Remote Sense Image Classification Based on CART Algorithm

Author:

Yang Bao Hua1,Li Shuang1

Affiliation:

1. Anhui Agriculture University

Abstract

This papers deals with the study of the algorithm of classification method based on decision tree for remote sensing image. The experimental area is located in the Xiangyang district, the data source for the 2010 satellite images of SPOT and TM fusion. Moreover, classification method based on decision tree is optimized with the help of the module of RuleGen and applied in regional remote sensing image of interest. The precision of Maximum likelihood ratio is 95.15 percent, and 94.82 percent for CRAT. Experimental results show that the classification method based on classification and regression tree method is as well as the traditional one.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference6 articles.

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3. R. ROLLET: submitted to Journal of International Journal of Remote Sensing. Vol. 19 (1998), p.2665.

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5. Atkinson P M, Tatnall A R L: submitted to Journal of Neural networks in remote sensing. Vol. 18 (1997), p.699.

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