Study on Classification method of TM Image with Artificial Neural Network
Given the shortage of classified methods for remote sensing informations at present,the Self-organizing Artificial Neural Network is applied to classifying for TM image in order to improve classification accuracy in this paper.At the same time,as for the effecting factors of classification remote sensing image,Surface structure is considered as important parameter,which is different from other classified methods only considering spectral characters(including ENVI,Tasseled Cap,principle components,TM seven bands and etcs).Taking example for the research area of Guangzhou city,comparing with the traditional maximum likelihood classification,the result shows that the Self-organizing Artificial Neural Network is better than the supervised Maximum likelihood classification and the new method is more efficient,It is very important to provide one new mean for the classification of surface object characters in remote sensing image.
TM image classification surface structure Self-organizing Artificial Neural Network Maximum likelihood
Zhenhua Liu WenYa Jianbo Xu
College of Informatics,South China Agricultural University,GuangZhou City,GuangDong Province,P.R .China 510642
国际会议
第16届国际地理信息科学与技术大会(16th International Conference on GeoInformatics and the Joint Conference)
广州
英文
2008-06-28（万方平台首次上网日期，不代表论文的发表时间）