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Spatiotemporal Transformation of Urban Social Landscape: A Case Study of Wuhan, China

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Abstract

For decades, urbanization has been a major topic of discussion among academics and professionals when investigating issues such as social segregation, spatial inequality, and urban sustainability. However, little attention has been given to the relationship between social characteristics and the ever-changing development of urban spaces. This paper seeks to investigate progressive changes in the social stratification structure in Wuhan’s urban development zone (UDZ) while focusing on their associated spatial transformations, based on census data of Wuhan in 1990, 2000, and 2010. To obtain this objective, the study will answer two key questions: (1) What are the characteristics of urban social spatial evolutions of Wuhan the second-tier city in China? (2) What are the mechanisms of social spatial evolution? And (3) what role does the social spatial evolution play in urban social planning and management? We used varimax rotated principal component analysis (PCA) to extract social dimensions along with ArcMap to enhance spatial analysis while visualizing the distribution of social factor scores. The results show that since 1990, the local population (particularly the aging population) has reflected a hollowing trend. Industrial relocation and population mobility have become the main social dimensions in the 1990s and 2000s respectively. The characteristics of socio-spatial transformations are from concentric rings as well as combinations of concentric rings, axial aggregations, and multiple clusters. These transformations are formed by the push–pull force of the large area and the centripetal and centrifugal forces inside the city. We have concluded that top-down systems dominate socio-spatial transformations in the early stages, while public participatory management plays a more important role in the later stages, which will become inclusive governance.

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source: http://hb.ifeng.com/news/jjcs/detail_2013_07/05/967640_0.shtml; A national central city Wuhan in a high-speed railway network, source: )

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Notes

  1. The city tier system is a hierarchical classification of Chinese cities with four categories. Although Chinese government does not recognize an official definition of the tier system, it is frequently referred to by various media publications and academic papers. The tier system has gained wide popularity in recent years as a point of reference. According to the city classification of the National Bureau of Statistics in the residential sales price survey, the first-tier cities are Beijing, Shanghai, Guangzhou and Shenzhen. The second tier-tier cities are provincial capital cities, autonomous capital cities and other sub-provincial cities, including Wuhan, Hangzhou, Nanjing, Tianjin, Chengdu, etc. The third- and fourth-tier cities are the rest (China National Bureau of Statistics, 2018).

  2. Wuhan has experienced the evolution of three traditional towns. They are Hankou (west of the Yangtze River and north of the Han River), Hanyang (west of the Yangtze River and south of the Han River) and Wuchang (east and south of the Yangtze River). Traditional towns are mainly concentrated in the city center near the intersection of rivers.

  3. For the variables interpreting the same factor, if the correlation coefficients are equal or greater than 0.9, only one is kept.

  4. According to the rule of thumb, if the skewness standard error is between -0.5 and 0.5, the data are approximately symmetrical.

  5. The KMO test measures ‘sampling adequacy. This measure varies between 0 and 1, and values closer to 1 are better’. The BTS tests ‘the null hypothesis that the correlation matrix is an identity matrix’. This null hypothesis should be rejected for factor analysis. (Source: https://stats.idre.ucla.edu/spss/output/factor-analysis/).

  6. Varimax is to ‘minimize the number of variables that have high loadings on each factor, which simplifies the interpretation of the factors’. (Source: https://stats.idre.ucla.edu/spss/output/factor-analysis/).

  7. The dependence of Wuhan's local finance on land transfer fee is higher than 0.7, ranking top 10 among big cities in China. In 2007, the dependence was as high as 0.86. (Data source: Research Institute of Taxation, State Administration of Taxation (2014).).

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Social spatial transformation (city center)

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Zhang, L., Han, R. & Cao, H. Spatiotemporal Transformation of Urban Social Landscape: A Case Study of Wuhan, China. Soc Indic Res 163, 1037–1061 (2022). https://doi.org/10.1007/s11205-022-02929-2

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