Sustainable Mitigation Strategies for Urban Heat Island Effects in Urban Areas

Sustainability, Год журнала: 2023, Номер 15(14), С. 10767 - 10767

Опубликована: Июль 9, 2023

The globe is at a crossroads in terms of the urban heat island effect, with rising surface temperatures due to urbanization and an expanding built environment. This cause-and-effect connection may be linked weather-related dangers, natural disasters, disease outbreaks. Urbanization industrialization will not lead secure sustainable future. Finding solutions problems such as effect forefront scientific research policy development. Sustainable ways decrease impacts are core principle for planners. literature study examines benefits adding green infrastructure materials built-up areas reduce effect. Materials reflective street pavements, coating including light-colored paint, phase-change materials, color-changing fluorescence energy-efficient appliances considered whereas like roofs, walls, parking shaded streets mitigate hurdles widespread adoption practices include lack governmental legislation, insufficient technological development, erroneous estimation economic gains, unwillingness on part impacted parties.

Язык: Английский

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Evaluating the association between morphological characteristics of urban land and pluvial floods using machine learning methods

Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104891 - 104891

Опубликована: Авг. 22, 2023

Язык: Английский

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Optimizing the spatial pattern of the cold island to mitigate the urban heat island effect

Ecological Indicators, Год журнала: 2023, Номер 154, С. 110550 - 110550

Опубликована: Июнь 27, 2023

Numerous studies on reducing the urban heat island effect have concentrated isolated cold islands, analyzing their cooling impact in terms of size and shape. From an international perspective, shown that enhancing connectivity islands can enhance but they do not suggest specific processes ideas for connectivity. This study aims to investigate how connect optimize spatial pattern island. Therefore, a framework is constructed this study: source area - network. Firstly, core was identified by morphological analysis. Then, analysis applied identify sources. Afterward, minimum cumulative resistance model used construct In Nanjing, case point, results reveal total 27 areas 52 corridors been identified. 6 first-level CSAs situated northern suburbs Nanjing prevent spread effect. 2 second-level 18 third-level are scattered throughout improve climate. The 29 primary help mitigate transfer from city center. 23 secondary mainly located centers contributing preventing aggregating. be as strategic measure fragmentation isolation island, which provides implications further expansion

Язык: Английский

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Comparative Analysis of the Seasonal Driving Factors of the Urban Heat Environment Using Machine Learning: Evidence from the Wuhan Urban Agglomeration, China, 2020

Atmosphere, Год журнала: 2024, Номер 15(6), С. 671 - 671

Опубликована: Май 31, 2024

With the ongoing advancement of globalization significantly impacting ecological environment, continuous rise in Land Surface Temperature (LST) is increasingly jeopardizing human production and living conditions. This study aims to investigate seasonal variations LST its driving factors using mathematical models. Taking Wuhan Urban Agglomeration (WHUA) as a case study, it explores characteristics employs Principal Component Analysis (PCA) categorize factors. Additionally, compares traditional models with machine-learning select optimal model for this investigation. The main conclusions are follows. (1) WHUA’s exhibits significant differences among seasons demonstrates distinct spatial-clustering different seasons. (2) Compared geographic spatial models, Extreme Gradient Boosting (XGBoost) shows better explanatory power investigating effects LST. (3) Human Activity (HA) dominates influence throughout year positive correlation LST; Physical Geography (PG) negative Climate Weather (CW) show similar variation PG, peaking transition; Landscape Pattern (LP) weak LST, winter while being relatively inconspicuous summer transition. Finally, through comparative analysis multiple constructs framework exploring features aiming provide references guidance development WHUA regions.

Язык: Английский

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Exploring the scale effect of urban thermal environment through XGBoost model

Sustainable Cities and Society, Год журнала: 2024, Номер 114, С. 105763 - 105763

Опубликована: Авг. 23, 2024

Язык: Английский

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Seasonal surface urban heat island analysis based on local climate zones

Ecological Indicators, Год журнала: 2024, Номер 159, С. 111669 - 111669

Опубликована: Фев. 1, 2024

A fundamental aspect of ensuring urban sustainability is a comprehensive understanding the driving mechanisms behind heat island (UHI) phenomenon. The primary objective this study to investigate spatiotemporal variations and underlying surface (SUHI) in Hefei. employed local climate zone (LCZ) method analyze land morphology spatial structure for 2014 2021. Subsequently, calculations were conducted derive intensity (SUHII), normalized difference built-up index (NDBI), vegetation (NDVI), gravity water (GWI), building fraction (BSF), road density (RD), poi (PD), population (PPD). exploration by which factors influence SUHI was utilizing both Pearson correlation analysis geographic detector models. results revealed that sparsely built (LCZ 9) low plants D) predominantly characterized natural coverage areas, respectively. summer season distinguished most extensive distribution highest SUHII levels. Significantly, consistently exceeded those LCZs when contrasted LCZs. Large lowrise 8) displayed levels, whereas G) exhibited lowest values. NDBI took precedence showed positive with SUHI. Among socio-economic factors, height (BH) demonstrated superior explanatory capability compared other variables. interaction between NDVI maximized explanation under different seasons. findings will serve as critical insights planners policymakers, enabling development scientifically-based efficacious strategies mitigate

Язык: Английский

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Revealing Multiscale and Nonlinear Effects of Urban Green Spaces on Heat Islands in High-Density Cities: Insights from MSPA and Machine Learning

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106173 - 106173

Опубликована: Янв. 1, 2025

Язык: Английский

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Spatially-optimized greenspace for more effective urban heat mitigation: Insights from regional cooling heterogeneity via explainable machine learning

Landscape and Urban Planning, Год журнала: 2025, Номер 256, С. 105296 - 105296

Опубликована: Янв. 16, 2025

Язык: Английский

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Blue-Green space seasonal influence on land surface temperatures across different urban functional zones: Integrating Random Forest and geographically weighted regression

Journal of Environmental Management, Год журнала: 2025, Номер 374, С. 123975 - 123975

Опубликована: Янв. 16, 2025

Язык: Английский

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How does Blue-Green Infrastructure affect the urban thermal environment across various functional zones?

Urban forestry & urban greening, Год журнала: 2025, Номер unknown, С. 128698 - 128698

Опубликована: Янв. 1, 2025

Язык: Английский

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