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Proceedings Paper

Application of multi-sensor images for detecting land cover change and analysis of urban expansion
Author(s): Jinsong Deng; Ke Wang; Yanhua Deng; Jun Li
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Paper Abstract

Zhejiang province is playing an increasingly vital role in China's overall economic growth. Concomitant with the dramatic economic development, this region has been undergoing tremendous urban growth on an unprecedented scale and rate. Many urbanization-related problems have been identified, including agricultural land and wetland loss, water pollution and soil erosion. There is an urgent need to detect and monitor the land cover change and analyze the magnitude and pattern, accurately and timely for planning and management. Remote sensing is a powerful tool for monitoring rapid change in the landscape resulting from urban development. However, change detection capabilities are intrinsically limited by the spatial resolution of the digital imagery in urban. The application of multi-sensor data provides the potential to more accurately detect land-cover changes through integration of different features of sensor data. Taking Hangzhou city as case study, this paper presents a method that combines principal component analysis (PCA) of multi-sensor data (SPOT-5 XS and ETM Pan data) and a hybrid classification involving unsupervised and supervised classier to detect and analysis land cover change. The study demonstrates that this method provides a very useful way in monitoring rapid land cover change in urban environment.

Paper Details

Date Published: 2 December 2005
PDF: 6 pages
Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604526 (2 December 2005); doi: 10.1117/12.651400
Show Author Affiliations
Jinsong Deng, Zhejiang Univ. (China)
Ke Wang, Zhejiang Univ. (China)
Yanhua Deng, Changsha Environmental Protection College (China)
Jun Li, Zhejiang Univ. (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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