A data-based approach to identifying regional typologies and exemplars across the urban–rural gradient in Europe using affinity propagation. Issue 12 (2nd December 2021)

• Record Type: Journal Article
• Authors: Fiaschetti, Maurizio; Graziano, Marcello; Heumann, Benjamin W.
• Is Part Of: Regional studies. Volume 55:Issue 12(2021)
• Page Start: 1939
• Page End: 1954
• Publication Date: 2021-12-02
• Subjects: rural -- urban -- affinity propagation -- European Union; C10 -- O52 -- R14; Regional planning -- Periodicals; Regional planning -- Great Britain -- Periodicals; 307.14
• DOI: 10.1080/00343404.2021.1871598
• Languages: English
• ISSNs: 0034-3404

Abstract

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.