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

Abstract

Abstract 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 sel...