东非共同体区域城市网络结构

doi:10.3969/j.issn.1004-9479.2025.03.20240451

摘要/Abstract

摘要：

随着人口增长和城市化快速发展，非洲等欠发达地区的城市网络形成过程及其结构特征引起了学者们的关注。基于航空流、城市人口和道路等级数据，构建东非共同体区域的城市网络并分析其结构特征，评估城市在网络中的中心性和控制功能。结果表明：①引力模拟网络由77个节点和543条边相互连接，呈现出由多个中心串联的半弧形结构。处于前25%的节点主要分布在区域中部，包括内罗毕及其周围中小城镇，以及坎帕拉、基加利、阿鲁沙、姆万扎、蒙巴萨等大中城市；②航空网络包含51个节点和147条航线，与模拟网络的差异在于强化了内罗毕、达累斯萨拉姆、坎帕拉等首位城市的地位，同时提升了马赛马拉等旅游性城市的转变中心性；③将复合网络中91个节点城市以转变中心性和控制力值为依据，划分为区域级、国家级和地方级，3类节点的数量呈金字塔结构，数量之比为1∶6∶84。马赛马拉是最接近区域性枢纽城市的节点，达累斯萨拉姆接近区域级门户城市，多多马、姆万扎等次区域中心则具有进一步发展的潜力。

关键词: 城市体系, 航空网络, 引力模型, 中心性, 城市地位

Abstract:

With the rapid development of population and urbanization, the structural characteristics of urban networks in underdeveloped areas like Africa have attracted attention. Based on data such as air flow, urban population, and road grades, this study constructed the regional urban network of the East African Community, analyzed its structural characteristics, and evaluated the centrality and power of cities. The results indicate: ①The gravity simulation network, consisting of 77 nodes and 543 edges, forms a semi-arc structure connected by multiple central hubs.The top 25% of nodes are primarily located in the central region, including Nairobi and its surrounding small and medium towns, as well as major cities like Kampala, Kigali, Arusha, Mwanza, and Mombasa. ②The airline network with 51 nodes and 147 routes, differs from the simulation network by strengthening the prominence of key cities such as Nairobi, Dar es Salaam, and Kampala, while also increased and enhanced alter-based centrality of tourist cities like Maasai Mara. ③The composite network categorizes 91 nodes based on alter-based centrality and power value into regional, national, and local levels, with the distribution of nodes following a pyramid structure in a ratio of 1:6:84. Maasai Mara emerges as the node closest to becoming a regional hub, Dar es Salaam is approaching regional gateway status, and sub-regional centers like Dodoma and Mwanza show potential for further development.

Key words: urban system, airline network, Gravity Model, centrality, urban positionality

刘圳南, 陈爽, 顾伟男. 东非共同体区域城市网络结构[J]. 世界地理研究, 2025, 34(3): 117-128.

Zhennan LIU, Shuang CHEN, Weinan GU. Regional urban network structure of the East African Community: An analysis based on Gravity Model and air flow[J]. World Regional Studies, 2025, 34(3): 117-128.

图/表 5

表1 城市网络分析指标及含义

Tab.1 Analysis indicators and meanings in urban network analysis

指标	公式	含义	来源
度数	$D C i = ∑ j = 1, j ≠ i n a i j$	指与城市i相连接的城市数量。式中，若城市i和城市j之间存在联系，则 $a i j$ =1；若不存在联系，则 $a i j$ =0	—
加权度数	$W D C i = ∑ j = 1, j ≠ i n a i j × R i j$	指城市i与网络中其他城市之间联系强度的总和。式中， $R i j$ 为城市i与j之间的联系强度，通过引力、航班次数等量化	—
转变中心性	$A C i = ∑ j = 1, j ≠ i n 1 - d i j) × R i j × D C j$ $其中 d i j = R i j W D C i$	代表城市i在网络中对于资源要素的集聚和扩散能力。为消除存在路径依赖的城市转变中心性过大的影响，加入依存度系数 $d i j$ 修正城市间位置差异，下同	Neal（2013）^[25]，赵梓渝等(2017)^[37]
转变控制力	$A P i = ∑ j = 1, j ≠ i n 1 - d i j) × R i j D C j$	代表城市i在网络中对资源流动的控制能力	Neal（2013）^[25]，赵梓渝等(2017)^[37]

表1 城市网络分析指标及含义

Tab.1 Analysis indicators and meanings in urban network analysis

指标	公式	含义	来源
度数	$D C i = ∑ j = 1, j ≠ i n a i j$	指与城市i相连接的城市数量。式中，若城市i和城市j之间存在联系，则 $a i j$ =1；若不存在联系，则 $a i j$ =0	—
加权度数	$W D C i = ∑ j = 1, j ≠ i n a i j × R i j$	指城市i与网络中其他城市之间联系强度的总和。式中， $R i j$ 为城市i与j之间的联系强度，通过引力、航班次数等量化	—
转变中心性	$A C i = ∑ j = 1, j ≠ i n 1 - d i j) × R i j × D C j$ $其中 d i j = R i j W D C i$	代表城市i在网络中对于资源要素的集聚和扩散能力。为消除存在路径依赖的城市转变中心性过大的影响，加入依存度系数 $d i j$ 修正城市间位置差异，下同	Neal（2013）^[25]，赵梓渝等(2017)^[37]
转变控制力	$A P i = ∑ j = 1, j ≠ i n 1 - d i j) × R i j D C j$	代表城市i在网络中对资源流动的控制能力	Neal（2013）^[25]，赵梓渝等(2017)^[37]

图2 东非共同体区域城市引力模拟网络

Fig.2 Urban gravity simulation network of East African Community regional

图3 东非共同体区域城市航空网络

Fig.3 Urban airline network of East African Community regional

表2 区域城市网络中城市的转变中心性与控制力

Tab.2 Alter-based centrality and power of cities in the regional urban network

排名	引力模拟网络				航空网络
排名	城市	转变中心性	城市	控制力	城市	转变中心性	城市	控制力
1	内罗毕	1.000	内罗毕	1.000	内罗毕	1.000	内罗毕	1.000
2	坎帕拉	0.147	坎帕拉	0.243	马赛马拉	0.992	马赛马拉	0.604
3	锡卡	0.078	达累斯萨拉姆	0.221	阿鲁沙	0.491	达累斯萨拉姆	0.529
4	阿西里弗	0.067	蒙巴萨	0.123	桑吉巴尔	0.436	阿鲁沙	0.240
5	龙盖	0.058	基加利	0.083	达累斯萨拉姆	0.435	桑吉巴尔	0.213
6	达累斯萨拉姆	0.052	布琼布拉	0.049	蒙巴萨	0.266	坎帕拉	0.137
7	纳库鲁	0.049	锡卡	0.047	曼雅拉湖	0.213	曼雅拉湖	0.101
8	埃尔多雷特	0.042	埃尔多雷特	0.036	坎帕拉	0.210	塞罗内拉	0.101
9	蒙巴萨	0.041	阿西里弗	0.035	格鲁美禁猎区	0.202	蒙巴萨	0.097
10	阿鲁沙	0.030	纳库鲁	0.032	塞罗内拉	0.198	格鲁美禁猎区	0.094

图4 基于转变中心性与控制力的城市类型划分

Fig.4 Types of cities based on alter-based centrality and power

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