复杂网络视角下的成渝城市群网络结构韧性演变

doi:10.3969/j.issn.1004-9479.2022.03.2020538

摘要/Abstract

摘要：

城市网络结构韧性是影响区域可持续发展的关键因素之一。分析城市网络结构韧性，找到结构薄弱环节，调整网络结构和优化区域资源配置，对促使区域稳定协调发展具有重要意义。以成渝城市群为研究对象，基于2014年与2018年的公路、铁路客运班次数据和百度指数大数据分别构建交通和信息联系网络，运用复杂网络理论借助Ucinet网络分析工具从网络整体完备度、网络结构特征、网络聚集性3个方面，网络密度、平均路径长度、度分布曲线斜率、“核心-边缘”结构拟合度、局部聚类系数和平均聚类系数6个指标对城市群网络韧性演变进行分析。结果表明：在研究时段内，交通联系网络的初始韧性弱于信息联系网络，后期韧性能力有所提高并强于信息联系网络，网络结构由松散、单极的弱连接状态演化为联系紧密、均衡复杂的稳定状态；信息联系网络的韧性能力相对于2014年大幅减弱，网络完备度下降，核心区域封闭性加剧，信息流传输路径单一，网络联系分布不均衡，网络结构抗干扰性弱；成渝城市群网络整体仍处于发展阶段，网络化程度较弱，韧性能力不足。最后对成渝城市群网络韧性现状进行了讨论，进而提出优化建议。

关键词: 成渝城市群, 网络拓扑结构, 复杂网络, 韧性

Abstract:

The resilience of urban network structure is one of the key factors affecting the sustainable development of the region. Analyzing the resilience of the urban network structure, finding structural weaknesses, adjusting the network structure and optimizing the allocation of regional resources are of great significance to promoting the stable and coordinated development of the region. Taking the Chengdu-Chongqing urban agglomeration as the research object, constructing traffic and information connection networks based on highway and railway passenger traffic data and Baidu index big data, using complex network theory and Ucinet network analysis tools to analyze the overall completeness of the network, network structure characteristics, and network aggregation In three aspects, network density, average path length, slope of degree distribution curve, core edge structure fit, local clustering coefficient and average clustering coefficient are six indicators to analyze the evolution of urban agglomeration network resilience. The results show that the initial resilience of the traffic connection network is weaker than that of the information connection network, and the later resilience is improved and stronger than the information connection network. The network structure has evolved from a loose, unipolar weak connection state to a tightly connected, balanced and complex stable state; The resilience of the information connection network is relatively weaker than in 2014, the completeness of the network has declined, the closure of the core area has increased, the information flow transmission path is single, the network connection is unevenly distributed, and the network structure is weak against interference; the overall network of the Chengdu-Chongqing city cluster remains In the development stage, the degree of networking is weak and the resilience ability is insufficient. Finally, the network resilience status of Chengdu-Chongqing urban agglomeration was discussed, and then optimization suggestions were put forward.

Key words: Chengdu-Chongqing urban agglomeration, network topology, complex network, resilience

侯兰功, 孙继平. 复杂网络视角下的成渝城市群网络结构韧性演变[J]. 世界地理研究, 2022, 31(3): 561-571.

Langong HOU, Jiping SUN. Evaluation of network structure resilience of Chengdu-Chongqing urban agglomeration from the perspective of complex networks[J]. World Regional Studies, 2022, 31(3): 561-571.

图/表 8

图 1 研究区示意图

Fig.1 Scope of the study area

图 2 成渝城市群交通联系网络（a）和信息联系网络（b）

Fig.2 The transportation network （a） and information network （b） of Chengyu urban agglomeration

图 3 成渝城市群交通网络拓扑结构（a）和信息网络拓扑结构（b）

Fig. 3 The topological structure of the transportation network （a） and information network （b） of Chengyu urban agglomeration

表 1 城市网络结构韧性指标

Tab.1 Urban network structural resilience indicators

指标	年份	网络密度D	平均路径长度L	度分布曲线斜率a	核心-边缘结构拟合度	平均聚类系数C
交通联系网络	2014	0.279	1.632	-1.9221	0.573	0.719
交通联系网络	2018	0.333	1.700	-1.491	0.543	0.755
信息联系网络	2014	0.321	1.642	-1.8071	0.832	0.837
信息联系网络	2018	0.300	1.700	-1.6340	0.896	0.869

表 2 成渝城市群城市局部聚类系数统计

Tab.2 Statistics of local clustering coefficients of Chengyu urban agglomeration

变量	年份	成都	重庆	德阳	眉山	雅安	资阳	内江	南充
交通	2014	0.263	0.833	1.000	0.750	-	0.567	0.917	0.833
交通	2018	0.200	0.253	0.750	0.667	-	1.000	1.000	0.750
信息	2014	0.267	0.267	1.000	1.000	1.000	1.000	1.000	0.667
信息	2018	0.200	0.200	1.000	1.000	1.000	1.000	1.000	1.000
变量	年份	达州	宜宾	广安	自贡	泸州	遂宁	乐山	绵阳
交通	2014	0.667	0.700	0.667	0.917	-	0.482	0.467	1.000
交通	2018	1.000	0.700	0.833	0.750	1.000	0.917	0.750	0.750
信息	2014	0.800	0.800	1.000	0.900	0.900	1.000	1.000	0.800
信息	2018	1.000	0.833	1.000	1.000	1.000	1.000	1.000	0.667

图 4 交通网络度值（a）和信息网络度值（b）空间分布

Fig.4 Spatial distribution of traffic network degree value （a） and information network degree value（b）

图 5 交通联系网络（a）和信息联系网络（b） “核心-边缘”划分

Fig.5 " Core-periphery" division of the transportation network （a） and information network （b）

图 6 交通联系网络（a）和信息联系网络（b）局部聚类系数空间分布

Fig.6 The spatial distribution of local clustering coefficients in the traffic network and information network

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