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发布时间:2018-03-21 09:29:07     发布者:yz     浏览次数:

标题:On the degree correlation of urban road networks

作者:Tian, J (Tian, Jing); Fang, HQ (Fang, Huaqiang); Wang, YH (Wang, Yiheng); Ren, C (Ren, Chang)

来源出版物:TRANSACTIONS IN GIS卷:22期:1页码: 119-148 DOI: 10.1111/tgis.12299 出版年:FEB 2018

摘要:Recent advances in network science and the development of volunteered geographic information (VGI) have created new research opportunities in the topological analysis of road networks. The degree correlation of road networks is rarely studied. This study applied four measures, including the average degree of nearest neighbor, correlation profile, Newman's assortativity coefficient, and Litvak-Hofstad's assortativity coefficient, to measure the degree correlations of road networks represented as dual graphs of strokes, axial lines, and named roads. After investigating 100 road networks worldwide obtained from OpenStreetMap, it has been found that road networks are mostly disassortative or uncorrelated in stroke and named road representations, but assortative when represented as axial lines. Inconsistency in different measures persists regardless of method of representation; therefore, qualitative dichotomy or trichotomy is insufficient to describe the actual connection pattern in road networks. A taxonomy of road network assortativity is proposed. Two of the proposed disassortative types are associated with the absence of a grid pattern and are less robust than the typical disassortative type.

入藏号:WOS:000425596600007

文献类型:Article

语种:English

扩展关键词: STREET NETWORKS; COMPLEX NETWORKS; PATTERN; LINES

通讯作者地址:Ren, C (reprint author), Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

电子邮件地址:imrc@whu.edu.cn

地址:

[Tian, Jing; Wang, Yiheng; Ren, Chang] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

[Tian, Jing] Wuhan Univ, Key Lab Geog Informat Syst, Wuhan, Hubei, Peoples R China.

[Tian, Jing] Wuhan Univ, Natl Adm Surveying Mapping & Geoinformat, Key Lab Digital Mapping & Land Informat Applicat, Wuhan, Hubei, Peoples R China.

[Fang, Huaqiang] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing, Peoples R China.

[Ren, Chang] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China.

影响因子:2.252

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