一种建筑物群智能聚类法

建筑物聚类是大比例尺地图自动制图综合中需要解决的关键问题。通过分析Gestalt原理的邻近性、相似性等,采用建筑物重心、建筑物间的距离、建筑物与邻近线状地物要素间位置关系等参数描述建筑物。本文提出的建筑物智能聚类方法包含两个连续的步骤：首先计算建筑物的描述参数,利用SOM网络的聚类能力,进行建筑物的初步聚类;然后,利用SOM竞争层行列扫描的方法,对初步聚类的建筑物类簇进行精确划分,获得满足建筑物聚类的全局和局部约束条件等制图要求的建筑物聚类群组。...

Full description

Saved in:
Bibliographic Details
Published in测绘学报 Vol. 42; no. 2; pp. 290 - 294
Main Author 程博艳 刘强 李小文
Format Journal Article
LanguageChinese
Published 95007部队,广东广州510071%电子科技大学资源与环境学院,四川成都,611731 2013
电子科技大学资源与环境学院,四川成都611731
Subjects
Gestalt准则
地图综合
建筑物聚类
自组织映射网络（SOM）
自组织映射网络(SOM)
Gestalt准则
地图综合
建筑物聚类
Online AccessGet full text
ISSN1001-1595

Cover

More Information
Summary:建筑物聚类是大比例尺地图自动制图综合中需要解决的关键问题。通过分析Gestalt原理的邻近性、相似性等,采用建筑物重心、建筑物间的距离、建筑物与邻近线状地物要素间位置关系等参数描述建筑物。本文提出的建筑物智能聚类方法包含两个连续的步骤：首先计算建筑物的描述参数,利用SOM网络的聚类能力,进行建筑物的初步聚类;然后,利用SOM竞争层行列扫描的方法,对初步聚类的建筑物类簇进行精确划分,获得满足建筑物聚类的全局和局部约束条件等制图要求的建筑物聚类群组。
Bibliography:11-2089/P
Building grouping is a key problem in automated map generalization.Principles of Gestalt theories,i.e.proximity,similarity,and common directions,are analyzed.Three parameters,i.e.centroid coordinates,minimum distance between buildings,and location relationship between buildings and roads,are selected for building description.An approach is presented for intelligent building grouping.The process of building grouping consists of two consecutive steps.Firstly,the three parameters are calculated and recorded.Based on the clustering characteristic of self-organizing map（SOM）,buildings are clustered preliminarily.Secondly,a method of grouping the result of clusters based on SOM is applied.The SOM output layer is scanned row by row and column by column respectively.A further subdivision is accomplished to retrieve building groups complying with the global constraints of contextual features,the local constraints from Gestalt principles.
CHENG Boyan1,2,LIU Qiang1,LI Xiaowen1 1.School of Resources and Environme
ISSN:1001-1595