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Methodological foundation of a numerical taxonomy of urban form

Author

Listed:
  • Martin Fleischmann
  • Alessandra Feliciotti
  • Ombretta Romice
  • Sergio Porta

Abstract

Cities are complex products of human culture, characterised by a startling diversity of visible traits. Their form is constantly evolving, reflecting changing human needs and local contingencies, manifested in space by many urban patterns. Urban morphology laid the foundation for understanding many such patterns, largely relying on qualitative research methods to extract distinct spatial identities of urban areas. However, the manual, labour-intensive and subjective nature of such approaches represents an impediment to the development of a scalable, replicable and data-driven urban form characterisation. Recently, advances in geographic data science and the availability of digital mapping products open the opportunity to overcome such limitations. And yet, our current capacity to systematically capture the heterogeneity of spatial patterns remains limited in terms of spatial parameters included in the analysis and hardly scalable due to the highly labour-intensive nature of the task. In this paper, we present a method for numerical taxonomy of urban form derived from biological systematics, which allows the rigorous detection and classification of urban types. Initially, we produce a rich numerical characterisation of urban space from minimal data input, minimising limitations due to inconsistent data quality and availability. These are street network, building footprint and morphological tessellation, a spatial unit derivative of Voronoi tessellation, obtained from building footprints. Hence, we derive homogeneous urban tissue types and, by determining overall morphological similarity between them, generate a hierarchical classification of urban form. After framing and presenting the method, we test it on two cities – Prague and Amsterdam – and discuss potential applications and further developments. The proposed classification method represents a step towards the development of an extensive, scalable numerical taxonomy of urban form and opens the way to more rigorous comparative morphological studies and explorations into the relationship between urban space and phenomena as diverse as environmental performance, health and place attractiveness.

Suggested Citation

  • Martin Fleischmann & Alessandra Feliciotti & Ombretta Romice & Sergio Porta, 2022. "Methodological foundation of a numerical taxonomy of urban form," Environment and Planning B, , vol. 49(4), pages 1283-1299, May.
  • Handle: RePEc:sae:envirb:v:49:y:2022:i:4:p:1283-1299
    DOI: 10.1177/23998083211059835
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    References listed on IDEAS

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    1. Juan C. Duque & Luc Anselin & Sergio J. Rey, 2012. "The Max-P-Regions Problem," Journal of Regional Science, Wiley Blackwell, vol. 52(3), pages 397-419, August.
    2. Geoffrey CARUSO & Mohamed HILAL & Isabelle THOMAS, 2017. "Measuring urban forms from inter-building distances: Combining MST graphs with a local index of spatial association," LIDAM Reprints CORE 2837, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Miguel Serra & Sophia Psarra & Jamie O'Brien, 2018. "Social and Physical Characterization of Urban Contexts: Techniques and Methods for Quantification, Classification and Purposive Sampling," Urban Planning, Cogitatio Press, vol. 3(1), pages 58-74.
    4. Castro, Kássia Batista de & Roig, Henrique Llacer & Neumann, Marina Rolim Bilich & Rossi, Maria Silvia & Seraphim, Ana Paula Albuquerque Campos Castalonga & Réquia, Weeberb João & Costa, Alexandre Bar, 2019. "New perspectives in land use mapping based on urban morphology: A case study of the Federal District, Brazil," Land Use Policy, Elsevier, vol. 87(C).
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    Cited by:

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