Understanding Urban Land Growth through a Social-Spatial Perspective

Abstract

To understand the urbanization process, it is essential to detect urban spatial growth and to study relations with social development. In this study, we take Wuhan as a case to examine urban land growth patterns and how social factors relate to the urban land evolution between 1990, 2000, and 2010. We first classify land cover using Landsat images and examine the urban growth patterns during various stages based on landscape metrics regarding the area, density, and shape. Afterwards, principal component analysis and census data are used to extract key social factors. Thirdly, we apply geographically weighted regression (GWR) to depict the link between urban land metrics and social factors. The results indicate that the urban land coalescence and diffusion simultaneously exist, for which redevelopment, infilling, and edge expansion dominate the city center, and diffusion dominates the peripheral areas. The social factors have global regression relationships with urban land areas while local spatial non-stationarity presents in the relationships with the urban land patch shape irregularities. Industrial upgrading, educational levelling up, and population aging show significant with local heterogeneities in the relationships. The simulation of the relationship provides a social-spatial perspective to understand urban land growth. The authors conclude that sustainable urban management should consider the coexistence of different urban spatial growth models and underline social transitions when examining the urban growth process. This works for cities in rapidly urbanizing countries or regions.

Keywords

• urban land growth
• urban expansion
• fractal dimension
• social transition
• geographically weighted regression (GWR)
• Wuhan