Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins DOI
Mingjie Yang, Lianqing Xue, Yuanhong Liu

и другие.

Environmental Research, Год журнала: 2023, Номер 243, С. 117813 - 117813

Опубликована: Дек. 1, 2023

Язык: Английский

Impact of seasonal global land surface temperature (LST) change on gross primary production (GPP) in the early 21st century DOI
Ao Wang, Maomao Zhang, Enqing Chen

и другие.

Sustainable Cities and Society, Год журнала: 2024, Номер 110, С. 105572 - 105572

Опубликована: Июнь 3, 2024

Язык: Английский

Процитировано

50

Exploring the scale effect of urban thermal environment through XGBoost model DOI
Jingjuan He, Yijun Shi, Lihua Xu

и другие.

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

Опубликована: Авг. 23, 2024

Язык: Английский

Процитировано

23

Assessing the differential impact of vegetated and built-up areas on heat exposure environment: A case study of Los Angeles DOI Creative Commons
Shengao Yi, Xiaojiang Li, Chenshuo Ma

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112538 - 112538

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

4

Impact of urban renewal on urban heat island: Study of renewal processes and thermal effects DOI

Songqing Zheng,

Xiaochun Chen,

Yilun Liu

и другие.

Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104995 - 104995

Опубликована: Окт. 12, 2023

Язык: Английский

Процитировано

34

Global distinct variations of surface urban heat islands in inter- and intra-cities revealed by local climate zones and seamless daily land surface temperature data DOI
Bo Yuan, Xuecao Li, Liang Zhou

и другие.

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2023, Номер 204, С. 1 - 14

Опубликована: Сен. 5, 2023

Язык: Английский

Процитировано

26

Modelling urban heat island effects: a global analysis of 216 cities using machine learning techniques DOI Creative Commons

Glenn Kong,

Yanni Zhao,

Jonathan Corcoran

и другие.

Computational 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

1

Greater local cooling effects of trees across globally distributed urban green spaces DOI Creative Commons
Jiyoung Kim, Abdou Khouakhi, Ron Corstanje

и другие.

The 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

22

Seasonal dynamics of land surface temperature and urban thermal comfort with land use land cover pattern in semi-arid Indian cities: Insights for sustainable Urban Management DOI

Shahfahad,

Swapan Talukdar, Mohd Waseem Naikoo

и другие.

Urban Climate, Год журнала: 2024, Номер 57, С. 102105 - 102105

Опубликована: Авг. 16, 2024

Язык: Английский

Процитировано

8

Dual potential of Garden Rooftop Farms for heat island mitigation and spatial productivity DOI
Xin Dong,

Xiaotong Feng,

Bao‐Jie He

и другие.

Building and Environment, Год журнала: 2025, Номер unknown, С. 112768 - 112768

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

1

Impacts of spatial explanatory variables on surface urban heat island intensity between urban and suburban regions in China DOI Creative Commons
Xuecao Li,

Shirao Liu,

Qiwei Ma

и другие.

International 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

5