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

Frontiers in Public Health, Год журнала: 2025, Номер 13

Опубликована: Март 6, 2025

Urban green spaces play a critical role in addressing health issues, ecological challenges, and uneven resource distribution cities. This study focuses on Wuhan, where low coverage rates imbalanced space allocation pose significant challenges. Adopting healthy city development perspective, the research aims to assess impact of optimization urban health, economic performance, social structure. A multivariable model was constructed using random forest Support Vector Machine (SVM) algorithms evaluate influence key indicators space. Core were integrated from three dimensions: residents' environmental quality, community interaction. Multiple linear regression analysis employed quantify potential benefits outcomes. The findings reveal that optimizing quality indices significantly enhances development. Green improvements drive 73% increase efficiency by improving extending life expectancy. Additionally, enhancements structure are achieved at 61% 52% through strengthened cohesion improved respectively. demonstrates high stability adaptability after multiple iterations, providing robust quantitative foundation for optimization. highlights multidimensional value promoting growth, stability. results offer solid theoretical basis practical guidance planning management cities, contributing scientific decision-making sustainable

Язык: Английский

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Research on the Impact of Urban Built Environments on PM2.5 Pollution Based on Machine Learning Methods

Atmospheric Pollution Research, Год журнала: 2025, Номер unknown, С. 102503 - 102503

Опубликована: Март 1, 2025

Язык: Английский

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A parametric study of urban ventilation corridors for improving air quality in compact cities

Journal of Cleaner Production, Год журнала: 2025, Номер 500, С. 145219 - 145219

Опубликована: Март 14, 2025

Язык: Английский

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Assessing the contribution of urban green space landscape patterns to ozone concentration variations

Environmental Research, Год журнала: 2025, Номер unknown, С. 121434 - 121434

Опубликована: Март 1, 2025

Язык: Английский

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Impact of Changes in—Blue and Green Spaces on the Spatiotemporal Evolution of the Urban Heat Island Effect in Ningbo and Its Implications for Sustainable Development

Sustainability, Год журнала: 2025, Номер 17(9), С. 4156 - 4156

Опубликована: Май 4, 2025

Blue and green spaces (BGS) play a crucial role in mitigating the urban heat island (UHI) effect by not only lowering land surface temperature (LST) but also regulating microclimate enhancing ecosystem services. In this study, Ningbo City is selected as research area. LST data for years 2014, 2017, 2020, 2023 were retrieved using Landsat 8 imagery processed via Google Earth Engine platform, employing an atmospheric correction approach. Simultaneously, use types classified random forest algorithm. Based on these datasets, Geographically Temporally Weighted Regression model was employed to quantitatively assess spatial temporal impacts of BGS changes UHI effect. The results reveal that (1) from 2014 2023, exhibited consistent decline, while construction expanded significantly, leading gradual increase annual average LST; (2) strong zones primarily concentrated urbanized closely aligned with regions elevated minimum, maximum, values blue significantly lower than those observed cultivated land; (3) variation influence coefficient space greater space, suggesting stronger spatiotemporal heterogeneity its regulatory thermal environment. Additionally, green-to-blue area ratio increased 9.7:1 12.8:1 deviating progressively optimal ecological balance. To promote sustainable development, it imperative strengthen conservation restoration BGS, optimize their configuration through evidence-based planning, ensure long-term stability functions.

Язык: Английский

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Spatiotemporal Analysis of Air Pollution and Climate Change Effects on Urban Green Spaces in Bucharest Metropolis

Atmosphere, Год журнала: 2025, Номер 16(5), С. 553 - 553

Опубликована: Май 7, 2025

Being an essential issue in global climate warming, the response of urban green spaces to air pollution and variability because rapid urbanization has become increasing concern at both local levels. This study explored vegetation Bucharest metropolis Romania from a spatiotemporal perspective during 2000–2024, with focus on 2020–2024 period. Through synergy time series situ data, derived biophysical variables MODIS Terra/Aqua satellite this applied statistical regression, correlation, linear trend analysis assess relationships between their pairwise associations. Green were measured normalized difference index (NDVI), leaf area (LAI), photosynthetically active radiation (FPAR), evapotranspiration (ET), net primary production (NPP), which capture complex characteristics systems (gardens, street trees, parks, forests), periurban forests, agricultural areas. For center (6.5 km × 6.5 km) metropolitan (40.5 40.5 test areas, five-year investigated period, found negative correlations NDVI ground-level concentrations particulate matter two size fractions, PM2.5 (city r = −0.29; p < 0.01, −0.39; 0.01) PM10 −0.58; −0.56; 0.01), as well gaseous pollutants (nitrogen dioxide—NO2, sulfur dioxide—SO2, carbon monoxide—CO. Also, parameters, relative humidity (RH), land surface albedo (LSA) observed. These results show potential improve quality through pollutant deposition, retention, alteration health, particularly dry seasons hot summers. same period analysis, positive solar irradiance (SI) planetary boundary layer height (PBL) recorded. Because summer season’s (June–August) increase ozone, significant (r −0.51, for city −76; area, may explain degraded or devitalized under high ozone research reported temperature 2 m (TA) −0.84; scale −0.90; (LST) p< −0.68, 0.01). During seasons, ET parameters TA 0.91; SI RH 0.65; 0.83; are associated cooling effects vegetation, showing that higher density is lower temperatures. The correlation LST −0.92; explains imprint diurnal variations contrast TA. decreasing NPP over 24 years highlighted feedback warming. future cities, contribute development advanced strategies protection better mitigation increased frequency extreme events.

Язык: Английский

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Daily mobility, greenspace exposure and affective states: A systematic review of studies that use mobile methods

Landscape and Urban Planning, Год журнала: 2025, Номер 262, С. 105407 - 105407

Опубликована: Май 23, 2025

Язык: Английский

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Assessing Supply and Demand Discrepancies of Urban Green Space in High-Density Built-Up Areas Based on Vitality Impacts: Evidence from Beijing’s Central Districts, China

Sustainability, Год журнала: 2025, Номер 17(11), С. 4828 - 4828

Опубликована: Май 23, 2025

In rapidly urbanizing areas, there is a notable aggregation of vitality in high-density urban environments, accompanied by an increasing discrepancy between the supply and demand green space (UGS). This study presented integrated framework comprising model for UGS supply-demand coupling coordination measure vitality. Using downtown Beijing as case study, Gini coefficient assessed disparities across different types. The examined how factors interact with vitality, revealing impact imbalances on various dimensions mismatches experienced groups. showed that: (1) 63.29% central Beijing’s areas had low coordination, 39.23% experiencing mismatches; (2) were significantly correlated spatial distribution; (3) these impacted comprehensive vitality; (4) distribution among groups, economic group perceiving greatest inequity (Gini = 0.311), followed social 0.289) cultural 0.247). These findings offer valuable insights more refined assessment enhancement UGS, aiming to achieve balanced, high-quality, sustainable development.

Язык: Английский

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Urban Climate Dynamics: Analyzing the Impact of Green Cover and Air Pollution on Land Surface Temperature—A Comparative Study Across Chicago, San Francisco, and Phoenix, USA

Atmosphere, Год журнала: 2024, Номер 15(8), С. 917 - 917

Опубликована: Июль 31, 2024

Rapid urbanization worldwide has significantly altered urban climates, creating a need to balance growth with thermal environmental quality for sustainable development. This study examines the relationship between land surface temperature (LST) and characteristics, particularly focusing on how green cover can mitigate heat air pollution increase temperatures. Recognizing predictive value of LST island (UHI) intensity, we analyzed three distinct U.S. cities—Chicago, San Francisco, Phoenix—each characterized by unique climate planning features. investigates atmospheric pollutants (SO2, NO2, CO, O3) Normalized Difference Vegetation Index (NDVI) using regression correlation analyses. The analysis aims elucidate changes in NDVI affect variations temperature. Regression is employed estimate coefficients independent variables quantify their impact LST. Correlation assesses linear relationships variables, providing insights into pairwise associations. also multicollinearity identify potential confounding factors. results reveal significant associations pollutants, NDVI, temperature, contributing our understanding factors influencing dynamics informing change mitigation strategies. observed inconsistencies correlations across cities highlight importance local context studies. Understanding these aid developing tailored policies that consider city characteristics more effective resilience. Furthermore, positive association was consistently obtained LST, indicating increased levels contribute higher temperatures different settings.

Язык: Английский

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Characterization of Spatial and Temporal Variations in Air Pollutants and Identification of Health Risks in Xi’an, a Heavily Polluted City in China

Atmosphere, Год журнала: 2024, Номер 15(6), С. 716 - 716

Опубликована: Июнь 14, 2024

The study of the temporal and spatial characteristics air pollutants in heavily polluted cities is extremely important for analyzing causes pollution achieving a viable means control. Such case Xi’an, typical city Fenwei Plain, China, have remained unclear due to limitations data accuracy research methods. monthly, daily, hourly patterns O3 particulate matter (PM2.5 PM10) are analyzed this using on-site provided by an urban quality monitoring network. analysis variance (ANOVA) method was used compare differences pollutant concentrations during different seasons time periods. distributions O3, PM2.5, PM10 at points following interpolation sites been analyzed. results show that concentration from 12 p.m. 3 significantly higher than morning evening, PM2.5 7 10 were those afternoon. number qualified days less 30 unqualified more 100 2019. There potential risk exposure with associated health risks. Even on same day, can differ significantly. This provides scientific basis reducing exposure. Outdoor activities summer beneficial reduce exposure, outdoor should be curtailed evening winter government formulate public policies activities.

Язык: Английский

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