多元流视角下新疆绿洲城市网络格局研究

doi:10.12118/j.issn.1000-6060.2024.158

Abstract

Abstract:

The spatial flow of various elements continues to reshape intercity connections. Compared with urban network research from a single-element perspective, analyzing urban networks through a multi-element flow perspective provides a more comprehensive understanding of urban spatial patterns and better reflects the regional characteristics of these networks. Using Xinjiang, China as a case study, this article examines intercity interactions based on relational data related to aviation, population, railway, logistics, information, and technology, employing social network analysis to evaluate the structural characteristics of the oasis city network. The findings indicate: (1) Influenced by the distribution pattern of oases, the urban network in arid regions exhibits the overall characteristics of “single-core leadership+flat development”, centered on core cities. (2) The primacy of traffic flow and technology flow networks is more pronounced, whereas logistics and information flow networks are less dominated by the primacy city. Urban centrality is more evenly distributed, and the disparity between cities is minimal. (3) The logistics and information flow networks are dense and mature, exhibiting a multi-center network structure. In contrast, the traffic flow, population flow, and technology flow networks are primarily single-centered, displaying a “core-edge” structure. (4) To achieve high-quality development of Xinjiang’s oasis cities and optimize the urban spatial system, fostering regional growth poles, transitioning to a multi-center network structure, and enhancing regional innovation and complementarity should be prioritized.

Key words: multiple element flow, urban network, flow space, oasis city, Xinjiang

GUO Jiali, DU Hongru. Network pattern of oasis cities in Xinjiang from the perspective of multiple flows[J].Arid Land Geography, 2025, 48(2): 323-332.

Figures/Tables 8

Fig. 1

Tab. 1

Tab. 2

Measure index"

指标	计算公式	公式说明	表征意义
联系强度	$C i j = C i - j + C j - i$	$C i j$ 为城市i和城市j的联系强度； $C i - j$ 为城市i流向城市j的要素流强度； $C j - i$ 为城市j流向城市i的要素流强度	指各要素流网络中节点城市间的连接强度，联系强度越大，城市间要素的流动性越好
网络密度	$D = ∑ i = 1 n ∑ j = 1 n d i j n (n - 1) ， i ≠ j$	D为网络密度；n为城市节点数； $d i j$ 为城市i和城市j的联系强度	反映城市间的联系紧密度，网络密度越大城际联系越紧密，城市网络发育越成熟^[22]
点度中心度	$C D (i) = ∑ j = 1 n X i j n - 1$	$C D (i)$ 为城市i的点度中心度； $X i j$ 为城市i和城市j的联系强度；n为城市节点数	刻画网络中节点的重要程度，出度衡量节点的辐射能力，入度衡量节点的集聚能力^[30]
中间中心度	$C B (n i) = ∑ j < k m j k (n i) m j k (m - 1) (m - 2)$	$C B (n i)$ 为中间中心度； $m j k$ 为城市j到k的最短路径数； $m j k (n i)$ 为节点j与节点k之间经过节点i的最短路径数	衡量网络中节点城市所具有的控制其他2个城市的交流能力，中间中心度越大，城市的资源控制能力越强^[31]

Tab. 2

Fig. 2

Fig. 3

Tab. 3

Fig. 4

Tab. 4

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类型	数据	来源	时段
航空流数据	航空客运班次	OAG航空数据库（https://oag.cn/）	2023年3月6—12日
人口流数据	城市迁入（迁出）规模指数、人口迁入（迁出）百分比	百度迁徙平台（https://qianxi.baidu.com/）	2023年2月、4月、7月1日至8月11日，共计100 d
信息流数据	基于双向搜索规则的城市日平均搜索指数	百度指数官网（https://index.baidu.com/）	2023年1月1日至10月11日
铁路流数据	普速和高速铁路客运班次	12306官网（https://www.12306.cn/）	2023年9月5日
技术流数据	发明、实用新型专利转移数据	国家知识产权局（https://www.cnipa.gov.cn/）	2018—2022年
物流数据	物流线路	阿里巴巴菜鸟运输市场（https://56.1688.com/）	2023年3月1日

城市	点度中心度		中间中心度	城市	点度中心度		中间中心度
城市	点出度	点入度	中间中心度	城市	点出度	点入度	中间中心度
乌鲁木齐市	60.11	58.32	36.90	石河子市	31.19	24.93	0.97
喀什地区	34.42	31.99	7.86	哈密市	23.63	25.54	0.04
伊犁州直	33.51	33.19	1.14	和田地区	23.58	24.75	0.10
阿克苏地区	32.08	32.22	6.61	博州	23.11	24.73	0.15
巴州	28.05	32.07	2.53	阿勒泰地区	17.02	16.52	0.00
昌吉州	26.69	30.87	1.28	图木舒克市	18.68	15.74	0.00
塔城地区	25.56	28.11	0.20	阿拉尔市	16.94	17.85	0.00
克拉玛依市	27.43	26.33	0.18	克州	16.24	15.58	0.00
吐鲁番市	25.39	26.26	0.26	五家渠市	12.60	11.25	0.00
平均值	26.46	26.46	3.23

联系级别	城市联系		关联强度		层级集聚度
联系级别	数量	数量占比/%	总量	强度占比/%	层级集聚度
一级联系	10	6.54	4.89	22.78	3.48
二级联系	16	10.46	4.12	19.19	1.83
三级联系	58	37.90	9.10	42.38	1.12
四级联系	69	45.10	3.36	15.65	0.35

Network pattern of oasis cities in Xinjiang from the perspective of multiple flows

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