顾及上下级空间关系相似性的道路网联动匹配方法

刘闯; 钱海忠; 王骁; 何海威; 陈竞男

doi:10.11947/j.AGCS.2016.20160062

测绘学报 >

2016 , Vol. 45 >Issue 11: 1371 - 1383

DOI: https://doi.org/10.11947/j.AGCS.2016.20160062

地图学与地理信息

顾及上下级空间关系相似性的道路网联动匹配方法

刘闯 ,
钱海忠 ,
王骁 ,
何海威 ,
陈竞男

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信息工程大学地理空间信息学院, 河南郑州 450052

刘闯(1992-),男,硕士生,研究方向为空间数据匹配与更新、自动制图综合。E-mail:liuchuang310@163.com

收稿日期: 2016-02-18

修回日期: 2016-06-27

网络出版日期: 2016-12-03

基金资助

国家自然科学基金（41171305；41571442）

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A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation

LIU Chuang ,
QIAN Haizhong ,
WANG Xiao ,
HE Haiwei ,
CHEN Jingnan

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Institute of Geospatial Information, Information Engineering University, Zhengzhou 450052, China

Received date: 2016-02-18

Revised date: 2016-06-27

Online published: 2016-12-03

Supported by

The National Natural Science Foundation of China (Nos.41171305; 41571442)

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摘要

现有道路网匹配方法中，大多利用道路自身结点和弧段特征进行匹配，而较少注意道路邻域要素在道路网匹配中的重要定位参考作用，从而影响匹配效率和正确率的进一步提高。针对上述问题，本文提出了一种顾及上下级空间关系相似性的道路网联动匹配方法，即模仿人在读图时通过特征地物和空间关联寻找目标地物的思维过程，将匹配看作是一种特征目标寻找、信息关联传递的推理过程。首先，运用Stroke技术将复杂道路网进行等级划分。其次，通过道路骨架关联关系树构建道路网联动匹配模型。最后，选取高等级骨干道路作为起始特征对象，计算道路间的上下级空间关系相似性，逐级迭代使匹配信息在道路网联动匹配模型中传递，从而得到匹配结果。试验表明，本文算法缩小了待匹配数据的搜索范围，能够有效提高匹配正确率和效率，尤其在数据位移较大、存在非系统性几何位置偏差的情况下优势明显。

关键词： 联动匹配; 空间关系; Stroke技术; 信息传递

本文引用格式

刘闯 , 钱海忠 , 王骁 , 何海威 , 陈竞男 . 顾及上下级空间关系相似性的道路网联动匹配方法[J]. 测绘学报, 2016 , 45(11) : 1371 -1383 . DOI: 10.11947/j.AGCS.2016.20160062

Abstract

Existing road network matching methods mostly use the characteristics of the road's own nodes and arcs to carry on the matching process, while less attention is focused on the importance of the road neighborhood elements in the road network matching, thus affecting further improvement of the matching efficiency and accuracy. In response to these problems, a linkage matching method for road network considering the similarity of upper and lower spatial relation is proposed. The linkage matching imitates the human thinking process of searching for target objects by the signal features and spatial correlation when reading maps, regarding matching as a reasoning process of goal feature searching and information association transmitting. Firstly, classify the complex road network by using Stroke technology. Secondly, establish the road network linkage matching model based on road skeleton relation tree. Finally, select the high-level road in the classifying results of the source data as the reference road to start matching, calculate the road between the upper and lower levels of the spatial relationship similarity, and through a step-by-step iteration, make the matching information transmit in the road network linkage matching model thus to obtain the final matching results. Experiment shows that the mentioned algorithm can narrow the search range of the data to be matched, effectively improving the match efficiency and accuracy, especially applicable to the data with large non systematic geometric location deviation.

Key words： linkage matching; spatial relations; Stroke technology; information transfer

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