TY - JOUR
T1 - Accessible Green Spaces? Spatial Disparities in Residential Green Space among People with Disabilities in the United States
AU - Wong, Sandy
AU - Rush, Johnathan
AU - Bailey, Franklin
AU - Just, Allan C.
N1 - Publisher Copyright:
© 2022 by American Association of Geographers.
PY - 2023
Y1 - 2023
N2 - This article presents new quantitative results on the distribution of residential green space for people with disabilities in the United States, building on and bridging scholarly research in two distinct domains: one involving approaches that quantify disparities in green space access among racialized minorities and socioeconomically disadvantaged groups, and the other using qualitative methods that demonstrate that most green spaces remain inaccessible and unwelcoming to disabled visitors. Using generalized additive models (GAMs) that controlled for demographic factors and climatological characteristics, we find that residential areas with more green space generally have a higher proportion of disabled residents. The statistical results run counter to expectations from the literature, thus complicating the prevailing narrative and indicating a need for mixed-methods research to examine multiple dimensions of access and environmental justice. Using cluster analysis to assess spatial trends, we detect residential clusters of high disability and low green space and find that they are located in predominantly non-White, urban, and more socioeconomically disadvantaged neighborhoods compared to clusters of high disability and high green space. Cluster analysis results suggest that there are inequities in green space access at the intersection of disability, race, and class, as well as across the urban–rural continuum.
AB - This article presents new quantitative results on the distribution of residential green space for people with disabilities in the United States, building on and bridging scholarly research in two distinct domains: one involving approaches that quantify disparities in green space access among racialized minorities and socioeconomically disadvantaged groups, and the other using qualitative methods that demonstrate that most green spaces remain inaccessible and unwelcoming to disabled visitors. Using generalized additive models (GAMs) that controlled for demographic factors and climatological characteristics, we find that residential areas with more green space generally have a higher proportion of disabled residents. The statistical results run counter to expectations from the literature, thus complicating the prevailing narrative and indicating a need for mixed-methods research to examine multiple dimensions of access and environmental justice. Using cluster analysis to assess spatial trends, we detect residential clusters of high disability and low green space and find that they are located in predominantly non-White, urban, and more socioeconomically disadvantaged neighborhoods compared to clusters of high disability and high green space. Cluster analysis results suggest that there are inequities in green space access at the intersection of disability, race, and class, as well as across the urban–rural continuum.
KW - GAMs
KW - cluster analysis
KW - disability
KW - environmental justice
KW - green space access
UR - http://www.scopus.com/inward/record.url?scp=85139194345&partnerID=8YFLogxK
U2 - 10.1080/24694452.2022.2106177
DO - 10.1080/24694452.2022.2106177
M3 - Article
AN - SCOPUS:85139194345
SN - 2469-4452
VL - 113
SP - 527
EP - 548
JO - Annals of the American Association of Geographers
JF - Annals of the American Association of Geographers
IS - 2
ER -