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Characterising the Morphology of Suburban Settlements: A Method Based on a Semi-automatic Classification of Building Clusters

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  • Fabian de Smet
  • Jacques Teller

Abstract

Urban sprawl is transforming our landscapes and rural areas at a spectacular pace. Measuring the strength of the phenomenon and proposing dynamic ways to delineate suburban areas have been the object of much debate amongst scientists. The present article takes the view that, beyond measuring and delineating suburban areas, more efforts should be directed to qualifying the morphology of built settlements within these areas. Therefore, it proposes a method based on a semi-automatic classification system of building clusters, designed to describe and interpret the phenomenon from a morphological perspective. This method is based on a combination of field surveys with numerical analyses of digital land cadastre maps. The application of this classification system to the suburban area around Liege reveals that, far from developing in a complete indifference of local conditions, contemporary suburban settlements are influenced by landscape structures inherited from the past.

Suggested Citation

  • Fabian de Smet & Jacques Teller, 2016. "Characterising the Morphology of Suburban Settlements: A Method Based on a Semi-automatic Classification of Building Clusters," Landscape Research, Taylor & Francis Journals, vol. 41(1), pages 113-130, January.
    • Handle: RePEc:taf:clarxx:v:41:y:2016:i:1:p:113-130
    DOI: 10.1080/01426397.2015.1045464
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    Cited by:

    1. Ronchi, Silvia & Pontarollo, Nicola & Serpieri, Carolina, 2021. "Clustering the built form at LAU2 level for addressing sustainable policies: Insights from the Belgium case study," Land Use Policy, Elsevier, vol. 109(C).
    2. Ahmed Mustafa & Anton Van Rompaey & Mario Cools & Ismaïl Saadi & Jacques Teller, 2018. "Addressing the determinants of built-up expansion and densification processes at the regional scale," Urban Studies, Urban Studies Journal Limited, vol. 55(15), pages 3279-3298, November.

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