国土资源遥感2016，Vol.28Issue(1)：22-27,6.DOI:10.6046/gtzyyg.2016.01.04
基于PCA的变化向量分析法遥感影像变化检测
Remote sensing image change detection based on change vector analysis of PCA component
摘要
Abstract
In order to monitor the change of land cover with remote sensing technology,the authors studied a method which is based on single-temporal remote sensing image in different years for extracting differences between the images and determining the change threshold automatically to extract the change area.The research took Landsat80LI images of Nantong City as an example.Principal component analysis (PCA) was carried out respectively on two images.After the PCA transformation,the first three components were operated based on change vector analysis (CVA) to get the difference image for change detection,which was compared with the extraction results based on the traditional PCA method and CVA method.Overall minimum error probability threshold determination method and local minimum error probability method were utilized to automatically determine the threshold of the three difference images and to get six change area images.The accuracy was evaluated by visual interpretation,and the results show that the overall accuracy of the new method can reach 92.78％,with kappa coefficient up to 0.842 6.This method is proved to be feasible and effective for extracting change area by single-temporal remote sensing image in different years.关键词
变化向量分析(CVA)/主成分分析(PCA)/阈值确定/变化检测Key words
change vector analysis(CVA)/principal component analysis(PCA)/threshold determination/change detection分类
计算机与自动化引用本文复制引用
黄维,黄进良,王立辉,胡砚霞,韩鹏鹏..基于PCA的变化向量分析法遥感影像变化检测[J].国土资源遥感,2016,28(1):22-27,6.基金项目
中科院战略性先导科技专项专题“应对气候变化的碳收支认证及相关问题”(编号:XDA05050107)资助. （编号:XDA05050107）
