Spatial Comparison of Population Distribution Patterns of the 50 Largest Cities in the World
Abstract
Evaluating the trends of population density on a spatial scale is a crucial way to examine the urban structure, which shows the urban form, including size, density, distribution, and composition. The relationship between population increase and change in the spatial distribution has attracted widespread concern on geographers. This study focuses on the gradient distance from the urban centers of the world's 50 largest cities using LandScan™ population data. For each city, the urban center is demarcated based on a landmark place, and population density is calculated using concentric buffers from the urban center. The spatial analysis using the population density model and ArcGIS has been employed for estimating the population distribution patterns. The fitting function method was applied to the 50 cities, and the MATLAB compiler was used for generating functions. The five basic spatial patterns based on distance decay effect were derived from the analysis: sharpest (7 cities), very sharp (17 cities), sharp (12 cities), moderate (8 cities), and Gaussian distribution (6 cities). It is found that the spatial patterns of population distribution in these cities were associated with various global, regional, and national factors. In this context, cities' spatial patterns demonstrated the differences between developing and developed countries. Although the framework of the approach built on the classical methodology of urban geography, the result of the analysis has deepened the understanding of urban complexity and paved a path for developing future urban theories.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMIN0060001W
- Keywords:
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- 1906 Computational models;
- algorithms;
- INFORMATICS;
- 1914 Data mining;
- INFORMATICS;
- 1942 Machine learning;
- INFORMATICS;
- 1952 Modeling;
- INFORMATICS