%0 Journal Article
%T Study on Automated Canal Selection<br>顾及网络特征的复杂人工河网的自动选取
%A WU Fang
%A TAN Xiao
%A WANG Hui-lian
%A ZHAI Ren-jian
%A WU Fang
%A TAN Xiao
%A WANG Hui-lian
%A ZHAI Ren-jian
%A WU Fang
%A TAN Xiao
%A WANG Hui-lian
%A ZHAI Ren-jian
%A WU Fang
%A TAN Xiao
%A WANG Hui-lian
%A ZHAI Ren-jian
%A <br>武芳
%A 谭笑
%A 王辉连
%A 翟仁健
%J 中国图象图形学报
%D 2007
%I 
%X This paper analyzes the character of the complex canal network, and imports the dynamic segmentation theory to organize the canal network data and its spatial knowledge. A method based on grid to detect the network density is put forward and the result show it is better than other method. And also a canal network selection model is set up based on decision of spatial knowledge. This model integrates five factors of the canal selection such as the attribute, length, link condition, spatial relation between canals and network density. Then, utilizes the multiple criteria decision to evaluate each canal by these five factors, and make alternated selection to preserve the whole network character.
%K automated map generalization
%K spatial relationship
%K multiple criteria decision model
%K dynamic Segmentation<br>自动综合
%K 空间关系
%K 多准则决策
%K 动态分段
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=787DC196C819EB68&yid=A732AF04DDA03BB3&vid=59906B3B2830C2C5&iid=B31275AF3241DB2D&sid=17FE7A1C78626A81&eid=8DABBEB130EFF191&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=7