测绘学报 ›› 2015, Vol. 44 ›› Issue (12): 1392-1400.doi: 10.11947/j.AGCS.2015.20150207

• 地理学与地理信息 • 上一篇    下一篇

顾及多空间相似性的地下管线数据匹配

龚敏霞1,2, 袁赛3, 储征伟4, 张书亮1,5, 房彩丽1   

  1. 1. 南京师范大学虚拟地理环境教育部重点实验室, 江苏 南京 210023;
    2. 江苏省国土资源信息中心, 江苏 南京 210017;
    3. 南京师范大学强化培养学院, 江苏 南京 210023;
    4. 南京市测绘勘察研究院有限公司, 江苏 南京 210019;
    5. 江苏省地理信息资源开发与利用协同创新中心, 江苏 南京 210023
  • 收稿日期:2015-04-20 修回日期:2015-10-15 出版日期:2015-12-20 发布日期:2016-01-04
  • 通讯作者: 张书亮,E-mail:zhangshuliang@njnu.edu.cn E-mail:zhangshuliang@njnu.edu.cn
  • 作者简介:龚敏霞(1976-),女,博士生,主要研究方向为空间相似性。E-mail:gmx@jsmlr.gov.cn
  • 基金资助:
    国家自然科学基金(41171301);江苏高校优势学科建设工程资助项目

Underground Pipeline Data Matching Considering Multiple Spatial Similarities

GONG Minxia1,2, YUAN Sai3, CHU Zhengwei4, ZHANG Shuliang1,5, FANG Caili1   

  1. 1. Key Laboratory of Virtual Geographic Environment for the Ministry of Education, Nanjing Normal University, Nanjing 210023, China;
    2. Information Center of Jiangsu of Land and Resources, Nanjing 210017, China;
    3. Honour School of Nanjing Normal University, Nanjing 210023, China;
    4. Nanjing Institute of Surveying, Mapping and Geotechnical Investigation, Co. Ltd, Nanjing 210019, China;
    5. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2015-04-20 Revised:2015-10-15 Online:2015-12-20 Published:2016-01-04
  • Supported by:
    The National Natural Science Foundation of China (No.41171301);A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

摘要: 综合地下管线与专业地下管线是同一管线地物的两种表达形式。综合地下管线数据精准、概括;专业地下管线数据表达范围广、属性信息翔实。本文以天然气管线数据为例,选取管点关联管段分布形态作为衡量依据计算管线结构相似性,从管点本体概念名称和属性两方面计算管线语义相似性,以两管点间管段分布形态为特征计算管线形状相似性。以此空间相似性构建管点特征向量,采用SVM(support vector machine)支持向量机的分类方法及管点唯一匹配原则实现管点实体匹配。试验表明该算法能够有效解决管点匹配问题。

关键词: 综合管线, 专业管线, 数据匹配, 空间相似性, SVM支持向量机

Abstract: Integrated and professional underground pipeline data are two forms of pipeline.Integrated underground pipeline data is accurate and general, while professional underground pipeline data expresses and contains detailed attribute information.Taking the data of natural gas pipeline as an example, this paper calculates structural similarity measured by the distribution pattern of pipelines that pipeline-point connects with, semantic similarity presented by the names and attributes of the pipeline-point ontology concept, and shape similarity characterized by the shape of arcs between two pipeline-points. The matching of pipe points is realized with the method of support vector machine classification algorithm and unique-matching principle combined with these spatial similarity. Test results show the matching of pipe points is well solved by the proposed algorithm.

Key words: integrated pipeline, professional pipeline, data matching, spatial similarity, support vector machine

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