Measuring Global Urban Complexity from the Perspective of Living Structure
Andy Jingqian Xue, Chenyu Huang, Bin Jiang

TL;DR
This paper introduces a method to measure global urban complexity based on hierarchical living structures, revealing increasing complexity in Earth's urban surface through geospatial data analysis.
Contribution
It develops a recursive approach to identify natural cities worldwide and quantifies urban complexity using hierarchical network analysis from multisource geospatial data.
Findings
Earth's surface complexity is increasing from an economic perspective.
Nighttime light imagery reveals more explicit urban dynamics than population data.
Urban complexity growth is linked to hierarchical living structures.
Abstract
As urban critic Jane Jacobs conceived, a city is essentially the problem of organized complexity. What underlies the complexity refers to a structural factor, called living structure, which is defined as a mathematical structure composed of hierarchically organized substructures. Through these substructures, the complexity of cities, or equivalent to the livingness of urban space (L), can be measured by the multiplication the number of cities or substructures (S) and their scaling hierarchy (H), indicating that complexity is about both quantity of cities and how well the city is organized hierarchically. In other words, complexity emerges from a hierarchical structure where there are far more small cities or substructures than large ones across all scales, and cities are more or less similar within each individual hierarchical level. In this paper, we conduct comprehensive case studies…
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Taxonomy
TopicsEconomic and Technological Innovation
