Urban green space (UGS) provides wide-ranging ecological, health, and social benefits, but its widespread inequitable distribution has become a critical environmental justice issue. As China undergoes the world’s largest and fastest-paced urbanization and population aging, its unique policy practices like the “park city” model and its leading access to multi-source big data create a natural laboratory for an in-depth study of green equity. Research on China can not only meet domestic governance needs but also provide valuable insights for the global theory of environmental justice. The theory of green equity originated from struggles against the disproportionate distribution of environmental hazards, such as pollution, among vulnerable groups, and later expanded to include the unequal allocation of environmental benefits, like parks. The assessment of green equity requires a comprehensive, multidimensional, and multi-scalar analytical framework. This framework integrates three core dimensions: distributive justice (the fairness of resource spatial layout), procedural justice (the inclusivity of decision-making processes), and interactional justice (the equality of user experience). At the same time, research must span the “nation–city–individual” scales, as the manifestations, drivers, and metrics of inequity are significantly scale-dependent. From macro-level patterns at the national scale to community configurations within cities, and down to the true dynamic exposure of individuals beyond their static residences (including workplaces and commutes), each scale reveals different facets of the problem. China’s current policy and governance systems are significant institutional root causes of green inequity. The statutory framework focuses on “equality” (e.g., per capita area) rather than “equity”; in administration, ineffective vertical policy transmission and horizontal inter-departmental fragmentation create governance gaps; and in planning and implementation, limited channels for public participation, fiscal biases, and a lack of accountability systematically undermine green equity. To address these challenges, this book constructs a multi-scalar analytical framework that integrates multi-source big data from remote sensing and street views, along with advanced methods such as GIS, econometrics, and machine learning. Through a policy loop of “diagnosis–prioritization–intervention–evaluation,” this framework aims not only to identify the patterns and hotspots of UGS inequity in China but also to reveal the complex mechanisms behind them. Ultimately, it seeks to propose institutional reforms and planning pathways that are both internationally comparable and locally adapted to achieve a “just green city.”

Overview of Research Progress on Urban Green Space Equity

章节
发表日期：

2026年

查看全文

Jiayu Wu

摘要

Urban green space (UGS) provides wide-ranging ecological, health, and social benefits, but its widespread inequitable distribution has become a critical environmental justice issue. As China undergoes the world’s largest and fastest-paced urbanization and population aging, its unique policy practices like the “park city” model and its leading access to multi-source big data create a natural laboratory for an in-depth study of green equity. Research on China can not only meet domestic governance needs but also provide valuable insights for the global theory of environmental justice. The theory of green equity originated from struggles against the disproportionate distribution of environmental hazards, such as pollution, among vulnerable groups, and later expanded to include the unequal allocation of environmental benefits, like parks. The assessment of green equity requires a comprehensive, multidimensional, and multi-scalar analytical framework. This framework integrates three core dimensions: distributive justice (the fairness of resource spatial layout), procedural justice (the inclusivity of decision-making processes), and interactional justice (the equality of user experience). At the same time, research must span the “nation–city–individual” scales, as the manifestations, drivers, and metrics of inequity are significantly scale-dependent. From macro-level patterns at the national scale to community configurations within cities, and down to the true dynamic exposure of individuals beyond their static residences (including workplaces and commutes), each scale reveals different facets of the problem. China’s current policy and governance systems are significant institutional root causes of green inequity. The statutory framework focuses on “equality” (e.g., per capita area) rather than “equity”; in administration, ineffective vertical policy transmission and horizontal inter-departmental fragmentation create governance gaps; and in planning and implementation, limited channels for public participation, fiscal biases, and a lack of accountability systematically undermine green equity. To address these challenges, this book constructs a multi-scalar analytical framework that integrates multi-source big data from remote sensing and street views, along with advanced methods such as GIS, econometrics, and machine learning. Through a policy loop of “diagnosis–prioritization–intervention–evaluation,” this framework aims not only to identify the patterns and hotspots of UGS inequity in China but also to reveal the complex mechanisms behind them. Ultimately, it seeks to propose institutional reforms and planning pathways that are both internationally comparable and locally adapted to achieve a “just green city.”