On the basis of the “space of flows” theory, city networks emphasizing factor connectivity and spatial connection have become a core perspective for regional spatial relationships. They provide a context for discussing the spatial structures of city networks and a scientific basis for making regional development policies. Relying on expressway traffic flow data from Jiangsu Province in 2014, this study describes macro-spatial patterns and hierarchical structures of city networks, and uses the Walktrap algorithm of community detection to execute space divisions and elucidate potential spatial connection structures in the city networks. In comparison with other algorithms, the Walktrap algorithm demonstrates significant adaptation and stability to the short expressway traffic flows with the characteristics of strong network density and sparse node distribution. The results indicate that the macro-spatial patterns of Jiangsu’s city networks have clear regional differences. The cities with relatively dense spatial linkages are distributed along the Yangtze River banks, and many different sub-network systems have also developed internally. Cities and linkage axles have clear hierarchical structures. City hierarchies have certain spatial couplings with the cities’ intrinsic social economic attributes and geographical locations. The linkage axles hierarchy has clear spatial interactions and superposition with geographical distance. The community detection algorithm identified six spatially connected “city communities”, the Suzhou-Wuxi-Changzhou Community (SWCC), the Nanjing-Zhenjiang-Yangzhou-Taizhou Community (NZYTC), the Nantong-Yancheng Community (NYC), the Lianyungang Community (LYGC), the Huai’an-Suqian Community (HSC), and the Xuzhou Community (XZC). The community spatial metaphors had four aspects. First, trans-prefectural linkages were formed through spatially integrated effects of metropolis regions. Second, some communities share the same boundaries with their prefecture level administrative units; this reveals that significant administrative regional economies still exist in contemporary Jiangsu. Third, several cities located in the marginal areas of prefectures and captured by the powerful center cities in neighboring prefectures have been absorbed into the communities of neighboring prefectures. Fourth, the two cities Jiangyin and Jingjiang, divided into different administrative districts, have switched status opposite city community divisions.

探索如何针对不同类型城镇化的发展特征实施差异化策略，是实现中国新型城镇化可持续健康发展的关键理论与现实问题。论文从人口的户籍地和现住地情况以及城乡划分中关于“城镇”的规定出发，基于2010年和2020年的人口普查数据，细分了海峡西岸城市群人口城镇化的在地、就地、就近、异地、户口未定5种城镇化类型，综合运用探索性时空数据分析和空间杜宾模型，探究了各人口城镇化类型的时空特征与影响因素。结果表明：① 空间分布上，各城镇化类型呈现整体提升或梯度扩散的宏观格局。其中，在地、就地城镇化在时段内整体水平显著提升。就近、异地、户口未定城镇化则呈现梯度扩散分布，各自形成了地级市中心为核心梯度扩散、沿海向腹地梯度递减以及沿海集聚而腹地分散的梯度格局。② 时空变动上，各类型城镇化存在显著的空间自相关，整体聚集特征稳中有变。在地城镇化“高—高”集聚区由潮汕扩展为潮汕—上饶双核；就地城镇化“高—高”集聚区向西部迁移；就近、异地及户口未定城镇化“低—低”集聚区在闽赣交界形成带状分布，而“高—高”则在沿海聚集。③ 影响机制上，自然条件奠定初期格局；在历史路径下形成的簇团社会文化网络促进了多元化的城镇化发展。同时，政府决策一方面通过开放性政策和户籍制度、行政区划调整和城乡划分直接影响城镇化，另一方面通过调控经济社会和空间因素产生间接影响。