Equity in Green Space Planning and Management

As cities densify to meet environmental and economic goals, the equitable distribution of urban green spaces (UGS) becomes critical for fostering community well-being, promoting environmental justice, and enhancing climate resilience. This report presents a synthesis study conducted by the Swedish University of Agricultural Sciences (SLU) in collaboration with Nilsson Landscape, aimed at understanding the relationship between socio-economy and accessibility to UGS, to assess and enhance green equity in urban environments. The research focuses on Malmö specifically, and have involved Region Skåne as a proxy for other municipalities in southern Sweden, leveraging data on green space access, canopy cover, socio-economic indicators, and maintenance costs.The primary objective of this study was to establish a data-driven, replicable framework that quantifies green space equity at the city district level. Specifically, the research seeks to (i) identify key indicators of green space availability and socio-economic status that can be measured consistently across Swedish municipalities; (ii) develop a composite relationship (a matrix or an index) that integrates these indicators to provide actionable insights for urban planners and policymakers, and (iii) to test the applicability of this index in Malmö, illustrating its potential to guide future investments in UGS for equitable urban development. The research integrates three complementary initiatives:i. KSLA Project: A synthesis of socio-economic and green space factors relevant to equity in urban environments. ii. FoMA Project: Development and testing of green space indicators, including canopy cover, urban green space per capita, and distance to the nearest green space, in relation to socio-economic metrics like income, education, and employment. iii. Movium Partnership: Evaluation of the Green Equity Matrix, a tool that categorizes neighborhoods based on their socio-economic status (SES) and green space status (GSS), and explores policy implications and maintenance costs.The ambition to develop a matrix or an index aligns with international models such as the Tree Equity Score and Spatial Equity NYC but adapts them to the Swedish context, where socioeconomic factors and access to UGS are measured differently. Data sources include GIS-based analyses, municipal records, and socio-economic data from Statistics Sweden. All computations of UGS rely on open datasets, which are updated at varying frequencies but not always regularly. All the SES data is easily accessible and reliable, and available at DeSO level.A Green Equity Matrix was developed, including seven indicators ‘UGS per capita’, ‘canopy cover’, ‘distance to UGS’ as Green Space Status (GSS) indicators, and ‘age dependency’, ‘income’, ‘education level’, and ‘employment rate’, as Socio-Economic Status (SES) indicators. Each indicator was computed and combined into two individual indexes. All indicators are combined unweighted, meaning they are treated equally when combined.Contrary to widespread assumptions, our analysis reveals that neighbourhoods with lower SES often have higher GSS in Malmö. Lower SES neighbourhoods in Malmö were often developed around the 1960’es and early 1970’es (the Million Program), where larger parks and green spaces were prioritized. As such, we believe these areas have benefited from earlier planning efforts aimed at providing green amenities to balance socio-economic disadvantages, and that the effects of these efforts are still notable in a Swedish context like in Malmö. However, while higher GSS in lower SES areas is a positive finding, it does not necessarily reflect equitable quality or functionality of Summary green spaces. Socio-economic disparities might still influence the usability, safety, and maintenance of these green areas, affecting their actual benefits to residents.We calculated maintenance cost in DeSOs characterized by both low GSS and low SES. Here, costs range from 24 to 335 SEK per capita, with an average in Malmö being 448 SEK per capita. Even though we indicate a relationship between low SES and low maintenance cost, we recognise the need for better data, including a calculation based on actual use, rather than cost per capita. However, such data is not available today.The actual quality of UGS should be further explored and considered incorporated into or related to the matrix. This will ensure that green space interventions align with the needs and preferences of residents. In line with this, local governments’ capacities to develop such indices should be explored too. However, the use of accessible data in combination with relatively simple GIS-based socio-ecological analysis has been prioritised for this project. Thus, our proposed method does not require advanced GIS skills, making it accessible for all municipalities.The suggested method ranks neighbourhoods within a municipality or urban area, meaning the GSS and SES results cannot be directly compared across different municipalities or urban areas. However, metrics such as the percentage of neighbourhoods within each quadrant or within a certain standard deviation can still be used for comparisons with other municipalities or urban areas.Our new and nuanced understanding of the relationship between SES and GSS challenges the conventional narrative that socio-economically disadvantaged neighbourhoods lack access to green spaces. Instead, it highlights the need for context-specific urban planning and management that recognizes both the strengths and challenges of different neighbourhoods.