The Regional Disparity of Urban Spatial Expansion Is Greater than That of Urban Socioeconomic Expansion in China: A New Perspective from Nighttime Light Remotely Sensed Data and Urban Land Datasets

Abstract

The regional disparity of urban expansion varies significantly in China’s different regions, hindering sustainable socioeconomic development. However, most studies to date have focused on a single aspect of urban expansion, e.g., urban spatial expansion (USS) disparity. This study attempts to define urban expansion from USS and urban socioeconomic expansion (USE) based on nighttime light remotely sensed (NTL) data and urban land datasets. Then, taking China’s 241 prefecture-level cities within different provinces as experimental subjects, the Dagum Gini (DG) coefficient and stochastic convergence test are employed to assess the disparity of urban expansion from two different dimensions. The results show that, on the national scale, the regional disparity of USS is always greater than that of USE and has a converging trend. Additionally, regional disparity is the main factor causing the difference between USS and USE, with average contribution rates of 55% and 45%, respectively. The average difference between USS and USE in the eastern region (ER) is greater than 10%, while it is the lowest in the northeastern region (NER) and shows a significant expansion trend in performance convergence with a regression coefficient of 0.0022, followed by the central (CR), eastern, and western (WR) regions. Through the panel unit root test, we found that urban expansion in China in terms of USS and USE has internal random convergence in certain regions under the premise of global random divergence, and there may be differentiation and formation of one or more convergence clubs in the future. Using this novel perspective to define urban expansion, this study quantifies the contributions of USS and USE to regional disparity and provides a scientific basis for governments to implement appropriate approaches to sustainable urban development in different regions.

Keywords

• nighttime light data
• urban expansion
• regional disparity
• Gini coefficient
• stochastic convergence