Multi-criteria spatial assessment of urban open spaces for promoting physical activity and spatial justice: a case study of Tehran metropolitan

Urban open spaces play a crucial role in enhancing citizens' quality of life and health, making the assessment of their quality essential for urban planning. This study aims to propose a framework for evaluating the spatial distribution of urban open space quality for physical activity based on a multi-criteria spatial approach. Tehran Metropolitan was selected as the case study area. Spatial data, including satellite imagery, digital elevation models, demographic information, urban infrastructure, and land use data, were collected for this purpose. The study generated maps of various effective spatial criteria, including ten environmental criteria and ten accessibility and infrastructure criteria. After normalizing the criteria using the min-max method, criterion weights were calculated using a hybrid approach combining the subjective best-worst method (BWM) and the objective criteria importance though intercriteria correlation method (CRITIC) method to enhance the accuracy and consistency of the weights. The weighted linear combination (WLC) model was used to integrate the spatial layers. For spatial analysis, Hot Spot Analysis (Getis-Ord Gi*) and Local Moran's I methods were employed to identify clusters of high desirability and analyze spatial patterns. To examine spatial justice and inequality in the distribution of desirable open spaces relative to population, the Lorenz curve was plotted, and the Gini coefficient was calculated. Results indicated that environmental criteria, with a total weight of 0.6, and accessibility and infrastructure criteria, with a weight of 0.4, play a fundamental role in determining the quality of open spaces. Sub-criteria such as NDVI and air pollution in the environmental category and proximity to public transport stations and sports facilities in the accessibility and infrastructure category were the most influential. Regarding environmental quality, the majority of the city falls within medium and low classes, with less than one-third of the urban area possessing favorable environmental conditions, mainly concentrated in the northern, some western, and eastern parts of the city. In contrast, access to infrastructure and urban services is significantly better, with more than half of the city's area falling within high and very high classes, reflecting the widespread distribution of transport and service infrastructure across the city. Spatial analysis using Hot Spot and Local Moran's I indices revealed that hot spot clusters, covering approximately 21% of the city, are mainly concentrated in the northern half, while cold spot clusters, covering 27% of the city, are mostly located in the southern and central parts, indicating substantial spatial inequality. Furthermore, the Gini coefficient of 0.6035 and the Lorenz curve confirm that the distribution of desirable open spaces is highly uneven relative to the population, with around 60% of the population having access to only 10% of these spaces. The study suggests that policymakers design targeted and balanced interventions in areas with unfavorable conditions and limited open spaces to reduce spatial inequalities and improve citizens' quality of life.