc.titleSpectral models for estimating water content in Eucalyptus leaves-
Título: dc.titleModelos espectrais para a estimativa do conteúdo de água em folhas de Eucalyptus-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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