Integrating genetic algorithm method with neural network for land use classification using SZ-3 CMODIS data  

作　　者：WANG Changyao LUO Chengfeng LIU Zhengjun 

机构地区：[1]The State Key Laboratory of Remote Sensing Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China [2]Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100039,China

出　　处：《Progress in Natural Science:Materials International》2005年第10期937-942,共6页自然科学进展·国际材料（英文版）

基　　金：Supported by the National High Technology Research and Development Program of China (Grant No. 2003 AA 131020, 863-308-13-03[02]) the Major State Basic Research Program of China (Grant No. G2000077902)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX1-SW-01-02)National Key Technologies R & D Program of China (Grant No.2001DF BA0005)

摘　　要：This paper presents a methodology on land use mapping using CMODIS （Chinese Moderate Resolution Imaging Spectroradiometer） data on-board SZ-3 （Shenzhou 3） spacecraft. The integrated method is composed of genetic algorithm （GA） for feature extraction and neural network classifier for land use classification. In the data preprocessing, a moment matching method was adopted to remove the stripes in the images. Then by using the reproduction, crossover and mutation operators of GA based on the mechanism of “natural selection”, and with Jeffries-Matusita distance as its discriminate rule and the training samples, the optimal band combination for land use classification was obtained. To generate a land use map, the three layers back propagation neural network classifier is used for training the samples and classification. Compared with the Maximum Likelihood classification algorithm, the results show that the accuracy of land use classification is obviously improved by using our proposed method, the selected band number in the classification process is reduced, and the computational performance for training and classification is improved. The result also shows that the CMODIS data can be effectively used for land use/land cover classification and change monitoring at regional and global scale.This paper presents a methodology on land use mapping using CMODIS (Chinese Moderate Resolution Imaging Spectroradiometer ) data on-board SZ-3 (Shenzhou 3) spacecraft. The integrated method is composed of genetic algorithm (GA) for feature extraction and neural network classifier for land use classification. In the data preprocessing, a moment matching method was adopted to reuse classification was obtained. To generate a land use map, the three layers back propagation neural network classifier is used for training the samples and classification. Compared with the Maximum Likelihood classification algorithm, the results show that the accuracy of land use classification is obviously improved by using our proposed method, the selected band number in the classification process is reduced,and the computational performance for training and classification is improved. The result also shows that the CMODIS data can be effectively used for land use/land cover classification and change monitoring at regional and global scale.

关 键 词：CMODIS genetic algorithm band selection neural network land use classification. 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]