Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands DOI Creative Commons
Haojian Deng,

Shiran Zhang,

Ming‐Hui Chen

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(16), P. 3048 - 3048

Published: Aug. 19, 2024

Local climate zones (LCZs) and urban functional (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding surface heat island (SUHI) effect. In this study, we retrieved two types land temperature (LST) data constructed 12 SUHI scenarios over Guangdong–Hong Kong–Macao Greater Bay Area Central region using six identification methods. It compared sensitivity differences among different LCZ UFZ to analyze global local influencing factors in by utilizing gradient boosting trees, geographically weighted regression, coefficient variation model. Results showed following: (1) The multi-scenario was significantly affected methods non-urban references. (2) morning, shading effect building clusters reduced intensity (SUHII) some built environment (such as 1 (compact high-rise zone) 5 (open midrise zone)). SUHIIs E (bare rock or paved 10 (industry were 4.22 °C 3.87 °C, respectively, both are classified highly sensitive SUHI. (3) exhibited regional variability, with importance such impervious ratio, elevation, average height, vegetation coverage, volume between LCZs UFZs. Amongst scenarios, an 87.43% 89.97% areas UFZs, found have low types. Overall, study helps planners managers gain more complexity high-density providing scientific basis future adaptability planning.

Language: Английский

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

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 114, P. 105763 - 105763

Published: Aug. 23, 2024

Language: Английский

Citations

18
Disentangling the non-linear relationships and interaction effects of urban digital transformation on carbon emission intensity DOI
Wentao Wang, Shenghua Zhou, Dezhi Li

et al.

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102283 - 102283

Published: Jan. 5, 2025

Language: Английский

Citations

0
Artificial Intelligence as a Catalyst for Management System Adaptability, Agility and Resilience: Mapping the Research Agenda DOI Creative Commons
Ion Popa, Simona Cătălina Ștefan,

Andrei Josan

et al.

Systems, Journal Year: 2025, Volume and Issue: 13(1), P. 47 - 47

Published: Jan. 12, 2025

Artificial intelligence (AI) is an increasingly notable presence in society, industries, and organizations, making its necessity felt more managerial decisions practices. This paper aims to outline the importance of topic related increase adaptability, agility, resilience management system as a result AI integration, resorting bibliometric type research. A total 107 papers from period 2007–2024 exported Web Science Core Collection database were analyzed, with support Biblioshiny software. proving be one heightened global interest, being comprehensively addressed by world leaders research technologies such United States, China, Great Britain, France, India, beyond. Collaborative relationships established between geographic regions are captured, noting power expansion theme on all continents globe. Likewise, thematic strategic evolution characterized surprising one, managing incorporate relate concepts strong technical IT character feature extraction, machine learning, reinforcement learning nature supporting customer-tailored interaction, employee skills development, company productivity, innovation.

Language: Английский

Citations

0
Unveiling Differential Impacts of Multidimensional Urban Morphology on Heat Island Effect Across Local Climate Zones: Interpretable CatBoost-SHAP Machine Learning Model DOI
Qiqi Liu,

Tian Hang,

Yunfei Wu

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112574 - 112574

Published: Jan. 1, 2025

Language: Английский

Citations

0
Revealing the driving factors of urban wetland park cooling effects using Random Forest regression and SHAP algorithm DOI
Yue Deng, Weiguo Jiang, Ziyan Ling

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106151 - 106151

Published: Jan. 1, 2025

Language: Английский

Citations

0
Net zero energy buildings and climate resilience narratives – Navigating the interplay in the building asset maintenance and management DOI
Bishal Baniya, Damien Giurco

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 1632 - 1648

Published: Jan. 21, 2025

Language: Английский

Citations

0
The Impact of Spatiotemporal Effect and Relevant Factors on the Urban Thermal Environment Through the XGBoost-SHAP Model DOI Creative Commons

Junqing Wei,

Yonghua Li,

Liqi Jia

et al.

Land, Journal Year: 2025, Volume and Issue: 14(2), P. 394 - 394

Published: Feb. 13, 2025

The urban thermal environment is a critical topic in contemporary studies. However, the mechanisms driving relationships between influencing factors and across different spatial scales temporal dimensions remain unclear, particularly as most of these exhibit nonlinearity. This study utilizes XGBoost SHAP models, combined with partial dependency plot, to analyze influence population activities, built environment, topography, ecological climatic conditions, landscape pattern on diurnal nocturnal land surface temperature (LST) changes rural areas Hangzhou throughout year. results indicate that during daytime, topography exerts strong LST both Hangzhou. At nighttime, activities becomes more pronounced. Meanwhile, patterns show no significant impact either or areas, regardless daytime nighttime. Additionally, we analyzed specific nonlinear LST. Finally, our findings suggest can interact synergistically pairs affect LST, this mechanism being prominent areas. Overall, categorizes examines contributing from perspectives, providing insights for developing planning strategies mitigate heat issues future.

Language: Английский

Citations

0
Nonlinear Effects of Human Settlements on Seasonal Land Surface Temperature Variations at the Block Scale: A Case Study of the Central Urban Area of Chengdu DOI Creative Commons

Muze Zhang,

Tong Hou, Yuping Ma

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 693 - 693

Published: March 25, 2025

The land surface temperature (LST) in the central urban area has shown a consistent upward trend over years, exacerbating heat island (SUHI) effect. Therefore, this study focuses on of Chengdu, using blocks as research scale. Gradient Boosting Decision Tree (GBDT) model and SHAP values are employed to explore nonlinear effects human settlements (HS) LST across different seasons. results show that (1) At block scale, overall impact HS all four seasons tracks following order: built environment (BE) > landscape pattern (LP) socio-economic development (SED). (2) LP is most important factor affecting summer, while BE greatest influence during spring, autumn, winter. (3) Most indicators exhibit seasonal variations their LST. impervious (ISA) exhibits significant positive autumn. In contrast, nighttime light index (NTL) functional mix degree (FMD) exert negative Additionally, normalized difference vegetation (NDVI) negatively affects both spring summer. Moreover, connectivity (CNT) density (FPD) demonstrate notable threshold (4) Certain interaction effects, some combinations these can effectively reduce This reveals HS–LST interactions through multidimensional analysis, offering block-scale planning strategies for sustainable thermal optimization.

Language: Английский

Citations

0
Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands DOI Creative Commons
Haojian Deng,

Shiran Zhang,

Ming‐Hui Chen

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(16), P. 3048 - 3048

Published: Aug. 19, 2024

Local climate zones (LCZs) and urban functional (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding surface heat island (SUHI) effect. In this study, we retrieved two types land temperature (LST) data constructed 12 SUHI scenarios over Guangdong–Hong Kong–Macao Greater Bay Area Central region using six identification methods. It compared sensitivity differences among different LCZ UFZ to analyze global local influencing factors in by utilizing gradient boosting trees, geographically weighted regression, coefficient variation model. Results showed following: (1) The multi-scenario was significantly affected methods non-urban references. (2) morning, shading effect building clusters reduced intensity (SUHII) some built environment (such as 1 (compact high-rise zone) 5 (open midrise zone)). SUHIIs E (bare rock or paved 10 (industry were 4.22 °C 3.87 °C, respectively, both are classified highly sensitive SUHI. (3) exhibited regional variability, with importance such impervious ratio, elevation, average height, vegetation coverage, volume between LCZs UFZs. Amongst scenarios, an 87.43% 89.97% areas UFZs, found have low types. Overall, study helps planners managers gain more complexity high-density providing scientific basis future adaptability planning.

Language: Английский

Citations

1