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Proceedings Paper

Comparison of land cover classification methods based on single-temporal MODIS data
Author(s): Tao Han; Xiaotao Xu; Yaohui Li; Yaowen Xie
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Paper Abstract

Based on single-temporal MODIS data of Gansu province, mainly using its spectra information, three classifiers - the Maximum likelihood, BP neural network and decision tree based on data mining software See 5.0 are applied in the Land cover classification research. The validated results show that decision tree algorithm has the best performance of extraction with an overall accuracy of 82.13 percent, followed by the BP network algorithm, and that of the maximum likelihood classifier is worst; the accuracy of low vegetation area is improved with the indexes of TVA and TVD; Data mining software of See 5.0 with boosting technique can build decision tree quickly and improve the precision of miscible classes.

Paper Details

Date Published: 7 November 2008
PDF: 9 pages
Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470H (7 November 2008); doi: 10.1117/12.813218
Show Author Affiliations
Tao Han, China Meteorological Administration (China)
Xiaotao Xu, Lanzhou Univ. (China)
Yaohui Li, China Meteorological Administration (China)
Yaowen Xie, Lanzhou Univ. (China)


Published in SPIE Proceedings Vol. 7147:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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