Environmental Research, Год журнала: 2023, Номер 243, С. 117813 - 117813
Опубликована: Дек. 1, 2023
Язык: Английский
Environmental Research, Год журнала: 2023, Номер 243, С. 117813 - 117813
Опубликована: Дек. 1, 2023
Язык: Английский
Sustainable Cities and Society, Год журнала: 2024, Номер 110, С. 105572 - 105572
Опубликована: Июнь 3, 2024
Язык: Английский
Процитировано
50Sustainable Cities and Society, Год журнала: 2024, Номер 114, С. 105763 - 105763
Опубликована: Авг. 23, 2024
Язык: Английский
Процитировано
23Building and Environment, Год журнала: 2025, Номер unknown, С. 112538 - 112538
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
4Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104995 - 104995
Опубликована: Окт. 12, 2023
Язык: Английский
Процитировано
34ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2023, Номер 204, С. 1 - 14
Опубликована: Сен. 5, 2023
Язык: Английский
Процитировано
26Computational Urban Science, Год журнала: 2025, Номер 5(1)
Опубликована: Апрель 8, 2025
Abstract Urban areas globally have become home to over half of the world's population, leading intensification urban heat island (UHI) effect, where cities experience higher temperatures than their rural counterparts. The current study develops a new model predicting UHI intensity for 216 across all climate zones both Global North and South using machine learning techniques, focusing on years 2019 2023. Utilising novel dataset, integrating climate, economic, land use data from worldwide, model, trained Support Vector Regression (SVR), demonstrates mean absolute error (MAE) 0.86 °C. Results reveal that wind speed significantly mitigates intensity, while in temperate climates exhibit more pronounced effects compared those located within tropical climbs. Additionally, results show crucial role coastal proximity reducing find no significant differences between South. Findings offer important empirical actionable insights alongside robust tool planners policymakers measure, map, monitor contributing development liveable sustainable environments.
Язык: Английский
Процитировано
1The Science of The Total Environment, Год журнала: 2023, Номер 911, С. 168494 - 168494
Опубликована: Ноя. 18, 2023
Urban green spaces (UGS) are an effective mitigation strategy for urban heat islands (UHIs) through their evapotranspiration and shading effects. Yet, the extent to which local UGS cooling effects vary across different background climates, plant characteristics settings global cities is not well understood. This study analysed 265 air temperature (TA) measurements from 58 published studies globally distributed sites infer potential influence of climate, variables among types (trees, grass, roofs walls). We show that trees were more at reducing TA, with reductions 2-3 times greater than grass walls. use a hierarchical linear mixed model reveal climate (mean annual temperature) (specific leaf area vegetation index) had greatest on types, while did significantly UGS. Notably, dominated overall cities, indicating tree growth in mild climates lower mean temperatures has against UHIs. Our findings provide insights using interventions, particularly worldwide diverse climatic environmental conditions highlight essential role creating healthy living environments citizens under extreme weather conditions.
Язык: Английский
Процитировано
22Urban Climate, Год журнала: 2024, Номер 57, С. 102105 - 102105
Опубликована: Авг. 16, 2024
Язык: Английский
Процитировано
8Building and Environment, Год журнала: 2025, Номер unknown, С. 112768 - 112768
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
1International Journal of Digital Earth, Год журнала: 2024, Номер 17(1)
Опубликована: Янв. 16, 2024
The intensified thermal environment in suburban areas is raising wide concerns for human society and public health due to rapid urbanization. Although the satellite-derived surface urban heat island intensity (SUHII) a commonly used indicator, it still needs be determined SUHII between challenges delineating their boundaries with changes. Thus, comprehensive analysis of spatial explanatory variables (SEVs) among highly needed. Here, using long-term satellite observations, we analyzed spatiotemporal patterns different temporal intervals (i.e. seasonal diurnal) contribution SEVs areas. Our results indicate that shows predominantly increasing trend from 2012–2021 cities China. Despite trends increasing/decreasing) being relatively consistent both suburban, latter higher proportion regarding various SEVs. Besides, partial least squares regression (PLSR) model major contributors are landscape shape index (LSI), patch density (PD), digital elevation (DEM), while areas, those critical LSI, normalized difference built-up (NDBI), DEM. These findings can facilitate sustainable design planning nature-based solution.
Язык: Английский
Процитировано
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