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

Exploring the relationship between urban green development and heat island effect within the Yangtze River Delta Urban Agglomeration DOI
Zhanyu Liu,

S.Y. Zhang

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106204 - 106204

Published: Feb. 1, 2025

Language: Английский

Citations

4

Decoding spatial patterns of urban thermal comfort: Explainable machine learning reveals drivers of thermal perception DOI
Chunguang Hu, Hui Zeng

Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 114, P. 107895 - 107895

Published: March 5, 2025

Language: Английский

Citations

4

Valuation of the 2020 Gross Ecosystem Product of China and Analysis of Driving Factors DOI
Kairui Li, Hong Fan,

Jiani Ouyang

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145741 - 145741

Published: May 1, 2025

Language: Английский

Citations

0

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

Examining urban agglomeration heat island with explainable AI: An enhanced consideration of anthropogenic heat emissions DOI

Tianyu Sheng,

Zhixin Zhang,

Zhen Qian

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 59, P. 102251 - 102251

Published: Dec. 20, 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

1