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Proceedings Paper

Classification and extraction of the urban land-use information from high-resolution image based on the multi-features of the objects
Author(s): Chunfang Kong; Kai Xu; Chonglong Wu; Gang Liu
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Paper Abstract

The land in an urban is the basic space for urban dwellers. It provides places for various economic activities and is the economic radiation source that affects the development of the surrounding areas. With the fast development of industrialization and urbanization, the contradiction in land-use becomes tenser, which makes the urban administrators and decision-makers seek modern methods and technology to provide information support for the urban development. Recently, with the fast development of the high-resolution sensor technology, people can obtain lots of data, which can create the advantage for people to study sustainable development of urban land-use and provide a large amount of first-hand data. However, these data are not information. They are only information sources and are mixture of various "information" and "noise". Only through further process, analysis and information extraction of the data, can the remote sensing data and image obtained through remote sensing technology be converted into useful information from which valuable knowledge can be extracted to afford guideline for scientific decision-making. Therefore, this paper extracts the urban land-use information of high-resolution image by using the multi-features information of high-resolution image objects, as well as adopts Object-Oriented image analysis approaches and multi-scale image segmentation technology, and sets up the classifying and extracting model based on the multi-features of the image objects, in order to contribute to information for reasonable plan and effective management. It is obvious that this new image analysis approach offers a satisfying solution to extract information quickly and efficiently.

Paper Details

Date Published: 2 December 2005
PDF: 8 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 60452W (2 December 2005); doi: 10.1117/12.651831
Show Author Affiliations
Chunfang Kong, China Univ. of Geosciences (China)
Kai Xu, China Univ. of Geosciences (China)
Chonglong Wu, China Univ. of Geosciences (China)
Gang Liu, China Univ. of Geosciences (China)


Published in SPIE Proceedings Vol. 6045:
MIPPR 2005: Geospatial Information, Data Mining, and Applications
Jianya Gong; Qing Zhu; Yaolin Liu; Shuliang Wang, Editor(s)

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