A Temporal-Spatial Framework for Urban Green Space Equity Evaluation

Thesis Abstract

Urban green space (UGS) equity remains uneven across metropolitan areas, with access disparities linked to socioeconomic status, land use patterns, and evolving urban forms. This study develops a temporal-spatial framework to evaluate UGS equity by integrating time-dynamic and spatial-structural dimensions of accessibility, exposure, and utilization. The aim is to quantify how UGS distribution and access evolve across neighborhoods over a five-year period and to identify policy levers that promote equitable provision. Specific objectives are (i) to characterize spatiotemporal patterns of UGS quantity, quality, and accessibility using high-resolution land cover and facility data; (ii) to examine the relationship between neighborhood sociodemographic profiles and UGS accessibility changes through panel regression; (iii) to assess exposure and actual use of UGS via remote sensing-derived green space indices and household survey data; (iv) to test a temporal-spatial equity model integrating Moran’s I, Geographically Weighted Regression (GWR), and a dynamic accessibility framework; and (v) to propose a policy-analytic toolkit for targeting investments and monitoring equity outcomes. The methodology adopts a mixed-methods research design with a longitudinal, multi-city case study approach. The population includes residents of five mid-to-large European cities with contrasting urban morphologies and green space planning histories. A stratified random sample of 2,000 households per city (total N = 10,000) is surveyed to capture measures of perceived accessibility, use, and satisfaction, complemented by municipal inventories of UGS facilities, park service quality ratings, and demographic indicators from census data. Data collection instruments comprise a standardized household survey (n = 2,000 per city), city-level UGS inventories, and remotely sensed vegetation indices (NDVI) derived from 10-m Sentinel-2 imagery across the five-year window. Validity and reliability are established through pretesting (n = 200), pilot-reliability checks (Cronbach’s alpha > 0.85 for scale items), and triangulation with field observations and expert content review. Analytical techniques include (i) descriptive temporal-spatial mapping of UGS per capita, park area and service radius, and NDVI-derived green density; (ii) time-series analysis to detect trend shifts in access metrics; (iii) panel data regression to identify determinants of access changes, controlling for neighborhood fixed effects and city-specific policies; (iv) Geographically Weighted Regression (GWR) to capture spatially varying relationships between sociodemographic factors and UGS access; (v) a dynamic accessibility model that integrates travel-time potential, opening hours, and utilization rates to generate time-aware equity scores; and (vi) a structural equation model (SEM) to link equity proxies with well-being outcomes. The study also employs a policy simulation module to evaluate alternative allocation scenarios, guided by principles from urban political ecology and ecosystem services theory. Expected findings indicate persistent inequities in UGS access, with stronger improvements in high-income neighborhoods and central districts, but heterogeneous gains in peripheral areas. The temporal-spatial framework is anticipated to reveal six distinct equity trajectories across cities, driven by land use changes, transportation accessibility, and governance investments. GWR is expected to uncover non-stationary associations between deprivation indicators and access, necessitating localized policy responses. The study will demonstrate that incorporating time, travel behavior, and park quality yields more accurate assessments of equity than static measures alone, aligning with theories of environmental justice, accessibility theory, and urban regime theory. The contribution to knowledge lies in the development of a replicable temporal-spatial framework for assessing UGS equity that integrates time-variant accessibility, quality, and use across urban scales, offering a robust methodological suite for researchers and practitioners. The study provides empirically grounded, city-specific policy recommendations, including prioritization of investments in underserved neighborhoods, dynamic scheduling of park services, improved connectivity to green networks, and participatory governance mechanisms to sustain equitable green space provision. The main conclusion posits that equitable UGS outcomes require monitoring frameworks that simultaneously address temporal dynamics, spatial heterogeneity, and service quality, rather than static proximity alone, and recommends embedding the framework within urban planning dashboards to support adaptive, equity-oriented decision-making.