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A data-based approach to identifying regional typologies and exemplars across the urban–rural gradient in Europe using affinity propagation

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  • Maurizio Fiaschetti
  • Marcello Graziano
  • Benjamin W. Heumann

Abstract

We apply recent developments in data-mining and statistics, using affinity propagation (AP) to identify regional typologies in the European Union (EU) and characterize major factors between rural–rural and rural–urban regional differences, without predetermined thresholds. We identify a representative ‘exemplar’ within each cluster using the drivers of Copus enriched with climate and land-cover/land-use variables to provide geographical context and pinpoint differences driven by natural and human–natural landscapes. Building upon the works of Dijkstra and the Eudora Project, we expand the dimensions of regional differences, introducing a threshold-less, data-driven model able to identify exemplars, and the main characteristics of each cluster or regional typology.

Suggested Citation

  • Maurizio Fiaschetti & Marcello Graziano & Benjamin W. Heumann, 2021. "A data-based approach to identifying regional typologies and exemplars across the urban–rural gradient in Europe using affinity propagation," Regional Studies, Taylor & Francis Journals, vol. 55(12), pages 1939-1954, December.
    • Handle: RePEc:taf:regstd:v:55:y:2021:i:12:p:1939-1954
    DOI: 10.1080/00343404.2021.1871598
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    Cited by:

    1. Jacek Batog & Barbara Batog, 2021. "Typology and Development of Local Administrative Units: Spatial Discriminant Analysis," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 548-569.
    2. Valentina Cattivelli, 2022. "Delimiting Rural Areas: Evidence from the Application of Different Methods Elaborated by Italian Scholars," Land, MDPI, vol. 11(10), pages 1-21, September.

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