Identifying the spatio-temporal dynamics of mega city region range and hinterland: A perspective of inter-city flows

IF 7.1 1区 地球科学 Q1 ENVIRONMENTAL STUDIES
Haoyu Hu , Jianfa Shen , Hengyu Gu , Junwei Zhang
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引用次数: 0

Abstract

Mega city regions (MCRs) have emerged in many countries in the process of urbanisation. Understanding the spatio-temporal dynamics of MCRs is crucial for sustainable urban development. However, the spatial scales and boundaries of these MCRs remain poorly defined, and their temporal dynamics have received limited attention. To address these gaps, we propose a new framework and GSMA algorithm that considers inter-city flows to identify MCRs' central cities, ranges and hinterlands. By utilising comprehensive data of over 30 million inter-city flow records covering 369 cities from Amap and Tencent, calibrated with official data from the Ministry of Transport, we identify 10 MCRs and 16 central cities in China, providing a clearer understanding of the spatial ranges and core areas of MCRs. We find that MCR ranges show relative stability during routine activities and expansions during holiday periods. Compared with previous methods, the proposed framework and algorithm have two prominent advantages. First, our methodology incorporates the directional characteristics of flows into the identification of MCRs' central cities. Second, we strike a balance between enlarging regional influence and tightening the internal connections in MCR delineation. In addition, by incorporating temporal changes in inter-city flows, the study reveals the temporal dynamics of MCRs which reflects the intricate interplay between human activities and urban system dynamics.

确定特大城市区域范围和腹地的时空动态:城市间流动的视角
在城市化进程中,许多国家都出现了超大城市区域(MCRs)。了解特大城市区域的时空动态对城市的可持续发展至关重要。然而,这些特大城市区域的空间尺度和边界仍然没有得到很好的界定,它们的时空动态也只得到了有限的关注。为了弥补这些不足,我们提出了一个新的框架和金沙国际娱乐网址算法,该框架和算法考虑了城市间的流动,以识别多中心城市群的中心城市、范围和腹地。通过利用 Amap 和腾讯提供的涵盖 369 个城市的 3000 多万条城市间流量记录的综合数据,并与交通运输部的官方数据进行校准,我们确定了中国的 10 个多式联运中心和 16 个中心城市,从而更清晰地了解了多式联运的空间范围和核心区域。我们发现,在日常活动期间,多式联运中心的范围相对稳定,而在节假日期间则有所扩大。与之前的方法相比,我们提出的框架和算法有两个突出优势。首先,我们的方法将人流的方向性特征纳入了多式联运中心城市的识别中。其次,在多区域中心城市的划分中,我们在扩大区域影响力和加强内部联系之间取得了平衡。此外,通过纳入城市间人流的时间变化,本研究揭示了多区域中心城市的时间动态,反映了人类活动与城市系统动态之间错综复杂的相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
13.30
自引率
7.40%
发文量
111
审稿时长
32 days
期刊介绍: Computers, Environment and Urban Systemsis an interdisciplinary journal publishing cutting-edge and innovative computer-based research on environmental and urban systems, that privileges the geospatial perspective. The journal welcomes original high quality scholarship of a theoretical, applied or technological nature, and provides a stimulating presentation of perspectives, research developments, overviews of important new technologies and uses of major computational, information-based, and visualization innovations. Applied and theoretical contributions demonstrate the scope of computer-based analysis fostering a better understanding of environmental and urban systems, their spatial scope and their dynamics.
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