Abstract
The objective of this study is to develop a framework for re-examining and re-defining the classical concepts of spatial interaction and reorganization in the urban system. We introduce a modified radiation model for spatial interactions, coupled with migration big data, transport accessibility algorithm, and city competitiveness assessment for efficient distribution of the inter-city flow through the network. The Yangtze River Middle Reaches (YRMR) urban agglomeration (UA) is chosen as the case study region to systematically identify and measure its spatial configuration and to gain insights for other UAs’ sustainable development in China. The results are also compared with those computed by the classical gravity model to systematically discuss the applicability of spatial interaction laws and models, and related practical policies for regional sustainable development are discussed based on the findings as well. The conclusions are highlighted below: 1) Combining with the ‘city network paradigm’ and ‘central place theory’ can better express the spatial configurations of city systems in the context of ‘space of flows’; 2) The results validate the potentialities of a multi-analysis framework to assess the spatial configurations of city network based on the improved radiation model and network analysis tools; 3) The applications of spatial interaction models should be considered according to the specific geographical entity and its spatial scale.
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References
Anderson J E, van Wincoop E, 2003. Gravity with gravitas: a solution to the border puzzle. American Economic Review, 93(1): 170–192. doi: https://doi.org/10.1257/000282803321455214
Batten D F, 1995. Network cities: creative urban agglomerations for the 21st century. Urban Studies, 32(2): 313–327. doi: https://doi.org/10.1080/00420989550013103
Batty M, 2013. A theory of city size. Science, 340(6139): 1418–1419. doi: https://doi.org/10.1126/science.1239870
Berry B J L, 1964. Cities as systems within systems of cities. Papers in Regional Science, 13(1): 147–163. doi: https://doi.org/10.1111/j.1435-5597.1964.tb01283.x
Blondel V D, Guillaume J L, Lambiotte R et al., 2008. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10: 10008. doi: https://doi.org/10.1088/1742-5468/2008/10/p10008
Burger M J, Meijers E J, van Oort F G, 2014. Editorial: the development and functioning of regional urban systems. Regional Studies, 48(12): 1921–1925. doi: https://doi.org/10.1080/00343404.2014.979782
Camagni R P, Salone C, 1993. Network urban structures in northern Italy: elements for a theoretical framework. Urban Studies, 30(6): 1053–1064. doi: https://doi.org/10.1080/00420989320080941
Cao Z, Derudder B, Peng Z W, 2018. Comparing the physical, functional and knowledge integration of the Yangtze River Delta city-region through the lens of inter-city networks. Cities, 82: 119–126. doi: https://doi.org/10.1016/j.cities.2018.05.010
Capello R, Caragliu A, Fratesi U, 2018. Breaking down the border: physical, institutional and cultural obstacles. Economic Geography, 94(5): 485–513. doi: https://doi.org/10.1080/00130095.2018.1444988
Castells M, 1989. The Informational City: Information Technology, Economic Restructuring and the Urban-Regional Process. Oxford, UK: Basil Blackwell Oxford.
Christaller W, 1966. Central Places in Southern Germany. Englewood Cliffs, NJ: Prentic Hall.
Dadashpoor H, Afaghpoor A, Allan A, 2017. A methodology to assess the spatial configuration of urban systems in Iran from an interaction perspective. GeoJournal, 82(1): 109–129. doi: https://doi.org/10.1007/s10708-015-9671-1
Dennis C, Marsland D, Cockett T, 2002. Central place practice: shopping centre attractiveness measures, hinterland boundaries and the UK retail hierarchy. Journal of Retailing and Consumer Services, 9(4): 185–199. doi: https://doi.org/10.1016/S0969-6989(01)00021-2
Department of Urban Socio Economic Investigation, National Bureau of Statistics, 2017. China City Statistical Yearbook. Beijing: China Statistics Press. (in Chinese)
Fang C L, Yu D L, 2017. Urban agglomeration: an evolving concept of an emerging phenomenon. Landscape and Urban Planning, 162: 126–136. doi: https://doi.org/10.1016/j.landurbplan.2017.02.014
Han J, Liu J B, 2018. Urban spatial interaction analysis using inter-city transport big data: a case study of the yangtze river delta urban agglomeration of China. Sustainability, 10(12): 4459. doi: https://doi.org/10.3390/su10124459
He J H, Li C, Yu Y et al., 2017. Measuring urban spatial interaction in Wuhan Urban Agglomeration, Central China: a spatially explicit approach. Sustainable Cities and Society, 32: 569–583. doi: https://doi.org/10.1016/j.scs.2017.04.014
Hesse M, 2010. Cities, material flows and the geography of spatial interaction: urban places in the system of chains. Global Networks, 10(1): 75–91. doi: https://doi.org/10.1111/j.1471-0374.2010.00275.x
Hesse M, 2016. On borrowed size, flawed urbanisation and emerging enclave spaces: the exceptional urbanism of Luxembourg, Luxembourg. European Urban and Regional Studies, 23(4): 612–627. doi: https://doi.org/10.1177/0969776414528723
Hou H P, Liu Y L, Liu Y F et al., 2015. Using inter-town network analysis in city system planning: a case study of Hubei Province in China. Habitat International, 49: 454–465. doi: https://doi.org/10.1016/j.habitatint.2015.06.016
Hubei Provincial Bureau of Statistics, 2017. Hubei Statistical Yearbook. Beijing: China Statistics Press. (in Chinese)
Huff D L, Jenks G F, 1968. A graphic interpretation of the friction of distance in gravity models. Annals of the Association of American Geographers, 58(4): 814–824. doi: https://doi.org/10.1111/j.1467-8306.1968.tb01670.x
Hui E C M, Li X, Chen T T et al., 2018. Deciphering the spatial structure of China’s megacity region: a new bay area—The Guangdong-Hong Kong-Macao Greater Bay Area in the making. Cities. doi: https://doi.org/10.1016/j.cities.2018.10.011
Hunan Provincial Bureau of Statistics, 2017. Hunan Statistical Yearbook. Beijing: China Statistics Press. (in Chinese)
Jiang Y H, Shen J F, 2010. Measuring the urban competitiveness of Chinese cities in 2000. Cities, 27(5): 307–314. doi: https://doi.org/10.1016/j.cities.2010.02.004
Jiangxi Provincial Bureau of Statistics, 2017. Jiangxi Statistical Yearbook. Beijing: China Statistics Press. (in Chinese)
Kang C, Liu Y, Guo D et al., 2015. A generalized radiation model for human mobility: spatial scale, searching direction and trip constraint. PLoS One, 10(11): e0143500. doi: https://doi.org/10.1371/journal.pone.0143500
Lao X, Zhang X L, Shen T Y et al., 2016. Comparing China’s city transportation and economic networks. Cities, 53: 43–50. doi: https://doi.org/10.1016/j.cities.2016.01.006
Lenormand M, Bassolas A, Ramasco J J, 2016. Systematic comparison of trip distribution laws and models. Journal of Transport Geography, 51: 158–169. doi: https://doi.org/10.1016/j.jtrangeo.2015.12.008
Li F Z, Feng Z M, Li P et al., 2017. Measuring directional urban spatial interaction in China: a migration perspective. PLoS One, 12(1): e0171107. doi: https://doi.org/10.1371/journal.pone.0171107
Liu X J, Derudder B, Wu K, 2016. Measuring polycentric urban development in China: an intercity transportation network perspective. Regional Studies, 50(8): 1302–1315. doi: https://doi.org/10.1080/00343404.2015.1004535
Maly J, 2016. Impact of polycentric urban systems on intra-regional disparities: a micro-regional approach. European Planning Studies, 24(1): 116–138. doi: https://doi.org/10.1080/09654313.2015.1054792
Masucci A P, Serras J, Johansson A et al., 2013. Gravity versus radiation models: on the importance of scale and heterogeneity in commuting flows. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 88(2): 022812. doi: https://doi.org/10.1103/PhysRevE.88.022812
McArthur D P, Kleppe G, Thorsen I et al., 2011. The spatial transferability of parameters in a gravity model of commuting flows. Journal of Transport Geography, 19(4): 596–605. doi: https://doi.org/10.1016/j.jtrangeo.2010.06.014
Meijers E, 2005. Polycentric urban regions and the quest for synergy: is a network of cities more than the sum of the parts? Urban Studies, 42(4): 765–781. doi: https://doi.org/10.1080/00420980500060384
Meijers E, 2007. From central place to network model: theory and evidence of a paradigm change. Tijdschrift Voor Economische en Sociale Geografie, 98(2): 245–259. doi: https://doi.org/10.1111/j.1467-9663.2007.00394.x
Meijers E, Hoogerbrugge M, Cardoso R, 2018. Beyond polycentricity: does stronger integration between cities in polycentric urban regions improve performance? Tijdschrift Voor Economische En Sociale Geografie, 109(1): 1–21. doi: https://doi.org/10.1111/tesg.12292
Meijers E J, Burger M J, Hoogerbrugge M M, 2016. Borrowing size in networks of cities: city size, network connectivity and metropolitan functions in Europe. Papers in Regional Science, 95(1): 181–198. doi: https://doi.org/10.1111/pirs.12181
Meijers E J, Burger M J, 2017. Stretching the concept of ‘borrowed size’. Urban Studies, 54(1): 269–291. doi: https://doi.org/10.1177/0042098015597642
Mikkonen K, Luoma M, 1999. The parameters of the gravity model are changing: how and why? Journal of Transport Geography, 7(4): 277–283. doi: https://doi.org/10.1016/s0966-6923(99)00024-1
Mulligan G F, Partridge M D, Carruthers J I, 2012. Central place theory and its reemergence in regional science. The Annals of Regional Science, 48(2): 405–431. doi: https://doi.org/10.1007/s00168-011-0496-7
Neal Z, 2010. Refining the air traffic approach to city networks. Urban Studies, 47(10): 2195–2215. doi: https://doi.org/10.1177/0042098009357352
Neal Z, 2011a. Differentiating centrality and power in the world city network. Urban Studies, 48(13): 2733–2748. doi: https://doi.org/10.1177/0042098010388954
Neal Z P, 2011b. From central places to network bases: a transition in the U.S. urban hierarchy, 1900–2000. City & Community, 10(1): 49–75. doi: https://doi.org/10.1111/j.1540-6040.2010.01340.x
Reilly W J, 1929. Methods for the Study of Retail Relationships. Texas: University of Texas.
Ren Y, Ercsey-Ravasz M, Wang P et al., 2014. Predicting commuter flows in spatial networks using a radiation model based on temporal ranges. Nature Communications, 5: 5347. doi: https://doi.org/10.1038/ncomms6347
Sassen S, 2002. Locating cities on global circuits. Environment and Urbanization, 14(1): 13–30. doi: https://doi.org/10.1630/095624702101286034
Simini F, González M C, Maritan A et al., 2012. A universal model for mobility and migration patterns. Nature, 484(7392): 96–100. doi: https://doi.org/10.1038/nature10856
Stefanouli M, Polyzos S, 2017. Gravity vs radiation model: two approaches on commuting in Greece. Transportation Research Procedia, 24: 65–72. doi: https://doi.org/10.1016/j.trpro.2017.05.069
Tan Y T, Xu H, Zhang X L, 2016. Sustainable urbanization in China: a comprehensive literature review. Cities, 55: 82–93. doi: https://doi.org/10.1016/j.cities.2016.04.002
Taylor P J, Hoyler M, Verbruggen R, 2010. External urban relational process: introducing central flow theory to complement central place theory. Urban Studies, 47(13): 2803–2818. doi: https://doi.org/10.1177/0042098010377367
Taylor P J, Derudder B, Faulconbridge J et al., 2014. Advanced producer service firms as strategic networks, global cities as strategic places. Economic Geography, 90(3): 267–291. doi: https://doi.org/10.1111/ecge.12040
Thapa R B, Murayama Y, 2010. Drivers of urban growth in the Kathmandu valley, Nepal: examining the efficacy of the analytic hierarchy process. Applied Geography, 30(1): 70–83. doi: https://doi.org/10.1016/j.apgeog.2009.10.002
Tian Y, Wang L, 2019. Mutualism of intra- and inter-prefecture level cities and its effects on regional socio-economic development: a case study of Hubei Province, Central China. Sustainable Cities and Society, 44: 16–26. doi: https://doi.org/10.1016/j.scs.2018.09.033
Ullman, E L, 1941. A theory of location for cities. American Journal of Sociology, 46(6): 853–864.
van Meeteren M, Poorthuis A, Derudder B et al., 2016. Pacifying Babel’s Tower: a scientometric analysis of polycentricity in urban research. Urban Studies, 53(6): 1278–1298. doi: https://doi.org/10.1177/0042098015573455
Wang F H, Xu Y Q, 2011. Estimating O-D travel time matrix by Google Maps API: implementation, advantages, and implications. Annals of GIS, 17(4): 199–209. doi: https://doi.org/10.1080/19475683.2011.625977
Watts D J, Strogatz S H, 1998. Collective dynamics of ‘small-world’ networks. Nature, 393(6684): 440–442. doi: https://doi.org/10.1038/30918
Wesolowski A, O’Meara W P, Eagle N et al., 2015. Evaluating spatial interaction models for regional mobility in Sub-Saharan Africa. PLoS Computational Biology, 11(7): e1004267. doi: https://doi.org/10.1371/journal.pcbi.1004267
Xia C, Zhang A Q, Wang H J et al., 2019. Bidirectional urban flows in rapidly urbanizing metropolitan areas and their macro and micro impacts on urban growth: a case study of the Yangtze River middle reaches megalopolis, China. Land Use Policy, 82: 158–168. doi: https://doi.org/10.1016/j.landusepol.2018.12.007
Yang H R, Dijst M, Witte P et al., 2019. Comparing passenger flow and time schedule data to analyse High-Speed Railways and urban networks in China. Urban Studies, 56(6): 1267–1287. doi: https://doi.org/10.1177/0042098018761498
Ye Qiang, Zhang Lixuan, Peng Peng, et al., 2017. The network characteristics of urban agglomerations in the Middle Reaches of the Yangtze River based on Baidu migration data. Economic Geography, 37(8): 53–59. (in Chinese)
Zhang T L, Sun B D, Li W, 2017. The economic performance of urban structure: from the perspective of Polycentricity and Monocentricity. Cities, 68: 18–24. doi: https://doi.org/10.1016/j.cities.2017.05.002
Zhao Ziyu, Wei Ye, Wang Shijun et al., 2017. Measurement of directed alternative centricity and power of directed weighted urban network: a case of population flow network of China during ‘Chunyun’ period. Geographical Research, 36(4): 647–660. (in Chinese)
Zhen F, Qin X, Ye X Y et al., 2019. Analyzing urban development patterns based on the flow analysis method. Cities, 86: 178–197. doi: https://doi.org/10.1016/j.cities.2018.09.015
Zheng Wensheng, Run Jiying, Zhuo Rongrong et al., 2016. Evolution process of urban spatial pattern in Hubei Province based on DMSP/OLS nighttime light data. Chinese Geographical Science, 26(3): 366–376. doi: https://doi.org/10.1007/s11769-016-0814-1
Zhong C, Arisona S M, Huang X F et al., 2014. Detecting the dynamics of urban structure through spatial network analysis. International Journal of Geographical Information Science, 28(11): 2178–2199. doi: https://doi.org/10.1080/13658816.2014.914521
Zhou D, Xu J C, Wang L et al., 2015. Assessing urbanization quality using structure and function analyses: a case study of the urban agglomeration around Hangzhou Bay (UAHB), China. Habitat International, 49: 165–176. doi: https://doi.org/10.1016/j.habitatint.2015.05.020
Zipf G K, 1946. The P1P2/D hypothesis: on the intercity movement of persons. American Sociological Review, 11(6): 677–686.
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The authors would like to thank Professor Fahui Wang of Louisiana State University for his valuable suggestions.
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Foundation item: Under the auspices of National Social Science Foundation of China (No. 17BJL052)
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Zheng, W., Kuang, A., Wang, X. et al. Measuring Network Configuration of the Yangtze River Middle Reaches Urban Agglomeration: Based on Modified Radiation Model. Chin. Geogr. Sci. 30, 677–694 (2020). https://doi.org/10.1007/s11769-020-1131-2
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DOI: https://doi.org/10.1007/s11769-020-1131-2