@InProceedings{DutraOliReiCalLu:2017:CoAgSy,
author = "Dutra, Luciano Vieira and Oliveira, Maria Ant{\^o}nia Falc{\~a}o
de and Reis, Mariane Souza and Calvi, Miqu{\'e}ias Freitas and
Lu, Dengsheng",
affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Cocoa agroforest systems classification with high resolution
images",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "304--311",
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 = "The objective of this work is to verify the viability of cocoa
agroforestry classification with High Resolution imagery to
include, in the cropland area, the mapping of cocoa planted under
forest, as well as open cocoa plantation. In order to avoid
overestimating the cocoa area, we introduce the concept of
counter-examples (CE). Counter-examples are areas of known
classes, not directly involved in classification focus, but
identified to avoid the classes of focus being misleadingly
classified. Two set of CE was used. The first one is the merging
of 7 non-cocoa classes in one training set. The other uses each of
these 7 CE classes separately in the training set. Among the
several classifiers tested, the best one was SVM with RBF kernel.
Results showed that using one CE set produces a more uniform
classification map than using 7 CE separately and captures 20%
more cocoa cultivated area in a test field, than mapping open
cocoa only, with similar user accuracy.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "60283",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PS43PA",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS43PA",
targetfile = "60283.pdf",
type = "Processamento de imagens",
urlaccessdate = "27 abr. 2024"
}