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Drivers of urban expansion over the past three decades: a comparative study of Beijing, Tianjin, and Shijiazhuang

  • Wenjia Wu
  • Shuqing ZhaoEmail author
  • Geoffrey M. Henebry
Article
  • 89 Downloads

Abstract

Urban expansion is influenced by various natural and anthropogenic factors. Understanding the driving forces of urban expansion is crucial for modeling the process of urban expansion as well as guiding urban planning and management. Here, we quantified and compared the effects of natural, socioeconomic, and neighboring factors on urban expansion and their temporal dynamics in three large cities in the Jing-Jin-Ji Urban Agglomeration: Beijing, Tianjin, and Shijiazhuang. We used remote sensing imagery from six epochs (circa 1980, 1990, 1995, 2000, 2005, and 2010) integrated with GIS techniques and analyzed using binary logistic regression. The relative importance of the three types of driving forces was further decomposed using variance partitioning. We found that the direction and/or magnitude of effects on the drivers of urban expansion varied with both epoch and city. Natural factors placed significant constraints at early stages of urban expansion, but this constraint relaxed over time. As precursor drivers of urbanization, socioeconomic factors significantly influenced urban growth in most epochs for each city. Non-urban lands near existing urban areas were more likely to be urbanized, due to easier access to existing transportation infrastructure and other facility resources. Furthermore, with urbanization, individual effects of drivers tended to be replaced by joint effects, especially for the neighboring factors. Similarities and differences in the individual and joint effects of drivers on urban expansion across cities and through time will provide valuable information for adaptive urban development strategies in the national capital region of China.

Keywords

Remote sensing Urban expansion Driving forces Logistic regression Variance partitioning Jing-Jin-Ji Urban Agglomeration 

Notes

Acknowledgements

We thank Dr. Xiaochen Meng for providing the road and railway dataset.

Funding information

This study was supported by the National Natural Science Foundation of China grants 41590843, 41571079, and 41771093.

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Authors and Affiliations

  1. 1.College of Urban and Environmental Sciences and Key Laboratory for Earth Surface Processes of the Ministry of EducationPeking UniversityBeijingChina
  2. 2.Department of Geography, Environment, and Spatial Sciences and Center for Global Change and Earth Observations (CGCEO)Michigan State UniversityEast LansingUSA

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