多元流视角下黄河流域城市网络空间结构及其影响因素

doi:10.13249/j.cnki.sgs.2022.10.010

地理科学 ›› 2022, Vol. 42 ›› Issue (10): 1778-1787.doi: 10.13249/j.cnki.sgs.2022.10.010

多元流视角下黄河流域城市网络空间结构及其影响因素

赵金丽¹(), 张学波²(), 任嘉敏¹, 陈肖飞³

1.山东师范大学地理与环境学院，山东济南 250358
2.曲阜师范大学地理与旅游学院，山东日照 276800
3.河南大学黄河文明与可持续发展研究中心暨黄河文明省部共建协同创新中心，河南开封 475001

收稿日期:2021-02-12 修回日期:2021-10-10 出版日期:2022-10-10 发布日期:2022-12-06
通讯作者: 张学波 E-mail:zhaojinli302@126.com;xuebozhang@126.com
作者简介:赵金丽（1989−），女，山东聊城人，博士，讲师，主要从事城市地理和金融地理研究。E-mail: zhaojinli302@126.com
基金资助:
教育部人文社会科学青年基金项目(19YJCZH262);国家自然科学基金项目(42071150)

Spatial Structure and Influencing Factors of Urban Network in the Yellow River Basin Based on Multiple Flows

Zhao Jinli¹(), Zhang Xuebo²(), Ren Jiamin¹, Chen Xiaofei³

1. College of Geography and Environment, Shandong Normal University, Jinan 250358, Shandong, China
2. School of Geography and Tourism, Qufu Normal University, Rizhao 276800, Shandong, China
3. Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization, Henan Province and Ministry of Education, Henan University, Kaifeng 475001, Henan, China

Received:2021-02-12 Revised:2021-10-10 Online:2022-10-10 Published:2022-12-06
Contact: Zhang Xuebo E-mail:zhaojinli302@126.com;xuebozhang@126.com
Supported by:
Social Science Humanity Foundation of Education Ministry(19YJCZH262);National Natural Science Foundation of China(42071150)

摘要/Abstract

摘要：

运用社会网络分析方法，从金融、信息和交通等多要素流视角对黄河流域城市网络的层级、格局与方向进行了分析，并借助QAP回归分析方法揭示其空间结构的影响因素。结果表明：① 黄河流域各要素城市网络中心性地区差异显著，交通网络差异最大且规模分布最为集中，西部中小城市交通发展滞后；信息网络差异较小，人口大市和旅游城市中心性较高；金融网络差异最小且规模分布最为分散，东部地区整体优势最为显著。② 黄河流域主干金融网络连通了流域各中心城市及山东、河南各市，形成菱形网络；主干信息网络呈现为以省域中心城市为核心的若干星形组团；主干交通网络以主要交通干线为轴，形成轴辐式网络，且各主干网络均是以西安、郑州和济南为核心。③ 城市间金融联系择优连接最为明显，信息联系以择优连接为主，在河南、山东表现出一定的邻近连接，交通联系邻近连接特征最为明显，形成若干交通次中心。④ 城市全球化水平、行政等级和政府职能转变力度及省际行政壁垒是影响黄河流域城市网络空间结构的主要因素。

关键词: 黄河流域, 多要素流, 城市网络, 社会网络分析

Abstract:

Based on finance, information and traffic flow, the urban network structure of the Yellow River Basin is analyzed from the perspective of hierarchy, pattern, direction and influencing factors by using social network analysis method. The results show that: 1) There are significant regional differences in the centrality of the urban network based on various factor flows in the Yellow River Basin. The traffic network has the largest difference and the most concentrated size distribution, and the traffic development of small and medium-sized cities in the western China lags behind. The difference of information network is relatively small and the centrality of cities with large population or rich tourism resources is relatively high. The financial network has the smallest difference and the most decentralized size distribution, and the eastern region has the most significant overall advantage. 2) The backbone financial network has connected the central cities of the basin and the cities of Shandong and Henan, forming a diamond network; the backbone information network appears as several star clusters with the provincial central cities as the core; the backbone traffic network is composed of several groups with the traffic trunk as the axis, and the backbone networks are all centered on Xi'an, Zhengzhou and Jinan. 3) The preferential attachment and geographic proximity interactions are important mechanisms in the development of basin urban network. The financial network is absolutely dominated by the preferential attachment; the information network is also dominated by the preferential connection, but it shows certain geographical proximity features in Shandong and Henan; while the transportation network is dominated by the geographical proximity interaction, forming several traffic sub-centers. 4) The level of globalization, administrative hierarchy and government functional transformation, and provincial boundary barriers are the main factors influencing the urban network spatial structure in the Yellow River Basin.

Key words: the Yellow River Basin, multiple factor flows, urban network, social network analysis

中图分类号:

K902

赵金丽, 张学波, 任嘉敏, 陈肖飞. 多元流视角下黄河流域城市网络空间结构及其影响因素[J]. 地理科学, 2022, 42(10): 1778-1787.

Zhao Jinli, Zhang Xuebo, Ren Jiamin, Chen Xiaofei. Spatial Structure and Influencing Factors of Urban Network in the Yellow River Basin Based on Multiple Flows[J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(10): 1778-1787.

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类型	变量	金融网络	信息网络	交通网络
注：^、、**分别表示10%、5%、1%的水平上显著。
全球化	外商直接投资差值	0.279^***	0.279^***	0.163^***
市场化	产业结构差异性	0.083^*	0.068^**	0.045^*
分权化	城市行政等级0-1网络	0.427^***	0.364^***	0.128^***
分权化	政府干预程度差值	−0.353^***	−0.079^***	−0.060^***
一体化	省级行政边界0-1网络	0.212^***	0.349^***	0.306^***
	地区行政边界0-1网络	−0.102^***	0.024	0.027
	自然区边界0-1网络	0.011	0.054^***	0.077^***
R²		0.500	0.397	0.183

多元流视角下黄河流域城市网络空间结构及其影响因素

Spatial Structure and Influencing Factors of Urban Network in the Yellow River Basin Based on Multiple Flows

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		金融网络		信息网络		交通网络
		Top1	Top3	Top1	Top3	Top1	Top3
全部中心节点数		9	9	12	34	29	58
前3名节点连接比重/%		59.8	68.8	49.4	40.4	39.0	21.8
连接城市总数量	西安	34	70	15	60	9	19
	郑州	24	77	17	24	16	20
	济南	27	87	11	15	6	14
	太原	17	34	10	10	7	10
	兰州	6	17	12	23	6	14
	呼和浩特	12	14	5	7	4	9
	青岛	6	24	5	24	0	4
	银川	10	11	4	6	3	6
	西宁	6	6	7	7	3	3
连接省区外城市数量	西安	25	61	6	51	1	11
	郑州	7	60	0	7	1	4
	济南	12	72	0	0	0	0
	太原	7	24	0	0	0	0
	兰州	6	6	0	10	1	6
	呼和浩特	7	9	0	1	0	3
	青岛	6	19	0	9	0	0
	银川	7	7	0	2	0	2
	西宁	0	6	0	0	0	0