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Delineation of Demographic Regions with GIS and Computational Intelligence

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  • Thomas Hatzichristos

    (Department of Geography and Regional Planning, National Technical University of Athens, Zografou Campus, Iroon Polytexneiou 9, 15780 Zografou, Greece)

Abstract

This paper presents a methodology for the creation of homogeneous demographic regions with geographical information systems (GIS) and computational intelligence. The proposed method is unsupervised fuzzy classification performed by neural networks using the fuzzy Kohonen algorithm. GIS technology offers a powerful set of tools for the input, management, and output of data, whereas computational intelligence is used for the analysis and the classification of the data. The proposed methodology is applied to the municipality of Athens, in Greece. Finally the advantages and disadvantages of the approach are discussed.

Suggested Citation

  • Thomas Hatzichristos, 2004. "Delineation of Demographic Regions with GIS and Computational Intelligence," Environment and Planning B, , vol. 31(1), pages 39-49, February.
    • Handle: RePEc:sae:envirb:v:31:y:2004:i:1:p:39-49
    DOI: 10.1068/b1296
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    Cited by:

    1. Francisco Javier Abarca-Alvarez & Francisco Sergio Campos-Sánchez & Fernando Osuna-Pérez, 2019. "Urban Shape and Built Density Metrics through the Analysis of European Urban Fabrics Using Artificial Intelligence," Sustainability, MDPI, vol. 11(23), pages 1-23, November.

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