Acta Geodaetica et Cartographica Sinica >

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

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

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
Expand
  • 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)

Fold

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

Cite this article

LIU Chuang , QIAN Haizhong , WANG Xiao , HE Haiwei , CHEN Jingnan . A Linkage Matching Method for Road Networks Considering the Similarity of Upper and Lower Spatial Relation[J]. Acta Geodaetica et Cartographica Sinica, 2016 , 45(11) : 1371 -1383 . DOI: 10.11947/j.AGCS.2016.20160062

References

[1] QUDDUS M A, OCHIENG W Y, NOLAND R B. Map Matching Algorithms for Intelligent Transport Systems Applications[C]//Proceedings of the 13th World Congress on Intelligent Transport Systems and Services. London: ITRD, 2006.
[2] WALTER V, FRITSCH D. Matching Spatial Data Sets: A Statistical Approach[J]. International Journal of Geographical Information Science, 1999, 13(5): 445-473.
[3] MANTEL D, LIPECK U. Matching Cartographic Objects in Spatial Databases[C]//Proceedings of the ISPRS Congress, Commission 4. Istanbul, Turkey: ISPRS, 2004.
[4] ZHANG Meng, MENG Liqiu. An Iterative Road-matching Approach for the Integration of Postal Data[J]. Computers, Environment and Urban Systems, 2007, 31(5): 597-615.
[5] GABAY Y, DOYTSHER Y. Adjustment of Line Maps[C]//Proceedings of the GIS/LIS'94. Phoenix, Arizona:[s.n.], 1994: 191-199.
[6] MUSTIÈRE S. Results of Experiments on Automated Matching of Networks at Different Scales[C]//Proceedings of the ISPRS Workshop:Multiple Representation and Interoperability of Spatial Data. Hannover, Germany: ISPRS, 2006.
[7] MUSTIÈRE S, DEVOGELE T. Matching Networks with Different Levels of Detail[J]. GeoInformatica, 2008, 12(4): 435-453.
[8] DENG Min, LI Zhilin, CHEN Xiaoyong. Extended Hausdorff Distance for Spatial Objects in GIS[J]. International Journal of Geographical Information Science, 2007, 21(4): 459-475.
[9] ZHANG Meng, SHI Wei, MENG Liqiu. A Generic Matching Algorithm for Line Networks of Different Resolutions[C]//Proceedings of the 8th ICA Workshop on Generalisation and Multiple Representation. Coruña, Spain:[s.n.], 2005.
[10] 陈玉敏, 龚健雅, 史文中. 多尺度道路网的距离匹配算法研究[J]. 测绘学报, 2007, 36(1): 84-90. DOI: 10.3321/j.issn:1001-1595.2007.01.015. CHEN Yumin, GONG Jianya, SHI Wenzhong. A Distance-based Matching Algorithm for Multi-scale Road Networks[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(1): 84-90. DOI: 10.3321/j.issn:1001-1595.2007.01.015.
[11] ZHANG M. Methods and Implementations of Road-network Matching[D]. Munich, Germany: Technical University of Munich, 2009: 47-94.
[12] 童小华, 邓愫愫, 史文中. 基于概率的地图实体匹配方法[J]. 测绘学报, 2007, 36(2): 210-217. DOI: 10.3321/j.issn:1001-1595.2007.02.017. TONG Xiaohua, DENG Susu, SHI Wenzhong. A Probabilistic Theory-based Matching Method[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(2): 210-217. DOI: 10.3321/j.issn:1001-1595.2007.02.017.
[13] 赵东保, 盛业华. 全局寻优的矢量道路网自动匹配方法研究[J]. 测绘学报, 2010, 39(4): 416-421. ZHAO Dongbao, SHENG Yehua. Research on Automatic Matching of Vector Road Networks Based on Global Optimization[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(4): 416-421.
[14] 张云菲, 杨必胜, 栾学晨. 利用概率松弛法的城市路网自动匹配[J]. 测绘学报, 2012, 41(6): 933-939. ZHANG Yunfei, YANG Bisheng, LUAN Xuechen. Automated Matching Urban Road Networks Using Probabilistic Relaxation[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(6): 933-939.
[15] 刘海龙, 钱海忠, 王骁, 等. 采用层次分析法的道路网整体匹配方法[J]. 武汉大学学报(信息科学版), 2015, 40(5): 644-651. LIU Hailong, QIAN Haizhong, WANG Xiao, et al. Road Networks Global Matching Method Using Analytical Hierarchy Process[J]. Geomatics and Information Science of Wuhan University, 2015, 40(5): 644-651.
[16] 刘海龙, 钱海忠, 黄智深, 等. 采用Stroke层次结构模型的道路网匹配方法[J]. 测绘科学技术学报, 2013, 30(6): 647-651, 657. LIU Hailong, QIAN Haizhong, HUANG Zhishen, et al. Road Network Matching Method with Stroke-hierarchical Model[J]. Journal of Geomatics Science and Technology, 2013, 30(6): 647-651, 657.
[17] THOMSON R C, RICHARDSON D E. The "Good Continuation" Principle of Perceptual Organization Applied to the Generalization of Road Networks[C]//Proceedings of the 19th International Cartographic Conference. Ottawa, Canada:[s.n.], 1999: 1215-1223.
[18] THOMSON R C. The Stroke Concept in Geographic Network Generalization and Analysis[C]//Proceedings of the 12th International Symposium on Spatial Data Handling. Vienna, Austria:[s.n.], 2006: 681-697.
[19] ANG Y H, LI Z, ONG S H. Image Retrieval Based on Multidimensional Feature Properties[C]//Proceedings of the SPIE 2420, Storage and Retrieval for Image and Video Databases III. San Jose, CA: SPIE, 1995: 47-57.
[20] 翟仁健. 基于全局一致性评价的多尺度矢量空间数据匹配方法研究[D]. 郑州: 信息工程大学, 2011: 31-36. ZHAI Renjian. Research on Automated Matching Methods for Multi-scale Vector Spatial Data Based on Global Consistency Evaluation[D]. Zhengzhou: Information Engineering University, 2011: 31-36.
[21] 钱海忠, 张钊, 翟银凤, 等. 特征识别、Stroke与极化变换结合的道路网选取[J]. 测绘科学技术学报, 2010, 27(5): 371-374, 378. QIAN Haizhong, ZHANG Zhao, ZHAI Yinfeng, et al. Road Selection Method Based on Character Recognition, Stroke and Polarization Transformation[J]. Journal of Geomatics Science and Technology, 2010, 27(5): 371-374, 378.
[22] 钱海忠, 武芳, 朱鲲鹏, 等. 一种基于降维技术的街区综合方法[J]. 测绘学报, 2007, 36(1): 102-107, 118. QIAN Haizhong, WU Fang, ZHU Kunpeng, et al. A Generalization Method of Street Block Based on Dimension-reducing Technique[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(1): 102-107, 118.
[23] 何海威, 钱海忠, 刘海龙, 等. 道路网层次骨架控制的道路选取方法[J]. 测绘学报, 2015, 44(4): 453-461. DOI: 10.11947/j.AGCS.2015.20130787. HE Haiwei, QIAN Haizhong, LIU Hailong, et al. Road Network Selection Based on Road Hierarchical Structure Control[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(4): 453-461. DOI: 10.11947/j.AGCS.2015.20130787.
[24] 杨敏, 艾廷华, 周启. 顾及道路目标Stroke特征保持的路网自动综合方法[J]. 测绘学报, 2013, 42(4): 581-587, 594. YANG Min, AI Tinghua, ZHOU Qi. A Method of Road Network Generalization Considering Stroke Properties of Road Object[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(4): 581-587, 594.
[25] EGENHOFER M J, FRANZOSA R D. Point-set Topological Spatial Relations[J]. International Journal of Geographical Information Systems, 1991, 5(2): 161-174.
[26] EGENHOFER M J, MARK D M. Naive Geography[M]//FRANK A U, KUHN W. Spatial Information Theory:A Theoretical Basis for GIS. Berlin: Springer, 1995: 1-15.
[27] 刘涛, 杨树文, 李轶鲲, 等. 空间线群目标方向相似度计算模型[J]. 测绘科学, 2013, 38(1): 156-159. LIU Tao, YANG Shuwen, LI Yikun, et al. Direction Similarity Calculation Model of Spatial Line Groups[J]. Science of Surveying and Mapping, 2013, 38(1): 156-159.
[28] 刘涛. 空间群(组)目标相似关系及计算模型研究[D]. 武汉: 武汉大学, 2011: 45-57. LIU Tao. Similarity of Spatial Group Objects[D]. Wuhan: Wuhan University, 2011: 45-57.
Options
Outlines

/

〈 〉