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Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis

Park green space (PGS) provides numerous environmental and health benefits for urban residents, and raises the issue of green justice for its uneven distribution in cities. Previous studies focus more on the measurements of spatial equity in accessibility, but are limited in exploring its impacts—es...

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Autores principales: Du, Sainan, He, Huagui, Liu, Yanfang, Xing, Lijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407995/
https://www.ncbi.nlm.nih.gov/pubmed/36011991
http://dx.doi.org/10.3390/ijerph191610357
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author Du, Sainan
He, Huagui
Liu, Yanfang
Xing, Lijun
author_facet Du, Sainan
He, Huagui
Liu, Yanfang
Xing, Lijun
author_sort Du, Sainan
collection PubMed
description Park green space (PGS) provides numerous environmental and health benefits for urban residents, and raises the issue of green justice for its uneven distribution in cities. Previous studies focus more on the measurements of spatial equity in accessibility, but are limited in exploring its impacts—especially the nonlinear influence. This study first measures accessibility and equity in two traffic modes, and then explores the nonlinear influence of multidimensional factors by using the gradient boosting decision tree (GBDT) model across the central urban area of Wuhan. The results show significant spatial disparities in spatial accessibility and equity by walking and driving within 15 min. Multidimensional factors—including characteristics of PGS, the built environment, and socioeconomic factors—present stronger nonlinear influences on spatial accessibility and equity, and the nonlinear influence indicates that the contributions of the built environment and socioeconomic factors are greater than those of park characteristics, accounting for at least 79.76%. The key variables affecting the accessibility and equity are not completely consistent, leading to synergistic and heterogeneous effects, which may provide policy implications for streets where accessibility and equity are mismatched. These findings could provide guidance for PGS planning by decision-makers to improve the living environment and urban health.
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spelling pubmed-94079952022-08-26 Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis Du, Sainan He, Huagui Liu, Yanfang Xing, Lijun Int J Environ Res Public Health Article Park green space (PGS) provides numerous environmental and health benefits for urban residents, and raises the issue of green justice for its uneven distribution in cities. Previous studies focus more on the measurements of spatial equity in accessibility, but are limited in exploring its impacts—especially the nonlinear influence. This study first measures accessibility and equity in two traffic modes, and then explores the nonlinear influence of multidimensional factors by using the gradient boosting decision tree (GBDT) model across the central urban area of Wuhan. The results show significant spatial disparities in spatial accessibility and equity by walking and driving within 15 min. Multidimensional factors—including characteristics of PGS, the built environment, and socioeconomic factors—present stronger nonlinear influences on spatial accessibility and equity, and the nonlinear influence indicates that the contributions of the built environment and socioeconomic factors are greater than those of park characteristics, accounting for at least 79.76%. The key variables affecting the accessibility and equity are not completely consistent, leading to synergistic and heterogeneous effects, which may provide policy implications for streets where accessibility and equity are mismatched. These findings could provide guidance for PGS planning by decision-makers to improve the living environment and urban health. MDPI 2022-08-19 /pmc/articles/PMC9407995/ /pubmed/36011991 http://dx.doi.org/10.3390/ijerph191610357 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Du, Sainan
He, Huagui
Liu, Yanfang
Xing, Lijun
Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title_full Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title_fullStr Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title_full_unstemmed Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title_short Identifying Key Factors Associated with Green Justice in Accessibility: A Gradient Boosting Decision Tree Analysis
title_sort identifying key factors associated with green justice in accessibility: a gradient boosting decision tree analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407995/
https://www.ncbi.nlm.nih.gov/pubmed/36011991
http://dx.doi.org/10.3390/ijerph191610357
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