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Inequalities in the quality and proximity of green space exposure are more pronounced than in quantity aspect: Evidence from a rapidly urbanizing Chinese city
Affiliation:The College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
Abstract:
Substantial studies have revealed that exposure to green spaces (GSs) yields a variety of health benefits. However, daily GS exposure scenarios are multidimensional, and relevant analyses require a comprehensive framework that assesses GS exposure from overhead- to eye-level perspectives, focusing on GS attributes from quantity and proximity to quality. Moreover, GSs are often unevenly distributed across cities, resulting in green distribution injustice. To this end, this study aimed to systematically evaluate multiple GS exposures considering two-dimensional (2D) spatial exposures (i.e., quantity-based availability, distance-based accessibility, and quality-based attractiveness) and three-dimensional (3D) visual exposures (quantity-based street GS visibility and quality-based street GS perceivability). It then examined the inequalities in GS exposure among socioeconomically disadvantaged groups. Housing prices were employed as proxies for socioeconomic status. Local indicators of spatial association(LISA) were employed to examine the existence of bivariate statistically significant spatial clusters of housing prices and multiple GS exposure. Furthermore, the spatial lag regression model was used to determine inequities in GS exposure among urban residents living in communities with different housing prices. The Nanjing metropolitan area, one of the most densely populated cities in China, was selected as the study case. Residential exposure to GS was comprehensively assessed using a 15-min walkable zone lens. The results suggest that: 1) the spatial cluster of ‘low GS exposure – low housing price’ occupied the largest proportion; 2) all five types of GS exposure were positively associated with housing prices, indicating that the affluent groups are more likely to have access to various GSs; and 3) GS exposure inequalities are more pronounced in measurements of quality(and proximity) than quantity in both spatial and visual exposure metrics. These findings can inform the development of environmental planning and policy strategies for more effective, efficient, and equitable GS provisions that address health issues and green injustice in rapidly urbanizing cities.
Keywords:Green infrastructure  Environmental injustice  Urban planning  Housing  Big Data  Machine Learning
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