%0 Journal Article
%T Multi-temporal Remote Sensing Change Detection Using Dynamic Bayesian Networks<br>利用动态贝叶斯网络进行多时相遥感变化检测
%A Ouyang Yun
%A Ma Jian-wen
%A Dai Qin
%A <br>欧阳赟
%A 马建文
%A 戴芹
%J 电子与信息学报
%D 2007
%I 
%X Utilizing Dynamic Bayesian Networks (DBNs) to deal with multi-temporal remote sensing data, the multi-temporal data of different time can be input simultaneously, and the classification and the acquirement of relationships between the output types can be finished simultaneously. Using the Landsat TM remote sensing data of Beijing eastern area acquired in May of 1994, 2001 and 2003 for the experiment, the experimental results indicate that the DBN-based change detection method is a new effective method of remote sensing change detection, and show its great potential for the research on the analysis of the dynamic changes of remote sensing time-series data.
%K Bayesian Networks (BNs)
%K Dynamic Bayesian Networks (DBNs)
%K Remote sensing change detection<br>贝叶斯网络
%K 动态贝叶斯网络
%K 遥感变化检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=4008F58EC635E4A1&yid=A732AF04DDA03BB3&vid=771469D9D58C34FF&iid=38B194292C032A66&sid=811ACA5D3673A764&eid=385E3C2062167B88&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=22