测绘通报 ›› 2018, Vol. 0 ›› Issue (3): 66-70.doi: 10.13474/j.cnki.11-2246.2018.0077

• 行业观察 • 上一篇    下一篇

节点相似度辅助下的线要素匹配方法设计

方敏1, 霍亮2, 宋磊1, 鲍鹏1, 王锐1, 田军3   

  1. 1. 北京建筑大学测绘与城市空间信息学院, 北京 100044;
    2. 现代城市测绘国家测绘地理信息局重点实验室, 北京 100044;
    3. 北京城建勘测设计研究院有限责任公司, 北京 100101
  • 收稿日期:2017-09-08 出版日期:2018-03-25 发布日期:2018-04-03
  • 作者简介:方敏(1992-),女,硕士生,主要从事自主知识产权地理信息平台的研发。E-mail:2108160315003@stu.bucea.edu.cn
  • 基金资助:

    国家重点研发计划(2016YFC0803108)

Design of Linear Feature Matching Method Based on Node Similarity

FANG Min1, HUO Liang2, SONG Lei1, BAO Peng1, WANG Rui1, TIAN Jun3   

  1. 1. School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;
    2. Key Laboratory of Modern Urban Surveying and Mapping, National Administration of Surveying, Mapping and Geoinformation, Beijing 100044, China;
    3. Beijing Urban Construction Exploration & Surveying Design Research Institute Co. Ltd., Beijing 100101, China
  • Received:2017-09-08 Online:2018-03-25 Published:2018-04-03

摘要:

同名要素匹配是空间数据集成、更新和融合的关键技术。针对要素匹配中不同尺度数据构成差异但拓扑结构相似的问题,本文提出一种基于节点相似度的线要素匹配方法。该方法以线要素节点为主要特征,选取了方向、距离等相似性度量指标,并构建了拓扑、方向和距离三类约束,在此基础上,设计了一种基于拓扑关系和空间位置的匹配模型,实现了线要素特征点的相似性匹配。采用大规模道路网进行试验,试验结果表明,该方法切实可行,能够有效解决复杂线要素匹配问题。

关键词: 节点相似度, 拓扑关系, 空间位置, 线要素, 相似性匹配

Abstract:

Identifying homonymous elements is the key techniques to the integration,updating and fusion of spatial data.For the problems of linear feature with the same topology but different data structure,this paper proposes a matching method of linear feature based on node similarity.This method takes the node as the main feature,selects direction and distance similarity measure criteria,and constructs three kinds of constraints,such as topology,direction and distance.On this basis,a model of similarity matching is established based on topology and spatial location,and the similarity matching of characteristic points of linear feature is realized.Experiments are carried out on a large scale road network.The experiment results show that this method is feasible and can effectively deal with the matching problem of complex linear feature.

Key words: node similarity, topology, spatial location, linear feature, similarity matching

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