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Proceedings Paper

The study on dynamic extraction of urban land use cover with remote sensing image based on AdaBoost algorithm
Author(s): Rui Li; Jiulin Sun; Juanle Wang; Lijun Zhu; Rui Liu
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Paper Abstract

In China, the contradiction of urban land use and cultivated land use is predominant, it's important to detect the urban land use cover for the guide of urban development. The primary problem of dynamic detecting on urban land use cover is how to get accurate classification of remote sensing data. Theoretically, if combining several low precision classifiers, a better classification result can be made and this paper introduces how to combine the low precision urban land use cover classifiers. We use CBERS (China-Brazil Earth Resources Satellite) remote sensing images of the year 2007 for Shanghai's urban land use cover. We adopt the AdaBoost combination classifier, which combines spectral feature information, texture structure information and improved Normalized Difference Built-up Index (NDBI) to improve the individual classification precision. The experiment results show that a notable improvement of classification precision of urban land use cover is achieved after using AdaBoost algorithm.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981U (30 October 2009); doi: 10.1117/12.833730
Show Author Affiliations
Rui Li, Henan Univ. (China)
Institute of Geographical Sciences and Natural Resources Research (China)
Jiulin Sun, Henan Univ. (China)
Institute of Geographical Sciences and Natural Resources Research (China)
Juanle Wang, Institute of Geographical Sciences and Natural Resources Research (China)
Lijun Zhu, Institute of Geographical Sciences and Natural Resources Research (China)
Rui Liu, Institute of Geographical Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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