Quantifying the organization of urban elements through the statistical distributions of their spatial spreading metrics

Camille D. Perlada, Alfiero K. Orden, Michelle T. Cirunay and Rene C. Batac

Physica A: Statistical Mechanics and its Applications, 2021, vol. 568, issue C

Abstract: We probe the underlying organization emerging out of the growth of urban settlements by using various measures that quantify their spatial spreading. In particular, we report the emergence of fat-tailed regimes in the distributions of the three metrics we investigated in the case of the self-organized Metro Manila conurbation: (1) the city road lengths and the areas of road-bounded blocks; (2) the Voronoi areas, the effective “areas of influence” of each of the buildings in the city; and (3) the k-nearest-neighbor (kNN) distances of economic structures in the city. Statistical goodness-of-fit tests are conducted to obtain representative decaying power-law trends for these fat-tailed distributions, as a first approximation for the scaling behavior, particularly at the largest scales. The obtained distributions are found to differ significantly from the corresponding results generated from memoryless null models. The key insights from these data analyses add to the growing literature on quantitative characterizations of urban zones, and may help uncover the underlying mechanics responsible for growth.

Keywords: Cities; Scaling phenomena in complex systems; Road networks; Self-organization of complex systems (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120310153
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:568:y:2021:i:c:s0378437120310153

DOI: 10.1016/j.physa.2020.125717

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().