Title
An Object-Oriented Approach of Extracting Special Land use Classification by using Quick Bird Image
Abstract
The ability to extract the special land use type of environment, and associated temporal changes, has important societal and economic meaning. This paper uses the high spatial resolution of the image---QuickBird to extract greenhouse in agriculture of Hexian region, ANHUI province in China. The paper uses software package eCognition to process data and extract information. The software adopted object-oriented image segmentation and classification which is based on fuzzy logic. In this study the greenhouse is a special land cover type in agricultural land, we use not only image object's attributes, but also the relationship between networked image objects; it can perform sophisticated classification and get satisfied classification result, allows the integration of a broad spectrum of different object features, such as spectral values, shape and texture. The aim of this work was to develop an object-oriented segmentation and classification approach for extracting special land cover type.
Year
DOI
Venue
2008
10.1109/IGARSS.2008.4779825
IGARSS
Keywords
Field
DocType
geophysical techniques,geophysics computing,land use type,anhui province,land use,spectral values,land use classification,china,greenhouse,image segmentation,object-oriented,data processing,quickbird image,object-oriented approach,land cover type,agriculture,fuzzy logic,hexian region,texture features,image objects shape,feature extraction,image classification,quickbird,greenhouse extraction,greenhouses,image texture,ecognition software package,object-oriented methods,agricultural land,spatial resolution,meteorology,satisfiability,classification algorithms,object oriented,data mining,spectrum,satellites,pixel,crops,image resolution
Computer vision,Computer science,Segmentation,Image texture,Remote sensing,Image segmentation,Feature extraction,Artificial intelligence,Contextual image classification,Statistical classification,Land cover,Land use
Conference
Volume
ISBN
Citations 
4
978-1-4244-2808-3
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Wenbo Xu177.75
Guoping Zhang200.34
Jianxi Huang31013.31