Urban Heat Island Differentiation and Influencing Factors: A Local Climate Zone Perspective DOI Open Access
Shunbin Ning, Yuan Zhou, Manlin Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(20), P. 9103 - 9103

Published: Oct. 21, 2024

With the acceleration of urbanization, urban heat island (UHI) effect has become a major environmental challenge, severely affecting quality life residents and ecological environment. Quantitative analysis factors influencing intensity (UHII) is crucial for precise planning. Although extensive research investigated causes UHI effects their spatial variability, most studies focus on macro-scale analyses, overlooking heterogeneity thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, study took central area Chengdu, constructing LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze clustering across different LCZs. By Ordinary Least Squares (OLS) Geographically Weighted Regression (GWR) models, further explored these zones. The results showed that: (1) Chengdu’s built natural environments had comparable proportions, with scattered building zone comprising highest proportion at 22.12% in environment, low vegetation accounting 21.8% UHII values ranged from 10.2 °C −1.58 °C, based specific measurement conditions. Since varied meteorological conditions, time, seasons, selection rural reference points, represented dynamic during period were not constant. (2) morphology exhibited significant heterogeneity, global I index 0.734, indicating high degree correlation. value found impervious surfaces (0.776), while lowest floor ratio (0.176). (3) GWR model demonstrated greater explanatory power compared OLS model, fit 0.827. impact morphological significantly environments, substantial difference observed sky view factor, which standard deviation 13.639. findings provide recommendations planning, aiming mitigate enhance residents.

Language: Английский

Mapping local climate zones and its applications at the global scale: A systematic review of the last decade of progress and trend DOI

Renfeng Wang,

Mengmeng Wang, Chao Ren

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 57, P. 102129 - 102129

Published: Sept. 1, 2024

Language: Английский

Citations

16

Thermal hazards in urban spaces: A review of climate-resilient planning and design to reduce the heat stress DOI
Aman Gupta, Bhaskar De,

Sutapa Das

et al.

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102296 - 102296

Published: Jan. 25, 2025

Language: Английский

Citations

2

Optimizing Urban Green Space Configurations for Enhanced Heat Island Mitigation: A Geographically Weighted Machine Learning Approach DOI
Yue Zhang,

Jingtian Ge,

Siyuan Wang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 106087 - 106087

Published: Dec. 1, 2024

Language: Английский

Citations

8

Decadal assessment of local climate utilizing meteorological analysis and observation data: Thermal environment changes in the Tokyo area DOI
Xiang Wang,

Hongyuan Jia,

Keisuke Nakao

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106138 - 106138

Published: Jan. 1, 2025

Language: Английский

Citations

0

Isolating Urban Form Impacts on Spatiotemporal Distribution of Surface Meteorology in Coastal Cities during Extreme Heat Events DOI Creative Commons
Dun Zhu, Ryozo Ooka

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106242 - 106242

Published: Feb. 1, 2025

Language: Английский

Citations

0

Revealing the impact of urban land use patterns on land surface temperature through graph attention networks DOI

Hongbin Xu,

Siyi Zhang, Chong Wu

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106369 - 106369

Published: April 1, 2025

Language: Английский

Citations

0

Impact of block morphology on urban thermal environment with the consideration of spatial heterogeneity DOI
Chanjuan Wang,

Zongmao Li,

Yuan Su

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 113, P. 105622 - 105622

Published: July 2, 2024

Language: Английский

Citations

2

Rural heat island effect of centralized residences in China: Mitigation through localized measures DOI
Yiming Du, Anxiao Zhang, Zhen Qi

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 114, P. 105782 - 105782

Published: Aug. 28, 2024

Language: Английский

Citations

2

Spatiotemporal characteristics and robustness analysis of the thermal network in Beijing, China DOI
Xiang Cao,

Fei Feng,

Chengyang Xu

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 106092 - 106092

Published: Dec. 1, 2024

Language: Английский

Citations

2

Urban Heat Island Differentiation and Influencing Factors: A Local Climate Zone Perspective DOI Open Access
Shunbin Ning, Yuan Zhou, Manlin Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(20), P. 9103 - 9103

Published: Oct. 21, 2024

With the acceleration of urbanization, urban heat island (UHI) effect has become a major environmental challenge, severely affecting quality life residents and ecological environment. Quantitative analysis factors influencing intensity (UHII) is crucial for precise planning. Although extensive research investigated causes UHI effects their spatial variability, most studies focus on macro-scale analyses, overlooking heterogeneity thermal characteristics within local climate zones (LCZs) under rapid urbanization. To address this gap, study took central area Chengdu, constructing LCZ map using multisource remote sensing data. Moran’s Index was employed to analyze clustering across different LCZs. By Ordinary Least Squares (OLS) Geographically Weighted Regression (GWR) models, further explored these zones. The results showed that: (1) Chengdu’s built natural environments had comparable proportions, with scattered building zone comprising highest proportion at 22.12% in environment, low vegetation accounting 21.8% UHII values ranged from 10.2 °C −1.58 °C, based specific measurement conditions. Since varied meteorological conditions, time, seasons, selection rural reference points, represented dynamic during period were not constant. (2) morphology exhibited significant heterogeneity, global I index 0.734, indicating high degree correlation. value found impervious surfaces (0.776), while lowest floor ratio (0.176). (3) GWR model demonstrated greater explanatory power compared OLS model, fit 0.827. impact morphological significantly environments, substantial difference observed sky view factor, which standard deviation 13.639. findings provide recommendations planning, aiming mitigate enhance residents.

Language: Английский

Citations

0