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Proceedings Paper

Identification of coastal wetland using rule inferring
Author(s): Renzong Ruan; Landi Xia; Ziqi Yan
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Paper Abstract

The main purpose of this paper was to explore the potential of decision tree classifier in the identification and change monitoring of coastal wetland. A part of the coastal wetland in the Northern Jiangsu Province was taken as test area. Decision tree classifiers derived using different ways were applied to the classification of coastal wetland and the results were compared by independent sampling points. It was shown that the post-classification improvements by using knowledge rules could achieve higher accuracy than automatic machine learning method. In the post-classification improvements, the selection of feature vectors was crucial to the improvement of accuracy of classification.

Paper Details

Date Published: 26 July 2007
PDF: 10 pages
Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 67522L (26 July 2007); doi: 10.1117/12.760766
Show Author Affiliations
Renzong Ruan, Hohai Univ. (China)
Landi Xia, Hohai Univ. (China)
Ziqi Yan, Hohai Univ. (China)


Published in SPIE Proceedings Vol. 6752:
Geoinformatics 2007: Remotely Sensed Data and Information

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