| description abstract | Incorporating three-dimensional (3D) spatial measurement into the urban expansion measurement system plays an important role in understanding the degree of urban expansion and regulating and governing it. This article proposes an urban concrete forest and constructs an Urban Volume Sprawl Index to quantitatively study the spatiotemporal characteristics of the three-dimensional expansion of Chinese prefecture-level cities. Furthermore, geographic detectors are used to study its influencing factors. The following conclusions are drawn: (1) Between 1990 and 2018, the volume of Chinese cities has increased from 414.67 to 1,406.29 km3, with a growth rate of 239.13%. (2) The overall growth rate of urban volume shows a gradual slowing trend during the research period, from 55.99% to 40.83%. (3) Between 1990 and 2018, the Urban Volume Sprawl Index nationwide gradually slowed down (from 5.18% to 3.90%), with the largest rate reported in the western region (4.1%), the middle in the eastern region (3.46%), and the smallest in the central region (3.28%). (4) Government and economic factors have the greatest impact on the three-dimensional expansion of Chinese cities (over 69%), with social factors in the middle, and natural factors having the weakest explanatory power (less than 15%). (5) There are differences in the degree of urban expansion between two-dimensional and three-dimensional perspectives. A total of 38.1% of cities have a greater degree of urban expansion from a two-dimensional (2D) analysis perspective, which are mainly small cities located in the western and eastern regions. A total of 5.4% of cities (mainly located in the Yangtze River Delta and Pearl River Delta regions) have a greater degree of urban expansion from a 3D perspective. The remaining cities (56.5%) go through the same level of urban expansion in both analysis dimensions. A 3D urban expansion analysis can better explain and reveal the actual production and living space provided by urban expansion than 2D analysis. It can provide temporal data for urban land efficiency evaluation, ghost city identification, etc., and it has good application and promotion prospects. | |
