@InProceedings{CarvalhoKuxFlor:2012:UrLaCo,
author = "Carvalho, Marcus and Kux, Hermann Johann Heinrich and Florenzano,
Teresa Gallotti",
affiliation = "{} and undefined and undefined",
title = "Urban land cover classification with Worldview-2 images using Data
mining and Object-based image analysis",
booktitle = "Proceedings...",
year = "2012",
editor = "Feitosa, Raul Queiroz and Costa, Gilson Alexandre Ostwald Pedro da
and Almeida, Cl{\'a}udia Maria de and Fonseca, Leila Maria Garcia
and Kux, Hermann Johann Heinrich",
pages = "431--436",
organization = "International Conference on Geographic Object-Based Image
Analysis, 4. (GEOBIA).",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "Remote sensing, Data mining, Geographic object-based image
analysis, Urban land cover, High spatial resolution satellite
images.",
abstract = "The products available from new satellite sensor systems with high
spatial resolution present a considerable potential for
applications in urban areas. These datasets open new perspectives
for the automatic extraction of information for environmental
planning and management. However in order to get efficiently the
information required, innovative concepts are necessary at both
working phases: segmentation and discrimination of objects within
the image. The objective of this study is to develop a methodology
using OBIA and Data mining techniques to map land cover with
WorldView-2 images in a western district of S{\~a}o Paulo
municipality (Brazil). The Data mining techniques used were
decision trees at algorithm C4.5 from the free software package
WEKA, known as J48. It allows the system user to configure
different functionalities which intervene at the final Data mining
result, such as MinNumObj: the minimum number of instances
(objects) by sheet. Through this functionality it is possible to
control the size and complexity of the tree generated. In this
study the performance of image classification obtained from two
decision trees was evaluated, considering different MinNumObj. The
statistical assessment indicated a good precision for both maps,
with Kappa Indices of 0.7876 (MinNumObj: 25) and 0.8383
(MinNumObj: 2).",
conference-location = "Rio de Janeiro",
conference-year = "May 7-9, 2012",
isbn = "978-85-17-00059-1",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP8W/3BTG99B",
url = "http://urlib.net/ibi/8JMKD3MGP8W/3BTG99B",
targetfile = "117.pdf",
type = "Urban Applications",
urlaccessdate = "09 maio 2024"
}