Hierarchical Scaling in Systems of Natural Cities

TL;DR

This paper demonstrates that natural cities follow hierarchical scaling laws, which can be modeled by exponential functions leading to power laws, and shows that their evolution is driven by entropy maximization principles.

Contribution

It reveals the hierarchical scaling laws in natural city systems and links their development to entropy maximization, providing a new understanding of city size and area distributions.

Findings

Natural cities follow hierarchical scaling laws.

Size and area distributions fit power laws within certain ranges.

Hierarchical conservation law is supported by empirical data.

Abstract

Hierarchies can be modeled by a set of exponential functions, from which we can derive a set of power laws indicative of scaling. The solution to a scaling relation equation is always a power law. The scaling laws are followed by many natural and social phenomena such as cities, earthquakes, and rivers. This paper is devoted to revealing the power law behaviors in systems of natural cities by reconstructing the hierarchy with cascade structure. The cities of America, Britain, France, and Germany are taken as examples to make empirical analyses. The hierarchical scaling relations can be well fitted to the data points within the scaling ranges of the size and area of the natural cities. The size-number and area-number scaling exponents are close to 1, and the allometric scaling exponent is slightly less than 1. The results show that natural cities follow hierarchical scaling laws and hierarchical conservation law very well. The hierarchical scaling law proved to be derived from entropy maximization principle, and this suggests that the evolution of natural cities is dominated by entropy maximization laws. This study is helpful for scientists to understand the power law behavior in the development of cities and systems of cities.