%0 Journal Article
%T Landcover Classification of Remote Sensing Imagery Using Self organizing Neur al Network<br>自组织网络在遥感土地覆盖分类中应用研究
%A SUN Dan Feng
%A JI Chang Yuan
%A LIN Pei
%A <br>孙丹峰
%A 汲长远
%A 林培
%J 遥感学报
%D 1999
%I 
%X In this peaper,the implement and comparison of different self-organizing learning algorithm in landcover clas- sification of Landsat TM imagery it is found that with the combination of unsupervised and supervised learning method and the nearest neighbour principle these algorithms have no significant difference in classification accuracy .The study result shows that the self-organizing network is an another method to classify the landcover type in remote sensing imagery by combining the unsupervised and supervised learning phase with the nearest neighbour principle .Because of the sim- plicitv of the Simple Competivite Learning the self-organizing network can use the Simple Competivite Learning algorithm in remotely sensed data classification.
%K Self-organizing network
%K Unsupervised and Supervised learning
%K Kappa agreement coefficent
%K Overall accuracvg Z test<br>自组织网络
%K 遥感分类
%K 土地覆盖
%K 土地利用
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=C5125C6F1445703B&yid=B914830F5B1D1078&vid=38B194292C032A66&iid=0B39A22176CE99FB&sid=12DC19455C3A2FA8&eid=475189FCB44F11F6&journal_id=1007-4619&journal_name=遥感学报&referenced_num=13&reference_num=2