Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city

This study highlights the multidimensional value of green space optimization in promoting urban health, economic growth, and social stability. The results offer a solid theoretical basis and practical guidance for green space planning and management in healthy cities, contributing to scientific decision-making and sustainable urban development.

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Publication Details

Journal
Frontiers in Public Health
Published
2025-03-06
DOI
https://doi.org/10.3389/fpubh.2025.1490857
Citations
2
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
2.40
Controls
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article

Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city

Xiaofei Zou, Wenzuixiong Xiong, Xuechun Zhou
2 citations
Frontiers in Public Health
Urban Green Space and Health
2.40
article

Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city

Xiaofei Zou, Wenzuixiong Xiong, Xuechun Zhou
article en
2 citations

Abstract

This study highlights the multidimensional value of green space optimization in promoting urban health, economic growth, and social stability. The results offer a solid theoretical basis and practical guidance for green space planning and management in healthy cities, contributing to scientific decision-making and sustainable urban development.

Frontiers in Public HealthVol. 13
Hubei University (CN), University of Glasgow (GB)
Openalex Percentile: Top 14%
Urban Green Space and Health
2.40
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