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The size distribution, scaling properties and spatial organization of urban clusters: A global and regional percolation perspective

Authors
/persons/resource/till.fluschnik

Fluschnik,  Till
Potsdam Institute for Climate Impact Research;

/persons/resource/kriewald

Kriewald,  Steffen
Potsdam Institute for Climate Impact Research;

/persons/resource/garcia.cantu.ros

García Cantú Ros,  Anselmo
Potsdam Institute for Climate Impact Research;

/persons/resource/Bin.Zhou

Zhou,  Bin
Potsdam Institute for Climate Impact Research;

/persons/resource/dominik.reusser

Reusser,  Dominik E.
Potsdam Institute for Climate Impact Research;

/persons/resource/Juergen.Kropp

Kropp,  Jürgen P.
Potsdam Institute for Climate Impact Research;

/persons/resource/Diego.Rybski

Rybski,  Diego
Potsdam Institute for Climate Impact Research;

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Citation

Fluschnik, T., Kriewald, S., García Cantú Ros, A., Zhou, B., Reusser, D. E., Kropp, J. P., Rybski, D. (2016): The size distribution, scaling properties and spatial organization of urban clusters: A global and regional percolation perspective. - ISPRS International Journal of Geo-Information, 5, 7, 110.
https://doi.org/10.3390/ijgi5070110


Cite as: https://publications.pik-potsdam.de/pubman/item/item_21221
Abstract
Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined by maximally connected urban clusters. The analysis of the city size distribution for all cities on the globe confirms Zipf’s law. Moreover, by investigating the percolation properties of the clustering of urban areas we assess the closeness to criticality for various countries. At the critical thresholds, the urban land cover of the countries undergoes a transition from separated clusters to a gigantic component on the country scale. We study the Zipf-exponents as a function of the closeness to percolation and find a systematic dependence, which could be the reason for deviating exponents reported in the literature. Moreover, we investigate the average size of the clusters as a function of the proximity to percolation and find country specific behavior. By relating the standard deviation and the average of cluster sizes—analogous to Taylor’s law—we suggest an alternative way to identify the percolation transition. We calculate spatial correlations of the urban land cover and find long-range correlations. Finally, by relating the areas of cities with population figures we address the global aspect of the allometry of cities, finding an exponent δ ≈ 0.85, i.e., large cities have lower densities.