Title:	Classificador de máxima verossimilhança aplicado à identificação de espécies nativas na Floresta Amazônica.
Authors:	MORAS FILHO, L. O. FIGUEIREDO, E. O. ISAAC JÚNIOR, M. A. BARROS, V. C. C. de HOTT, M. C. BORGES, L. A. C.
Affiliation:	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).
Date Issued:	2017
Citation:	In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017.
Pages:	6 p.
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
Keywords:	Manejo florestal Método de classificação digital Maximum Likelihood Máxima verossimilhança Rio Branco (AC) Acre Amazônia Ocidental Western Amazon Amazonia Occidental Especies nativas Análisis estadístico Bosques tropicales Estimación Identificación de plantas Sistemas de información geográfica Teledetección
ISBN:	978-85-11-00088-1
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CPAF-AC)