@InProceedings{SaitoArguMore:2013:MiDaAn,
author = "Saito, Nath{\'a}lia Suemi and Arguello, Fernanda Viana Paiva and
Moreira, Maur{\'{\i}}cio Alves",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Minera{\c{c}}{\~a}o de dados para an{\'a}lise da cobertura
florestal",
booktitle = "Anais...",
year = "2013",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio
Soares",
pages = "2400--2407",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "The landscape ecology metrics associated with spectral and space
data mining can be used to increase the potential of the analysis
and applications of remote sensing data becoming an important tool
for decision making. The present study sought to use data mining
techniques and metrics of landscape ecology to classify and
quantify the different types of vegetation present in S{\~a}o
Luis do Paraitinga city, Sao Paulo, Brazil. The images went
through object-oriented analysis through the plugin GeoDMA to
obtain spectral and spatial data. This information was used to
classify classes by decision trees. Eucalyptus and Forest fragment
areas represented 8.6% and 36,1% of the total area, respectively.
The decision tree generated by the classification algorithm was
used to obtain the map of forest cover. The classification by
decision tree showed kappa of 0.80, indicating little confusion.
The results indicate the importance of the forest sector and
contribute in studies to contain the impacts and problems caused
by the expansion of eucalyptus plantations in the municipality.
The generation of classifications by the method of data mining
metrics associated with landscape ecology proved to be an
affordable and reliable tool to extract the spatial and spectral
data with remote sensing techniques. The method was efficient for
the separation of forest classes and the metrics used were
important to better understand the objects inserted in the
landscape and the pressures they suffer.",
conference-location = "Foz do Igua{\c{c}}u",
conference-year = "13-18 abr. 2013",
isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
label = "1444",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "3ERPFQRTRW34M/3E7GLCP",
url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GLCP",
targetfile = "p1444.pdf",
type = "Classifica{\c{c}}{\~a}o e Minera{\c{c}}{\~a}o de Dados",
urlaccessdate = "2024, Apr. 26"
}