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

и другие.

Sustainability, Год журнала: 2024, Номер 16(20), С. 9103 - 9103

Опубликована: Окт. 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.

Язык: 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, Год журнала: 2025, Номер unknown, С. 106204 - 106204

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

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, Год журнала: 2025, Номер 114, С. 107895 - 107895

Опубликована: Март 5, 2025

Язык: Английский

Процитировано

4

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

Jiani Ouyang

и другие.

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 145741 - 145741

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

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

Fei Feng,

Chengyang Xu

и другие.

Sustainable Cities and Society, Год журнала: 2024, Номер unknown, С. 106092 - 106092

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2

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

Tianyu Sheng,

Zhixin Zhang,

Zhen Qian

и другие.

Urban Climate, Год журнала: 2024, Номер 59, С. 102251 - 102251

Опубликована: Дек. 20, 2024

Язык: Английский

Процитировано

2

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

и другие.

Sustainability, Год журнала: 2024, Номер 16(20), С. 9103 - 9103

Опубликована: Окт. 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.

Язык: Английский

Процитировано

1