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Megaregion has emerged as a global urban form, typically based on the polycentric strategy to enhance regional development. How to measure megaregional spatial structure and discriminate different roles of cities has become increasingly important to enrich the knowledge of the formation of a megaregion. Meanwhile, various indices have been used to identify vital nodes in the field of complex network. Which indices, however, are suitable for megaregion analysis remain unsolved. To address this requirement, this study first reviewed the typical indices for identifying vital nodes in the complex network theory, and pointed out that in a weighted city network scenario, weighted degree centrality, hub & authority score, and S-core decomposition (which represent network centrality, connectivity, and structures, respectively) are suitable for analyzing megaregional spatial structures. Then, we explored the city hierarchies and spatial structure in Guangdong Province, China, using the three indices. The hierarchical structure of the weighted city network in Guangdong Province had been identified using S-core decomposition. From the perspective of polycentric structure, Guangzhou and Shenzhen have the strongest node degrees and strength of mobility flows, while the Guangzhou-Dongguan-Shenzhen corridor has been identified via the hub & authority score which is designed to evaluate the connectivity in a weighted network. Moreover, we conducted a comparison analysis of three indices. The findings of this study not only enrich the understanding of city hierarchies and the structure of a megaregion, but also highlight that although various indices are available, they should be applied selectively in accordance with the study context. [ABSTRACT FROM AUTHOR]

Social area analysis has been applied to analyze how urban space is spatially arranged. Related studies have divided urban residents into different groups whose socioeconomic status are similar. However, few studies have attempted to explore the mobility of these social groups, especially for developing countries where census data with travel information are not readily available. This study explores whether people in the same social area have similar work mobility and whether location matters from an aggregated neighborhood perspective. A case study is conducted in Shenzhen, China with fine-grained census and mobile phone data. The neighborhood committee based census and cell tower based mobile phone data are integrated into 500 m grid for analysis. Results show that different social areas have significantly different work mobility, and the within-group heterogeneity is also prominent. Three location factors are examined and it is found that there exist variations in the influence of spatial factors on work mobility for different social areas. Findings of this study will supplement current knowledge about social areas, location and mobility in urban China at the mesoscale. In addition, the methodology provides a feasible framework of integrating city-scale socioeconomic information and mobility data from different sources for future urban studies. • Similar social groups have different mobility at the aggregated level. • The difference is related to interactions of socio-economic status and location. • Variations in the influence of location on mobility for different social group • A framework of integrating census and mobile phone data [ABSTRACT FROM AUTHOR]