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Proceedings Paper

Application of expert classification system in dynamic monitor of ecology environment
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Paper Abstract

Now, the recovering and reconstruction of ecology environment are more and more focused by people all the nation, when government began to develop the west of nation. But, how to make the exact evaluation to the construction work of ecology environment, and how to make the best out of the limited resource of constructing work, these need to dynamic monitor the variation of the land-use in research region. In this paper, we mainly work over the method witch using remote sensing technology and working with LANDSAT TM satellite RS images, digital evolution model data, RS base situation investigation data, vectorized data of terrain map and outside investigation information etc., to establish the models based on judgment rules, acquired from expert experiment, and form the expert classification system. The research results indicate that (1) it is precise method to classify the RS images because of combined use of all kinds of data and science geographic model, especially, the variation of land-use can be cleanly interpreted from RS images. (2) It can be used to classify the same objects with same spectral feature which can not be classified by traditional methods just like supervised and unsupervised classification. (3) By using this method, the precise of classification can be improved because it excludes something being classified unreasonable.

Paper Details

Date Published: 14 July 2003
PDF: 6 pages
Proc. SPIE 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land, (14 July 2003); doi: 10.1117/12.466825
Show Author Affiliations
Fengdong Deng, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)
Anlin Liu, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)
Dengke Li, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)
Jinghong Zhang, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)
Jin Dai, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)
Jing Zhuo, Shaanxi Remote Sensing Information Ctr. for Agriculture (China)


Published in SPIE Proceedings Vol. 4890:
Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land
Xiaoling Pan; Wei Gao; Michael H. Glantz; Yoshiaki Honda, Editor(s)

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