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Assessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indices

dc.contributor.authorRossi, Fernando Saragosa [UNESP]
dc.contributor.authorDella-Silva, João Lucas
dc.contributor.authorTeodoro, Larissa Pereira Ribeiro
dc.contributor.authorTeodoro, Paulo Eduardo
dc.contributor.authorSantana, Dthenifer Cordeiro
dc.contributor.authorBaio, Fábio Henrique Rojo
dc.contributor.authorMorinigo, Wendel Bueno
dc.contributor.authorCrusiol, Luís Guilherme Teixeira
dc.contributor.authorLa Scala, Newton [UNESP]
dc.contributor.authorda Silva, Carlos Antonio
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionState University of Mato Grosso (UNEMAT)
dc.contributor.institutionUniversidade Federal de Mato Grosso do Sul (UFMS)
dc.contributor.institutionFederal University of Mato Grosso (UFMT)
dc.contributor.institutionEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.date.accessioned2025-04-29T20:11:25Z
dc.date.issued2024-12-01
dc.description.abstractEucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data.en
dc.description.affiliationPPG-Ciência do Solo State University of São Paulo (UNESP)
dc.description.affiliationPPG-Bionorte State University of Mato Grosso (UNEMAT)
dc.description.affiliationFederal University of Mato Grosso do Sul (UFMS)
dc.description.affiliationPPGCAM Federal University of Mato Grosso (UFMT)
dc.description.affiliationNational Soybean Research Center (Embrapa Soja) Brazilian Agricultural Research Corporation
dc.description.affiliationDepartment of Geography State University of Mato Grosso (UNEMAT), Mato Grosso
dc.description.affiliationUnespPPG-Ciência do Solo State University of São Paulo (UNESP)
dc.identifierhttp://dx.doi.org/10.1038/s41598-024-71430-2
dc.identifier.citationScientific Reports, v. 14, n. 1, 2024.
dc.identifier.doi10.1038/s41598-024-71430-2
dc.identifier.issn2045-2322
dc.identifier.scopus2-s2.0-85202870317
dc.identifier.urihttps://hdl.handle.net/11449/308150
dc.language.isoeng
dc.relation.ispartofScientific Reports
dc.sourceScopus
dc.titleAssessing soil CO2 emission on eucalyptus species using UAV-based reflectance and vegetation indicesen
dc.typeArtigopt
dspace.entity.typePublication

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