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The unprecedented urbanization in China has dramatically changed the urban spatial structure of cities. With the proliferation of individual-level geospatial big data, previous studies have widely used the network abstraction model to reveal the underlying urban spatial structure. However, the construction of network abstraction models primarily focuses on the topology of the road network without considering individual travel flows along with the road networks. Individual travel flows reflect the urban dynamics, which can further help understand the underlying spatial structure. This study therefore aims to reveal the intra-urban hierarchical spatial structure by integrating the road network abstraction model and individual travel flows. To achieve this goal, we 1) quantify the spatial interaction relatedness of road segments based on the Word2Vec model using large volumes of taxi trip data, then 2) characterize the road abstraction network model according to the identified spatial interaction relatedness, and 3) implement a community detection algorithm to reveal sub-regions of a city. Our results reveal three levels of hierarchical spatial structures in the Wuhan metropolitan area. This study provides a data-driven approach to the investigation of urban spatial structure via identifying traffic interaction patterns on the road network, offering insights to urban planning practice and transportation management. [ABSTRACT FROM AUTHOR]

Urban population size dynamic adjustment has been widely studied for a long time; however, the dynamic adjustment at the urban hierarchy level remains unknown. This study utilises China's urban population data to investigate the dynamic adjustment. Specifically, we utilise methods of the Gini coefficient, linear regression, and coefficients of Spearman, and Moran's I to explore the dynamic adjustment tendency, adjustment rate and correlation of urban population size distribution of different urban hierarchies and groups of different urban hierarchies. We find that the urban population size spatial distribution is gradually even within the same urban hierarchy. The adjustment rate to be even of Megacity II is the highest, and Megacity I is the bottom. We also find the population size spatial distribution of the whole urban system is gradually uneven. We explore the dynamic process by sorting urban hierarchies into six groups. Furthermore, we find there is a complex correlation between different urban hierarchies and global spatial correlation among China cities. These results are valuable as references for Chinese policy-makers and practitioners and will enable them to adopt sustainable land use and urban population management measures. The study outcomes will also benefit future studies on spatial population size distribution in international communities. [ABSTRACT FROM AUTHOR]