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Exploring Options for Public Green Space Development: Research by Design and GIS-Based Scenario Modelling

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  • Philip Stessens

    (Building, Architecture & Town Planning Department, Université libre de Bruxelles, 1050 Brussels, Belgium)

  • Frank Canters

    (Cartography & GIS Research Group, Department of Geography, Vrije Universiteit Brussel, 1050 Brussels, Belgium)

  • Ahmed Z. Khan

    (Building, Architecture & Town Planning Department, Université libre de Bruxelles, 1050 Brussels, Belgium)

Abstract

Green spaces have a positive influence on human well-being. Therefore, an accurate evaluation of public green space provision is crucial for administrations to achieve decent urban environmental quality for all. Whereas inequalities in green space access have been studied in relation to income, the relation between neighbourhood affluence and remediation difficulty remains insufficiently investigated. A methodology is proposed for co-creating scenarios for green space development through green space proximity modelling. For Brussels, a detailed analysis of potential interventions allows for classification according to relative investment scales. This resulted in three scenarios of increasing ambition. Results of scenario modelling are combined with socio-economic data to analyse the relation between average income and green space proximity. The analysis confirms the generally accepted hypothesis that non-affluent neighbourhoods are on average underserved. The proposed scenarios reveal that the possibility of reaching a very high standard in green space proximity throughout the study area if authorities would be willing to allocate budgets for green space development that go beyond the regular construction costs of urban green spaces, and that the types of interventions require a higher financial investment per area of realised green space in non-affluent neighbourhoods.

Suggested Citation

  • Philip Stessens & Frank Canters & Ahmed Z. Khan, 2021. "Exploring Options for Public Green Space Development: Research by Design and GIS-Based Scenario Modelling," Sustainability, MDPI, vol. 13(15), pages 1-52, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8213-:d:599605
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    References listed on IDEAS

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    Cited by:

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    2. Giuseppe Salvia & Irene Pluchinotta & Ioanna Tsoulou & Gemma Moore & Nici Zimmermann, 2022. "Understanding Urban Green Space Usage through Systems Thinking: A Case Study in Thamesmead, London," Sustainability, MDPI, vol. 14(5), pages 1-24, February.
    3. Wanida Saetang & Supaporn Chai-Arayalert & Siriwan Kajornkasirat & Jinda Kongcharoen & Aekarat Saeliw & Kritsada Puangsuwan & Supattra Puttinaovarat, 2024. "Eco-Friendly Office Platform: Leveraging Machine Learning and GIS for Carbon Footprint Management and Green Space Analysis," Sustainability, MDPI, vol. 16(21), pages 1-20, October.

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