Abstract
AbstractThis paper uses Baidu migration data to obtain the intercity trips between cities in China. Taking intercity travel as a functional connection between cities, taking into account the internal and external intercity travel connections of urban agglomerations, an improved rank scale distribution method was used to quantitatively measure the form and function of the Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, middle reaches of the Yangtze River, Chengdu-Chongqing, Central Plains, Guanzhong, and Harbin-Changchun urban agglomerations. It is found that, firstly, there are differences in the Functional Polycentricity presented by the internal and external connections of urban agglomerations, which are related to the economic development of urban agglomerations and central cities. Secondly, there are differences between Morphological Polycentricity and Functional Polycentricity of the eight urban agglomerations measured by the internal and external connections, indicating that the external connections have a significant impact. The internal and external connections of urban agglomerations are important functional connections of urban agglomerations. The study of urban agglomerations should not ignore the internal or external connections, and the overall consideration can more comprehensively reflect the polycentric characteristics of urban agglomerations. The internal and external connections of urban agglomerations are important functional connections, and the study of urban agglomerations should not ignore internal or external connections. Overall consideration can better reflect the polycentirccharacteristics of urban agglomerations.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference27 articles.
1. Batten, D. F. (1995). Network cities: Creative urban agglomerations for the 21st century. Urban Studies,
32(2), 313–327.
2. Burger, M., & Meijers, E. (2012). Form follows function? Linking morphological and functional polycentricity. Urban Studies,
49(5), 1127–1149.
3. Camagni, R., Stabilini, S., & Diappi, L. (1994). City networks in the Lombardy region: An analysis in terms of communication flows. Flux Cahiers Scientifiques Internationaux Réseaux Et Territoires,
10(15), 37–50.
4. Dieleman, F. M., & Faludi, A. (2010). Randstad, Rhine-Ruhr and Flemish diamond as one polynucleated macro-region? Tijdschrift Voor Economische En Sociale Geografie,
89(3), 320–327.
5. Gabaix, X., & Ibragimov, R. (2011). Rank−1/2: A simple way to improve the OLS estimation of tail exponents. Journal of Business & Economic Statistics,
29(1), 24–39.