School of Geography, Yunnan Normal University, Kunming, Yunnan, China.
Center for Myanmar Studies of Yunnan Normal University, Kunming, Yunnan, China.
PLoS One. 2020 Dec 21;15(12):e0244084. doi: 10.1371/journal.pone.0244084. eCollection 2020.
Regional differences in socioeconomic factors are important for assessing the regional development of an area. While much research has focused on the overall patterns of regional differences within independent cities and areas, the hierarchical spatiotemporal structures of megacity regions have seldom been discussed. To fill this gap, this paper investigates the multilevel regional differences within megacity regions. Employing GDP, population and total retail sales as socioeconomic indicators, the spatiotemporal patterns of socioeconomic trends are identified. A hierarchical clustering approach that utilizes socioeconomic similarities is proposed for the identification of the spatiotemporal patterns of individual cities. At the megacity regional level, gravity centers and pathways are constructed to evaluate spatial imbalances and temporal change intensities. Taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as its study area, this research produces results that show diverse spatiotemporal patterns among the individual cities, revealing high/low starting point and high/low growth rate modes in terms of city interactions. From the perspective of the entire GBA, the spatial imbalance of GDP is the highest of the factors, followed by the spatial imbalance of the total retail sales of the region and, finally, by that of its population. Total retail sales exhibit the highest level of temporal change intensity, followed by GDP and population. In terms of the contribution of the various cities to the overall regional changes, Guangzhou, Shenzhen and Hong Kong dominate the spatiotemporal changes in the gravity centers, while Foshan and Dongguan show significant potential to contribute to these socioeconomic patterns. These results provide effective guidance for the sustainable development of megacity regions.
区域间的社会经济因素差异对于评估一个地区的区域发展至关重要。虽然大量研究集中于独立城市和地区内部的区域差异总体模式，但大都市区的层次时空结构却很少被讨论。为了填补这一空白，本文探讨了大都市区内部的多层次区域差异。利用 GDP、人口和社会消费品零售总额作为社会经济指标，识别社会经济趋势的时空模式。提出了一种利用社会经济相似性的层次聚类方法，用于识别各个城市的时空模式。在大都市区层面，构建重力中心和路径来评估空间不平衡和时间变化强度。以粤港澳大湾区（GBA）为研究区域，本研究结果表明各个城市之间存在多样化的时空模式，揭示了城市互动方面的高/低起点和高/低增长率模式。从整个 GBA 的角度来看，GDP 的空间不平衡是三个因素中最高的，其次是区域社会消费品零售总额的空间不平衡，最后是人口的空间不平衡。社会消费品零售总额的时间变化强度最高，其次是 GDP 和人口。就各个城市对整体区域变化的贡献而言，广州、深圳和香港主导了重力中心的时空变化，而佛山和东莞显示出对这些社会经济模式的显著贡献潜力。这些结果为大都市区的可持续发展提供了有效的指导。
