@article{HU2025128939,
title = {Comparative analysis of greenery inequalities in New York and London: Social-economic and spatial dimensions},
journal = {Urban Forestry & Urban Greening},
volume = {112},
pages = {128939},
year = {2025},
issn = {1618-8667},
doi = {https://doi.org/10.1016/j.ufug.2025.128939},
url = {https://www.sciencedirect.com/science/article/pii/S1618866725002730},
author = {Yequan HU and Mingze CHEN and Yuxuan CAI},
keywords = {Big data, Urban green space (UGS), Green equity, Spatial heterogeneity, Multiscale Geographically Weighted Regression (MGWR)},
abstract = {With the rapid development of urbanization, the reduction of urban green spaces (UGS) has negatively impacted residents' quality of life and environmental quality. Recognizing that factors influencing environmental justice vary across different national and city contexts, this study aims to explore these differential impacts. However, most existing studies focus on single cities or specific regions, with limited comparative research between different countries. To explore the factors that differentially affect UGS in various cities, this study compares the distribution of UGS in New York City, U.S., and London, UK, investigating socio-economic variables (percentage of population in poverty, housing-cost burden, education level), demographic factors (proportion of minorities, elderly, individuals with disabilities), and built-environment indicators (residential density, road density, land-use types). These variables are measured using official census data and spatial datasets from each city, ensuring robust coverage of community vulnerability and development intensity. The research employs Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR), and Multiscale Geographically Weighted Regression (MGWR) methods to analyze the relationship between UGS. The OLS results indicate that in both New York and London, minority and elderly populations have a positive correlation with UGS usage, while low-income groups face greater inequalities. GWR and MGWR reveal that UGS inequalities are mainly concentrated in urban peripheries or economically weaker areas. Notably, New York is more affected by economic factors, showing significant spatial heterogeneity in economically underdeveloped areas. These findings are significant for developing more equitable and effective UGS policies. Such methods enable systematic evaluations across different countries based on case studies from major cities, breaking down regional isolation and fostering more equitable and effective UGS policies globally. Understanding these differences can lead to more targeted interventions, improve the quality of life for vulnerable groups, and promote sustainable urban development worldwide.}
}