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Geospatial simulation of urban neighbourhood densification potentials

  • Sven Eggimann*
  • , Michael Wagner
  • , Yoo Na Ho
  • , Mirjam Züger
  • , Ute Schneider
  • , Kristina Orehounig
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Although densification of urban areas is being proposed as a sustainable urbanisation strategy, frameworks for detailed large-scale analysis of densification potentials and their evaluation are lacking. A geospatial simulation framework is presented to assess and evaluate densification potentials at the neighbourhood level of already built-up residential areas. The focus is on post-war neighbourhoods, which are particularly promising for sustainable densification. Neighbourhoods are localised using geospatial analysis and based on literature and architectural designs, potentials are estimated for different neighbourhood archetypes and densification strategies. Potentials are simulated at a national scale using supervised archetype classification. The embeddedness into current mobility infrastructure is used as a proxy for evaluating the sustainability of neighbourhood densification. The developed framework is tested for Switzerland. Depending on the densification strategy, the simulated additional inhabitants for populating post-war urban neighbourhoods range between 4–15 % of the current population. More than half of this potential is located in central areas and is well connected by public transportation. The presented approach is suitable for assessing spatially explicit densification potential and for prioritising densification locations. We show that in countries with a high number of post-war neighbourhoods in well-connected locations, considerable densification opportunities could be realised in already built-up residential areas.

Original languageEnglish
Article number103068
JournalSustainable Cities and Society
Volume72
DOIs
StatePublished - Sep 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Author(s)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  2. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Archetype
  • Compact city
  • Machine learning
  • Redensification
  • Urban design
  • Urban structure unit

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