What is the developmental level of outlying expansion patches? A study of 275 Chinese cities using geographical big data. (October 2020)

• Record Type: Journal Article
• Authors: He, Qingsong; Zhou, Jiang; Tan, Shukui; Song, Yan; Zhang, Lu; Mou, Yanchuan; Wu, Jiayu
• Is Part Of: Cities. Volume 105(2020)
• Publication Date: 2020-10
• Subjects: Geographical big data -- Outlying expansion -- Evaluation, 275 cities -- Policy suggestions -- Urban spatial form; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2019.102395
• Languages: English
• ISSNs: 0264-2751

Abstract

Abstract: New outlying development zones are a common phenomenon in the development of Chinese cities, and exploring their development level is a matter of great interest. Using geographic big data that cover the entire country, this paper analyzes the urban development level (UDL) of newly added outlying patches within 275 cities at the prefecture level or above in China from 2005 to 2015. The results revealed the following. 1) High-value cities are primarily located in the east, whereas low-value cities are primarily located in the west. The Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is a major area with low UDLs, whereas the Yangtze River Delta urban agglomeration (YRDUA) and the Pearl River Delta urban agglomeration (PRDUA) are major areas with high UDLs. 2) The results of a multivariate regression demonstrate that GDP per capita (GDPPC), average elevation (AE), the distance between the new outlying urban patches, the proportion of secondary industry in GDP (PSI), the average land price in the city (ALP), the original urban land areas (DIS), and economic balance (GDPSD) significantly affect the UDL values of these cities. Relatively higher GDPPC and ALP are associated with a significant increase in the UDL, while more AE, DIS, GDPSD and PSI will decrease the UDL. The results of this paper provide a reference to understand the conditions of outlying developmental zones in China over the past 10 years as well as to explore healthy and reasonable urban spatial expansion forms. Highlights: The development level of new outlying development zones in China' 275 cities was evaluated using multisource big data. The causes of the differences in the urban development levels across different cities were explored. The higher the rank of the city is, the higher the average development level of the outlying expansion patches. A patch-based indicator showed that 79 cities belong to the desirable urban expansion group.