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Entree


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

Autor(es):
Miyoshi, G. T. ; Imai, N. N. ; Tommaselli, A. M. G. ; Honkavaara, E. ; IEEE
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: 2020 IEEE LATIN AMERICAN GRSS & ISPRS REMOTE SENSING CONFERENCE (LAGIRS); v. N/A, p. 6-pg., 2020-01-01.
Resumo

The 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. (AU)

Processo FAPESP: 13/50426-4 - Unmanned airborne vehicle-based 4D remote sensing for mapping Rain Forest biodiversity and its change in Brazil (UAV_4D_Bio)
Beneficiário:Antonio Maria Garcia Tommaselli
Modalidade de apoio: Auxílio à Pesquisa - Regular