Abstract
A quantitative analysis of spatial influencing factors on urban sprawl can offer better support for urban planning and management. There are many concerns regarding the influence of each factor. However, a quantitative analysis to detect the interactions between factors is limited because of the complexity of the urban systems, especially the role of planning. Additionally, spatial heterogeneity is often overlooked. This study aims to improve and strengthen the knowledge in this field through a spatial statistical method known as GeoDetector. A new spatial quantification of urban expansion was presented in this study and the spatio-temporal characteristics and mechanism of urban growth in Beijing from 2010 to 2015 were also analyzed. The results show that urban expansion presents spatial heterogeneity with different grid cells, and the optimal scale was 4500 m. At this scale, urban expansion in Beijing linearly expands along the traffic trunk. In addition, urban expansion in Beijing is jointly influenced by socioeconomic, geographical, and policy factors. Population density has had the greatest influence on urban expansion from 2010 to 2015, and policy factors rank first. The impact of economic factors on urban growth is gradually weakening. It is important for urban geographical research to further plans and guide urban development.
Highlights
The 2014 revision of World Urbanization Prospects notes that there is an increasing number of people living in urban areas and that the urban population will increase by 2.5 billion by 2050 [1]
The urban development boundary of the plan is a significant component of new urbanization trends of China, and is an important way to alleviate the current blight of the “urban disease”
Sprawl is often measured by the urban expansion intensity [37,38], or sometimes urban growth is replaced with urban population growth [39]
Summary
The 2014 revision of World Urbanization Prospects notes that there is an increasing number of people living in urban areas and that the urban population will increase by 2.5 billion by 2050 [1]. The urban population will increase in China, India, and Nigeria. In March 2014, China launched the “national new urbanization plan (2014–2020)” [2], which proposes to develop a harmonious relationship between “man” and “nature”. The urban development boundary of the plan is a significant component of new urbanization trends of China, and is an important way to alleviate the current blight of the “urban disease”. Pattern, and mechanism of urban expansion has become a scientific problem for researchers. Analysis on this topic is the key to simulating and predicting urban expansion. For some cellular automaton(CA)-based models and other urban growth models, predictable drivers usually form the basis of the model and can be used as input parameters to establish CA transition rules or calculate urban development potential [3,4]
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