ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1643214
Spatiotemporal Characteristics and Spatial Heterogeneity of Influencing Factors in China's Urbanization Process: Based on Nighttime Light Remote Sensing Data
Provisionally accepted
- 1Nanyang Normal University School of Civil Engineering and Architecture, Nanyang, China
- 2Henan Urban Planning and Design Institute CO., LTD., Zhengzhou, China
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The process of urbanization involves all aspects of society and understanding the spatial differences in urban development is crucial to promoting sustainable urban development. However, the existing studies still lack a spatial heterogeneity analysis of the driving factors of urbanization at the prefectural-level city scale and over a long period of time. This study uses nighttime light data, with 285 prefecture-level cities in China as the research objects. It employs spatial autocorrelation and the geographically weighted regression (GWR) model to investigate the spatial heterogeneity of the factors influencing urban development in China from 2000 to 2019. The results show that: (1) The overall level of urbanization in China is on the rise. Spatially, it exhibits a distribution pattern shifting from concentration to dispersion and from a single center to multiple centers. (2) The urbanization process in China exhibits a significant spatial correlation. The hotspots are mainly concentrated in the eastern part of China along the southern coast and the northern part of the southern coast, while the coldspots are located in the southwestern, northwestern, and northeastern regions. (3) The regression coefficients of the influencing factors exhibit significant spatial imbalance. Economic development, population size, public infrastructure, and economic openness all show a positive correlation with urbanization development as a whole; the industrial structure has a negative impact on urbanization development in most regions, and its inhibitory effect is weakest in the cold spots. Capturing this heterogeneity is of vital importance for understanding the diverse paths of urban development and formulating differentiated policies for specific regions.
Keywords: Urbanization process1, Geographically weighted regression2, Spatial heterogeneity3, Spatial autocorrelation4, Nighttime light5
Received: 08 Jun 2025; Accepted: 29 Jul 2025.
Copyright: © 2025 Ren, Zhang, Fan and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaonan Zhao, Nanyang Normal University School of Civil Engineering and Architecture, Nanyang, China
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