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

• Main Authors: Perlada, Camille D., Orden, Alfiero K., II, Cirunay, Michelle T., Batac, Rene C.
• Format: text
• Published: Animo Repository 2019
• Subjects: Scaling laws (Statistical physics); Cities and towns—Growth; Roads—Interchanges and intersections; Physics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/5935
• Institution: De La Salle University

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" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative;">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.