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dc.creatorSantos, Alexandre dos-
dc.creatorSantos, Isabel Carolina de Lima-
dc.creatorSilva, Nubia da-
dc.creatorZanetti, Ronald-
dc.creatorOumar, Zakariyyaa-
dc.creatorGuimarães, Lucas Fernando Resende-
dc.creatorCamargo, Mariane Bueno de-
dc.creatorZanuncio, José Cola-
dc.date.accessioned2020-06-16T17:37:15Z-
dc.date.available2020-06-16T17:37:15Z-
dc.date.issued2019-08-
dc.identifier.citationSANTOS, A. dos et al. Mapping defoliation by leaf-cutting ants Atta species in Eucalyptus plantations using the Sentinel-2 sensor. International Journal of Remote Sensing, London, v. 41, n. 4, p. 1542-1554, 2020.pt_BR
dc.identifier.urihttps://www.tandfonline.com/doi/abs/10.1080/01431161.2019.1672903pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/41458-
dc.description.abstractLeaf-cutting ants are one of the most important pests of eucalyptus plantations and it is essential to monitor and control these insects to avoid damage to wood production. The objective of this research was to assess the utility of the multispectral sensor, Sentinel-2 (S-2) in mapping defoliation caused by leaf-cutting ants in Eucalyptus plantations. The study was carried out in Eucalyptus plantations in Telêmaco Borba, Paraná state, Brazil. The leaf-cutting ant nests were located, measured and georeferenced. Multispectral images from bands 2, 3, 4 and 8 of the S-2 satellite and four vegetation indices (VIs) were tested in predicting and mapping leaf-cutting ant defoliation. From each image scene the reflectance values were extracted and a partial least squares discriminant analysis (PLS-DA) was performed. The predictive variables, included in the PLS-DA regression, were selected based on the calculation of the variable importance in the projection (VIP). The accuracy of the mapping was 84.5% using six main components, demonstrating a satisfactory approach to operationally classifying canopies of Eucalyptus stands attacked by leaf-cutting ants. The study indicates the potential of freely available medium resolution Multispectral instrument (MSI) S-2 images, to accurately detect and map defoliation caused by Atta species in commercial forest plantations.pt_BR
dc.languageenpt_BR
dc.publisherTaylor & Francis Grouppt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceInternational Journal of Remote Sensingpt_BR
dc.subjectLeaf-cutting antspt_BR
dc.subjectForest pestspt_BR
dc.subjectEucalyptus - Pestspt_BR
dc.subjectFormigas cortadeiraspt_BR
dc.subjectPragas florestaispt_BR
dc.subjectEucalipto - Doenças e pragaspt_BR
dc.titleMapping defoliation by leaf-cutting ants Atta species in Eucalyptus plantations using the Sentinel-2 sensorpt_BR
dc.typeArtigopt_BR
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