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Supervised Regionalization Methods: A Survey

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  • 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.

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Bibliographic Info

Article provided by in its journal International Regional Science Review.

Volume (Year): 30 (2007)
Issue (Month): 3 (July)
Pages: 195-220

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Handle: RePEc:sae:inrsre:v:30:y:2007:i:3:p:195-220

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Keywords: regionalization; constrained clustering; analytical regions;

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