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Supervised Regionalization Methods: A Survey

Author

Listed:
  • Juan Carlos Duque

    (Regional Analysis Laboratory (REGAL), Department of Geography, San Diego State University, jduque@rohan.sdsu.edu)

  • Raúl Ramos

    (Grup d'Anà lisi Quantitativa Regional (AQR), Universitat de Barcelona, rramos@ub.edu)

  • Jordi Suriñach

    (Grup d'Anà lisi Quantitativa Regional (AQR), Universitat de Barcelona, jsurinach@ub.edu)

Abstract

This article reviews almost four decades of contributions on the subject of supervised regionalization methods. These methods aggregate a set of areas into a predefined number of spatially contiguous regions while optimizing certain aggregation criteria. The authors present a taxonomic scheme that classifies a wide range of regionalization methods into eight groups, based on the strategy applied for satisfying the spatial contiguity constraint. The article concludes by providing a qualitative comparison of these groups in terms of a set of certain characteristics, and by suggesting future lines of research for extending and improving these methods.

Suggested Citation

  • Juan Carlos Duque & Raúl Ramos & Jordi Suriñach, 2007. "Supervised Regionalization Methods: A Survey," International Regional Science Review, , vol. 30(3), pages 195-220, July.
    • Handle: RePEc:sae:inrsre:v:30:y:2007:i:3:p:195-220
    DOI: 10.1177/0160017607301605
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    More about this item

    Keywords

    regionalization; constrained clustering; analytical regions;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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