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The generation of spatial population distributions from census centroid data.

I Bracken, D Martin

    Environment & Planning A
    |April 1, 1989
    PubMed
    Summary

    This study presents a novel method for generating population distribution surfaces from centroid data. This approach overcomes geographical limitations, enhancing the utility of census data for analysis and planning.

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    Area of Science:

    • Geographic Information Science
    • Spatial Analysis
    • Demography

    Background:

    • Census data is crucial for geographical analysis and planning.
    • Disaggregate census data presents enumeration challenges due to zonal geography.
    • Existing methods may not fully capture population distribution at finer scales.

    Purpose of the Study:

    • To introduce a novel surface generation approach for population distribution.
    • To overcome limitations of zonal geography in census data analysis.
    • To enhance the analytical and policy applications of census data.

    Main Methods:

    • Utilizes centroid-based data for population surface generation.
    • Develops a method independent of predefined geographical zones.
    Keywords:
    CensusDeveloped CountriesEconomic ConditionsEconomic FactorsEstimation TechnicsEuropeGeographic FactorsGeographyMacroeconomic FactorsMethodological StudiesNorthern EuropePopulationPopulation StatisticsResearch MethodologySocial SciencesSocioeconomic FactorsSpatial DistributionUnited KingdomWales

    Related Experiment Videos

  • Applies the approach to a case study in South Wales, UK.

    • Main Results:

    • Successfully generated a population distribution surface from centroid data.
    • Demonstrated independence from zonal geography, revealing underlying population patterns.
    • Illustrated the method's applicability in a specific geographical context.

    Conclusions:

    • The proposed surface generation method enhances census data value.
    • This approach supports diverse analytical, cartographic, and policy objectives.
    • It facilitates the creation of spatial indicators for socio-economic conditions.