Analysing urban green space accessibility and quality: A GIS-based model as spatial decision support for urban ecosystem services in Brussels

• Published in: Ecosystem services 2017-12, Vol.28, p.328-340
• Main Authors: Stessens, Philip, Khan, Ahmed Z., Huysmans, Marijke, Canters, Frank
• Format: Article
• Language: English
• Subjects: Cultural ecosystem services; Environmental quality; GIS; Proximity analysis; Spatial decision support; Urban green space
• ISSN: 2212-0416; 2212-0416
• DOI: 10.1016/j.ecoser.2017.10.016

•A GIS model is proposed for mapping green space proximity at the level of urban blocks.•Proximity and green space quality are combined into a single indicator.•An analysis is conducted for the Brussels Capital Region and its surroundings.•Areas with high and low scores in terms of green space provision are mapped.•Design and policy options can be simulated for green spaces’ quality and proximity. With the majority of people living in cities, urban green spaces are the primary source of contact with nature. Access to ecosystem services provided by urban green spaces is increasingly perceived as an important factor for quality of life, and it is a key component of sustainable urban design and planning. This paper presents a novel GIS-based tool to evaluate accessibility to – and quality of – urban green spaces. To demonstrate the tool’s applicability, it was implemented in Brussels. A series of indicators to evaluate the proximity to and quality of green spaces is proposed in the light of the analysis with the aim of supporting decision making and planning at the urban scale. The proximity and quality sub-models were parameterised through a comparative study of planning standards and through analysis of local preferences, acquired by means of a questionnaire. Applying the model to Brussels showed that approximately equally sized population groups have low, medium, and high access to green spaces. Concerning the proposed method for measuring green space quality, 62% of the population resides in urban blocks with access to green spaces with a lower than average quality score, which reveals a significant margin for improvement.