@InProceedings{ReisPantSantDutr:2015:ClCoTe,
author = "Reis, Mariane Souza and Pantale{\~a}o, Eliana and Sant'Anna,
Sidnei Jo{\~a}o Siqueira and Dutra, Luciano Vieira",
affiliation = "{} and {} and {} and {Instituto Nacional de Pesquisas Espaciais
(INPE)}",
title = "Classifica{\c{c}}{\~a}o de cobertura da terra utilizando dados
{\'o}ticos e de radares de abertura sint{\'e}tica",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "4612--4619",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "The availability of optical data is subject to weather conditions
and lighting of the scene. Images from Synthetic Aperture Radar
(SAR) can be obtained almost independently from weather
conditions, what renders this data a strong candidate to be used
in cover classification studies. Also, since these two different
data are complementary, their combination can improve the results
obtained with each separately. This work compares classification
results from optical data, SAR data and optical-SAR fusion data
and evaluates their performance for land cover identification. The
study area is located in Belterra, state of Par{\'a}, in the
Legal Amazon region. Different sets of data were used, including
the original data and other texture attributes extracted from
them. The aim of the study is to evaluate the use of optical, SAR
data and the fusion of both for the assessment of the
classifications and also the sensibility of the results to the
variations induced by the selection of the training data. Results
show that the use of SAR data together with optical data does not
improve classification results when compared to the use of only
optical data and the use of texture attributes of optical data may
be interesting for only some cover classes. In the absence of
optical data, texture attributes derived from filtrated SAR data
may be used instead, with less accurate results in general,
although the classification of fallow agriculture areas is
improved in comparison to that obtained from optical data.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "902",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM4D2H",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4D2H",
targetfile = "p0902.pdf",
type = "Sensoriamento remoto de microondas",
urlaccessdate = "27 abr. 2024"
}