SPECTRAL DIFFERENCES OF TREE SPECIES BELONGING TO ATLANTIC FOREST OBTAINED FROM UAV HYPERSPECTRAL IMAGES

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorNatl Land Survey Finland-
Autor(es): dc.creatorMiyoshi, G. T. [UNESP]-
Autor(es): dc.creatorImai, N. N. [UNESP]-
Autor(es): dc.creatorTommaselli, A. M. G. [UNESP]-
Autor(es): dc.creatorHonkavaara, E.-
Autor(es): dc.creatorIEEE-
Data de aceite: dc.date.accessioned2022-02-22T00:58:35Z-
Data de disponibilização: dc.date.available2022-02-22T00:58:35Z-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2021-06-25-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/210112-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/210112-
Descrição: dc.descriptionThe objective of this study is to evaluate the spectral difference between and within 11 tree species belonging to Brazilian Atlantic Forest located in the countryside of Sao Paulo State, Brazil. Tree species with different development stages may have different reflectance spectra because of the structural and phenological influence on it. Tree structure can affect the crown spectra due to the differences in geometry of view and density of shadow and sunlight pixels. Additionally, reflectance spectra can be similar between tree species belonging from different species, which affect the classification accuracy of these targets. In this sense, we evaluate the spectral difference between highly diverse Atlantic Forest using two different features extracted from individual tree crowns (ITCs). Mean reflectance spectra and mean normalized reflectance spectra of each ITC were used. They were computed from hyperspectral images acquired with sensor onboard unmanned aerial vehicle. Differences between tree species and within-species were calculated. Wilcoxon-Mann-Whitney test was applied in order to statistically evaluate whether the reflectance spectra were different. Results showed that the normalized values are more propense to increase the classification accuracies than using the mean values since it reduces the variability within-species and present a higher number of different values between-species.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionAcademy of Finland-
Descrição: dc.descriptionSao Paulo State Univ, Grad Program Cartog Sci, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Cartog, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionNatl Land Survey Finland, Finnish Geospatial Res Inst, Geodeetinrinne 2, Masala 02430, Finland-
Descrição: dc.descriptionSao Paulo State Univ, Grad Program Cartog Sci, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Cartog, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
Descrição: dc.descriptionCAPES: 001-
Descrição: dc.descriptionCAPES: 88881.187406/2018-01-
Descrição: dc.descriptionCNPq: 153854/2016-2-
Descrição: dc.descriptionFAPESP: 2013/50426-4-
Descrição: dc.descriptionAcademy of Finland: 305994-
Formato: dc.format60-65-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2020 Ieee Latin American Grss & Isprs Remote Sensing Conference (lagirs)-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectSpectral difference-
Palavras-chave: dc.subjectTree species-
Palavras-chave: dc.subjectTropical Atlantic forest-
Palavras-chave: dc.subjectHyperspectral imagery-
Palavras-chave: dc.subjectUAV-
Palavras-chave: dc.subjectWilcoxon-Mann-Whitney test-
Título: dc.titleSPECTRAL DIFFERENCES OF TREE SPECIES BELONGING TO ATLANTIC FOREST OBTAINED FROM UAV HYPERSPECTRAL IMAGES-
Aparece nas coleções:Repositório Institucional - Unesp

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