Looking for energy in demographic data; how to detect self-organization in human population distribution

TL;DR

This paper investigates how demographic data and energy consumption influence urban growth patterns, revealing self-organizing behaviors and spatial frequencies that evolve over time in human population distributions.

Contribution

It introduces a general model linking city growth to initial population and energy use, and applies spectral analysis to identify persistent spatial patterns in demographic data.

Findings

Identification of spatial frequencies that reinforce over time

Detection of self-organizing patterns in population distribution

Mapping of socioeconomic influences on urban growth

Abstract

In the present work we study the relationship between population allocation and the combined effects of urban size and energy consumption, for two given areas and through a major part of the twentieth century. Along these lines a general application model is laid down which relates city-growth rates to initial inhabitants and to exosomatic energy increment, the deviations from it showing order in space and time; as shown in a series of maps which hint at unaccounted socioeconomic factors. The study of the maps by means of spectral analysis allows finding patterns which reinforce over time, in such a manner that spatial frequencies can be determined whose weight increases up so granting surface evolution estimation.