@InProceedings{SantosOlLiViRaSa:2017:MéAlCl,
author = "Santos, Ronaldo Medeiros and Oliveira, Isaac Alves and Lima,
Vin{\'{\i}}cius Orlandi Barbosa and Vicente, Marcelo Rossi and
Ramalho, Ant{\^o}nio Henrique Cordeiro and Santos, Tarley
Aparecido",
title = "M{\'e}todo alternativo de classifica{\c{c}}{\~a}o de imagens
orbitais para o mapeamento do uso/cobertura da terra nas bacias
dos rios Pardo e Salinas - MG",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "7436--7443",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Land use / land cover mapping is a basic prerequisite for the
development of a wide variety os studies and environmental actions
planning, such as territorial management, rational exploitation of
natural resources, environmental conservation and urban and
agricultural planning. However, obtaining accurate results is
still a challenge, because both the characteristics of the
sensors, that generate the orbital images, and the different
formulations of the classifiers may not be adequate to the natural
complexity of the studied area, such as the northern region of
Minas Gerais, characterized by strong fragmentation of the
landscape. Therefore, the objective of the present work was to
propose and evaluate an alternative classification method, based
on decision tree algorithm, for the land use/cover mapping in the
Pardo and Salinas rivers basins, in the northern region of Minas
Gerais State. The methodology comprised the development of an
alternative automatic decision tree classifier, considering
spectral and non-spectral information, and the evaluation of its
performance; individually and compared to the result obtained
through classic automatic classifiers. 12 land use/cover classes
were identified and the alternative method proposed was presented
satisfactory and superior performance to that obtained by the
application of the classical Battacharya (region) and maximum
likelihoo (pixel-by-pixel) classifiers.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "60161",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSMFN8",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMFN8",
targetfile = "60161.pdf",
type = "Processamento de imagens",
urlaccessdate = "15 jun. 2024"
}