Preview

Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya

Advanced search

Modeling Connections in Urban Networks: Distance, Gravity, Radiation (the Case of the USA)

https://doi.org/10.7868/S2658697525050017

Abstract

The network revolution has breathed new life into the study of spatial nodal structures. While data on the centers and their characteristics are often available, data on connections are still relatively rare, especially when it is necessary to consider network dynamics over a long period of time. This makes it relevant to consider various approaches to modeling connections between points with known attributes. Such approaches can be grouped into three: nearest neighbor, gravity, and radiation models. The first two have become quite widespread in human geography, spatial economics and regional studies, while radiation models were proposed just over a decade ago and remain little known. We understand the volume of connections in urban networks as the potential volume of diverse flows between them. We model the US urban network for 2010 in three variants. Then we focus on geographical and structural differences and provide some quantitative comparisons. The nearest neighbor method makes it easy to identify the main dividing lines in the urban network and show the main urbanization gradients, but does not allow one to evaluate the strength of connections and misses their multiplicity. The gravity model depends on the calibration of the distance decay parameter and prioritizes links between nearby large cities as well as upward links between medium-sized cities and their nearest large neighbor, emphasizing the hierarchy of urban networks. The radiation model gives more weight to links between nearby cities of similar sizes and shows a smaller range of link strengths, emphasizing the “flat” nature of the network ontology.

About the Authors

R. A. Dokhov
Lomonosov Moscow State University; Institute of Geography, Russian Academy of Sciences
Russian Federation

Moscow



M. A. Topnikov
Institute of Geography, Russian Academy of Sciences
Russian Federation

Moscow



A. S. Voloshok
Institute of Geography, Russian Academy of Sciences
Russian Federation

Moscow



References

1. Anderson J. Ideology in geography: an introduction. Antipode, 1985, vol. 17, no. 2–3, pp. 28–34.

2. Batty M. The New Science of Cities. MIT Press, 2013. 520 p.

3. Berry B.J.L. Cities as systems within systems of cities. Pap. Reg. Sci., 1964, vol. 13, no. 1, pp. 147–163.

4. Blanutsa V.I. Geographical investigation of the network world: Basic principles and promising directions. Geogr. Nat. Resour., 2012, vol. 33, pp. 1–9.

5. Blumenfeld-Lieberthal E., Portugali J. Network cities: A complexity-network approach to urban dynamics and development. In Geospatial Analysis and Modelling of Urban Structure and Dynamics. Springer Netherlands, 2010, pp. 77–90.

6. Bretagnolle A., Delisle F., Mathian H., Vatin G. Urbanization of the United States over two centuries: an approach based on a long-term database (1790– 2010). Int. J. Geogr. Inf. Sci., 2015, vol. 29, no. 5, pp. 850–867.

7. Camagni R. P., Salone C. Network urban structures in northern Italy: elements for a theoretical framework. Urban Stud., 1993, vol. 30, no. 6, pp. 1053–1064.

8. Derudder B. Network analysis of ‘urban systems’: potential, challenges, and pitfalls. Tijdschr. Econ. Soc. Geogr., 2021, vol. 112, no. 4, pp. 404–420.

9. Elliott H.M. Macrocalifornia and the Urban Gradient. Calif. Geogr., 1981, vol. 21, pp. 1–17.

10. Elliott H.M. The Pacific coast nearest larger neighbor gradient. APCG Yearbook, 1982, vol. 44, pp. 29–45.

11. Elliott H.M. Surrounding larger neighbors and the Atlantic coast cardinal neighbor gradient. Econ. Geogr., 1983, vol. 59, no. 4, pp. 426–444.

12. Elliott H.M. Cardinal place geometry in the American South. Southeast. Geogr., 1984a, vol. 24, no. 2, pp. 65–77.

13. Elliott H.M. Cardinal Places and the Urban Gradient. Urban Geogr., 1984b, vol. 5, no. 3, pp. 223–239.

14. Elliott H.M. Cardinal place geometry. Geogr. Anal., 1985, vol. 17, no. 1, pp. 16–35.

15. Elliott H.M. Changing spatial structure in the Rocky Mountain regional system. APCG Yearbook, 1986, vol. 48, pp. 149–167.

16. Evteev O.A. The map of the potential of the settlement field as a special type of image of the population of the territory. Vestn. Mosk. Univ., Ser. 5: Geogr., 1969, no. 2, pp. 72–76. (In Russ.).

17. Florida R. The world is spiky. Atl.Mo., 2005, vol. 296, no. 3, pp. 48–51.

18. Florida R., Gulden T., Mellander C. The rise of the mega-region. Camb. J. Reg. Econ. Soc., 2008, vol. 1, no. 3, pp. 459–476.

19. Friedman T. The World is Flat: A Brief History of the Globalized World in the 21st Century. New York: Farrar, Straus and Giroux, 2005. 488 p.

20. Fujita M., Krugman P.R., Venables A. The spatial economy: Cities, regions, and international trade. MIT press, 2001. 367 p.

21. Glezer O.B. Using urban population potential surface for analyzing urbanization in rural areas (with particular reference to Dagestan ASSR). Soviet Geography, 1985, vol. XXVI, no. 4, pp. 252–267.

22. Haggett P., Chorley R.J. Models, paradigms and the new geography. In Integrated Models in Geography. Worcester, London: Methuen & Co, 1967, pp. 19–41.

23. Khanna P. Connectography: Mapping the future of global civilization. New York: Penguin Random House, 2016. 496 p.

24. Lee S., Joo H. Passenger and freight travel patterns: A cluster analysis based on urban networks. PloS ONE, 2025, vol. 20, no. 3, art. e0318084.

25. Lenormand M., Huet S., Gargiulo F., Deffuant G. A universal model of commuting networks. PLoS ONE, 2012, vol. 7, no. 10, art. e45985.

26. Lukermann F., Porter P.W. Gravity and potential models in economic geography. Ann. Assoc. Am. Geogr., 1960, vol. 50, no. 4, pp. 493–504.

27. Masucci A.P., Serras J., Johansson A., Batty M. Gravity versus radiation models: On the importance of scale and heterogeneity in commuting flows. Phys. Rev. E, 2013, vol. 88, no. 2, art. 022812.

28. Marston S.A., Jones III J.P., Woodward K. Human geography without scale. Trans. Inst. Br. Geogr., 2005, vol. 30, no. 4, pp. 416–432.

29. Medvedkov Yu.V. Ekonomgeograficheskaya izuchennost’ raionov kapitalisticheskogo mira. T. 2 [Economic-Geographical State of Knowledge of the Regions of the Capitalist World. Vol. 2]. Moscow: VINITI Publ., 1965.

30. Okabe A. Satoh T., Furuta T., Suzuki A., Okano K. Generalized network Voronoi diagrams: Concepts, computational methods, and applications. Int. J. Geogr. Inf. Sci., 2008, vol. 22, no. 9, pp. 965–994.

31. Piovani D., Arcaute E., Uchoa G., Wilson A., Batty M. Measuring accessibility using gravity and radiation models. R. Soc. Open Sci., 2018, vol. 5, no. 9, art. 171668.

32. Polyan P.M. Study of territorial structures by the potential method (using the example of machine-building industry of foreign European countries-members of the Comecon). Izv. Akad. Nauk SSSR, Ser. Geogr., 1976, no. 4, pp. 94–101. (In Russ.).

33. Popov F. On aims and methods in the study of urban zones of mental influence. Gorod. Issled. Praktiki, 2017, vol. 2, no. 2, pp. 13–32. (In Russ.).

34. Pumain D., Reuillon R. Urban dynamics and simulation models. Cham: Springer, 2017. 123 p.

35. Reilly W.J. The law of retail gravitation. New York: Knickerbocker Press, 1931. 75 p.

36. Ren Y., Ercsey-Ravasz M., Wang P., González M. C., Toroczkai Z. Predicting commuter flows in spatial networks using a radiation model based on temporal ranges. Nat. Commun., 2014, vol. 5, no. 1, art. 5347.

37. Ricardo D. On the principles of political economy and taxation. London: John Murray, 1817. 589 p.

38. Sheludkov A.V., Orlov M.A. Topology of a settlement network as a factor of rural population dynamics (a case study of Tyumen oblast). Reg. Res. Rus., 2020, vol. 10, no. 3, pp. 388–400. https://doi.org/10.1134/s2079970520030119

39. Simini F., González M.C., Maritan A., Barabási A.L. A universal model for mobility and migration patterns. Nature, 2012, vol. 484, no. 7392, pp. 96–100.

40. Simini F., Maritan A., Néda Z. Human mobility in a continuum approach. PloS ONE, 2013, vol. 8, no. 3, art. e60069.

41. Sinitsyn N.A. Regionalization of Russia-Belarus borderlands with demographic potential method. Reg. Issled., 2021, no. 2, pp. 32–47. (In Russ.).

42. Smirnyagin L.V. Delineation of the influence zones of cities by the method of main potentials. In Problemy sovremennoi urbanizatsii [Problems of Modern Urbanization]. Moscow: MFGO Publ., 1985, pp. 95– 105. (In Russ.).

43. Smirnyagin L.V. Raiony SShA: portret sovremennoi Ameriki [The Regions of the United States: A Portrait of Modern America]. Moscow: Mysl’ Publ., 1989. 380 p.

44. Smirnyagin L.V. Regionalization of society: Methodology and algorithms. In Voprosy ekonomicheskoi i politicheskoi geografii zarubezhnykh stran. T. 19 [Issues of Economic and Political Geography of Foreign Countries. Vol. 19]. Moscow, Smolensk: Oikumena Publ., 2011a, pp. 55–82. (In Russ.).

45. Smirnyagin L.V. Megaregions as a new form of the territorial organization of society. Vestn. Mosk. Univ., Ser. 5: Geogr., 2011b, no. 1, pp. 9–15. (In Russ.).

46. Smith A. An inquiry into the nature and causes of the wealth of nations. Vol. 1. London: Printed for W. Strahan and T. Cadell, 1776. 510 p.

47. Stouffer S.A. Intervening opportunities: a theory relating mobility and distance. Am. Sociol. Rev., 1940, vol. 5, no. 6, pp. 845–867.

48. Treivish A.I. The attempt of delineation of zones of potential influence of the USSR cities. In Problemy sovremennoi urbanizatsii [Problems of Modern Urbanization]. Moscow: MFGO Publ., 1985, pp. 105–113. (In Russ.).

49. Uitermark J., van Meeteren M. Geographical network analysis. Tijdschr. Econ. Soc. Geogr., 2021, vol. 112, no. 4, pp. 337–350.

50. Voronoi G. Nouvelles applications des paramètres continus à la théorie des formes quadratiques. Deuxième mémoire. Recherches sur les parallélloèdres primitifs. J. Reine Angew. Math., 1908, no. 134, pp. 198–287. (In French).

51. Wen H., Zhao D., Wang W., Hua X., Yu W. Exploring the spatial distribution structure of intercity human mobility networks under multimodal transportation systems in China. J. Trans. Geogr., 2025, vol. 123, art. 104144.

52. Wilson A.G., Senior M.L. Some Relationships between Entropy Maximizing Models, Mathematical Programming Models, and Their Duals. J. Reg. Sci., 1974, vol. 14, no. 2, pp. 207–215.

53. Yang Y. Herrera C., Eagle N., González M.C. Limits of predictability in commuting flows in the absence of data for calibration. Sci. Rep., 2014, vol. 4, no. 1, art. 5662.


Review

For citations:


Dokhov R.A., Topnikov M.A., Voloshok A.S. Modeling Connections in Urban Networks: Distance, Gravity, Radiation (the Case of the USA). Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya. 2025;89(5):685-698. (In Russ.) https://doi.org/10.7868/S2658697525050017

Views: 174

JATS XML

ISSN 2587-5566 (Print)
ISSN 2658-6975 (Online)