Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1072220
Research center of Embrapa/Collection: Embrapa Acre - Artigo em anais de congresso (ALICE)
Date Issued: 2017
Type of Material: Artigo em anais de congresso (ALICE)
Authors: MORAS FILHO, L. O.
FIGUEIREDO, E. O.
ISAAC JÚNIOR, M. A.
BARROS, V. C. C. de
HOTT, M. C.
BORGES, L. A. C.
Additional Information: Luiz Otávio Moras Filho, Universidade Federal de Lavras (Ufla); EVANDRO ORFANO FIGUEIREDO, CPAF-Acre; Marcos Antônio Isaac Júnior, Universidade Federal de Lavras (Ufla); Vanessa Cabral Costa de Barros, Universidade Federal de Lavras (Ufla); Marcos Cicarini Hott, Universidade Federal de Lavras (Ufla); Luís Antônio Coimbra Borges, Universidade Federal de Lavras (Ufla).
Title: Classificador de máxima verossimilhança aplicado à identificação de espécies nativas na Floresta Amazônica.
Publisher: In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017.
Pages: 6 p.
Language: pt_BR
Keywords: Manejo florestal
Método de classificação digital
Maximum Likelihood
Máxima verossimilhança
Rio Branco (AC)
Acre
Amazônia Ocidental
Western Amazon
Amazonia Occidental
Bosques tropicales
Teledetección.
Sistemas de información geográfica
Identificación de plantas
Estimación
Especies nativas
Análisis estadístico
Description: Among a variety of digital classification methods based on remote sensing images, the Maximum Likelihood (ML) is widely used in environmental studies, mainly for land cover and vegetation analysis. This study aimed to evaluate the effectiveness of supervised classification by ML technique in a forest management area of dense ombrophilous forest, using one RapidEye image. With this purpose, it was conducted the census of species over 30 cm in diameter at breast height and calculated the Cover Value Index (CVI), and selected the 20 species with the highest CVI as a parameter for classification in a Geographic Information System. 13 of the 20 species selected in the study area were not identified by the classification method, and among the seven identified species, two were underestimated and the others were overestimated. Both the maximum likelihood technique and the spatial resolution of the image used were not suitable for supervised classification of native vegetation, with Kappa index of 0.05 and global accuracy of 5.53%. Studies using spectral characterization in leaf level supported by higher or hyper spectral and spatial resolution images are recommended to increase the accuracy of classification.
Thesagro: Floresta tropical
Espécie nativa
Identificação
Estimativa
Sensoriamento remoto
Sistema de informação geográfica
Análise estatística
Método estatístico
NAL Thesaurus: Tropical forests
Indigenous species
Plant identification
Estimation
Remote sensing
Geographic information systems
Statistical analysis.
Data Created: 2017-07-07
ISBN: 978-85-11-00088-1
Appears in Collections:Artigo em anais de congresso (CPAF-AC)

Files in This Item:
File Description SizeFormat 
26344.pdf484,78 kBAdobe PDFThumbnail
View/Open

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace