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Urbanization in some hierarchical urban models.

H Beguin, D Peeters

    Regional Science and Urban Economics
    |February 1, 1981
    PubMed
    Summary

    This study analyzes urban population and urbanization ratios in hierarchical urban models with varying levels. Findings suggest approximations for simplifying complex analysis of urban systems.

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    Area of Science:

    • Urban and Regional Planning
    • Geographic Information Science
    • Computational Social Science

    Background:

    • Hierarchical urban models are crucial for understanding city structures.
    • Analyzing population and urbanization dynamics requires sophisticated modeling approaches.
    • Existing models may present analytical complexities with increasing hierarchical levels.

    Purpose of the Study:

    • To investigate variations in total urban population and urbanization ratio.
    • To examine these variations in relation to the number of hierarchical levels in urban models.
    • To identify and propose approximations for tractable analysis of complex urban systems.

    Main Methods:

    • Analysis of four distinct categories of hierarchical urban models.
    • Examination of population and urbanization ratio variations across different model types.
    Keywords:
    Demographic FactorsGeographic FactorsModels, TheoreticalPopulationPopulation CharacteristicsResearch MethodologySpatial DistributionUrban PopulationUrban Spatial DistributionUrbanization

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  • Development of approximations to simplify complex analytical results.

    • Main Results:

    • Observed variations in total urban population based on hierarchical structure.
    • Identified changes in urbanization ratio with increasing hierarchical levels.
    • Demonstrated the complexity of results, necessitating analytical simplifications.

    Conclusions:

    • Hierarchical levels significantly influence urban population and urbanization ratios.
    • The complexity of these variations requires simplified analytical approaches.
    • The proposed approximations enhance the tractability of hierarchical urban model analysis.