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多维要素流视角下成渝城市群空间结构特征研究
张扬1, 李娟2, 王兴平1
1.东南大学;2.成都理工大学
摘要:
随着交通、通讯设施的日益完善与经济的快速发展,城市间各类要素流动更为频繁并形成城市网络,促进“流空间”成为区域空间结构研究新范式。相比单一要素流,多维要素流可以从更加综合的视角刻画城市群内部网络联系,识别城市群空间结构特征。本文通过集成百度迁徙、快递物流线路、百度指数、企业总部-分支、科技论文合作等多元地理流数据建立成渝城市群人流、物流、信息流、资金流、技术流及综合流网络,借助社会网络分析方法识别网络节点特征并结合位序-规模法则评估城市体系规模结构,利用核密度分析法识别多维要素流动主要廊道,结合优势流和DBSCAN聚类分析成渝城市群空间组团特征。结果表明:①在多维要素流网络中,各节点层级分化明显,成都市、重庆市分别是“一主一副”中心节点城市,对多维要素流的集聚扩散能力突出,而其他城市普遍发育不足。②重庆市-成都市关联区间联系强度最高,成都市、重庆市与14个地级市组成的关联区间次之,14个地级市之间组成的关联区间最低,成渝发展主轴、成德绵乐城市带是要素流动的主要廊道。③在优势流约束下,成渝城市群内部形成成都-德阳-眉山、重庆-广安、南充-遂宁、内江-自贡-宜宾-泸州、乐山-雅安共5个空间聚类,其中南充-遂宁、内江-自贡-宜宾-泸州具备培育都市圈的潜力。结合本文分析结果和现有规划,建议将多维要素流网络中心度相对较高的绵阳、南充、宜宾作为次级中心城市培育,在重点发展成都都市圈、重庆都市圈的同时着力培育南充-遂宁、内自宜泸两大都市圈,促进绵阳市、雅安市、乐山市、达州市等圈群空隙城市差异化、特色化发展,强化宜宾-泸州-重庆沿江发展轴,逐步优化成渝城市群空间结构,形成区域协调发展新格局。
关键词:  空间结构  多维要素流  社会网络分析  位序-规模  核密度估计  DBSCAN聚类  成渝城市群
DOI:
分类号:TU982
基金项目:国家自然科学(52078115);四川省软科学研究计划项目(2023JDR0094)
Spatial structure characteristics of Chengdu-Chongqing Urban Agglomeration from the perspective of multi-dimensional factor flows
zhang yang,Li Juan,Wang xingping
Abstract:
With the increasingly perfect transportation and communication facilities and rapid economic development, various factor flows more frequently between cities and form a city network, promoting the" space of flow " to become a new paradigm for regional spatial structure research. Compared with single factor flow, multi-dimensional factor flows can depict the network connection and identify the spatial structure characteristics of the urban agglomeration from a more comprehensive perspective. This paper establishes networks of people flow, logistics flow, information flow, capital flow, technology flow, and comprehensive flow in the Chengdu-Chongqing urban agglomeration by integrating multi-dimensional geographic flow data such as Baidu Migration, express logistics routes, Baidu Index, headquarters-branches of enterprises, and paper cooperation. By using social network analysis to identify network node characteristics and combining rank-size rules to evaluate the scale structure of the urban system, and using kernel density analysis method to identify the main corridors of multi-dimensional factor flows, and combining advantage flow and density-based spatial Clustering of application with noise clustering analysis to analyze the spatial clustering characteristics of the Chengdu-Chongqing urban agglomeration. The results show that: In the multi-dimensional factor flow network, the hierarchical differentiation of each node is obvious. Chengdu and Chongqing are the central node cities, with prominent agglomeration and diffusion capabilities of multi-dimensional factor flow, while other cities are generally under developed. The interval between Chongqing and Chengdu has the strongest connection strength, followed by the interval of Chengdu, Chongqing, and 14 prefect ure-level cities, and the interval of 14 prefecture-level cities is the lowest. The main corridors of factor flow are the Chengdu-Chongqing development axis and the Chengdu-Deyang-Mianyang-Leshan urban belt. Under the constraint of the advantage flow, five spatial clusters are formed within the Chengdu-Chongqing urban agglomeration, including Chengdu-Deyang-Meishan, Chongqing-Guangan, Nanchong-Suining, Neijiang-Zigong-Yibin-Luzhou, and Leshan-Ya’an. Among them, Nanchong-Suining and Neijiang-Zigong-Yibin-Luzhou have the potential to develop into metropolitan areas. Based on the analysis results and existing plans, this paper suggests that Mianyang, Nanchong, and Yibin, which have relatively high centrality in the multi-dimensional element flow network, be cultivated as secondary central cities. While focusing on the development of the Cheng du metropolitan area and the Chongqing metropolitan area, efforts should be made to cultivate the two metropolitan areas of Nanchong-Suining and Neijiang-Zigong-Yibin-Luzhou, promote differentiated and characteristic development of urban gaps such as Mian yang, Ya"an, Leshan, and Dazhou, strengthen the development axis of Yibin-Luzhou-Chongqing along the Yangtze River, and gradually optimize the spatial structure of the Chengdu-Chongqing urban agglomeration, forming a new pattern of coordinated regional development.
Key words:  Spatial structure  Multi-dimensional factor flows  Social network estimation  Rank-size rule  Kernel density analysis  Density-based spatial clustering of application with noise (DBSCAN)  Chengdu-Chongqing urban agglomeration