Energy Efficiency Retrofit for Existing Residential Buildings in China’s HSCW Zone in Multiple Scenarios: Energy Economic Analysis DOI
Kaiyue Wu, Yuhua Li, Zhicheng Wu

et al.

Journal of Architectural Engineering, Journal Year: 2024, Volume and Issue: 31(1)

Published: Nov. 3, 2024

Language: Английский

Advancing the local climate zones framework: a critical review of methodological progress, persisting challenges, and future research prospects DOI Creative Commons
Jie Han, Nan Mo, Jingyi Cai

et al.

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: April 27, 2024

Abstract The local climate zones (LCZs) classification system has emerged as a more refined method for assessing the urban heat island (UHI) effect. However, few researchers have conducted systematic critical reviews and summaries of research on LCZs, particularly regarding significant advancements this field in recent years. This paper aims to bridge gap scientific by systematically reviewing evolution, current status, future trends LCZs framework research. Additionally, it critically assesses impact climate-responsive planning design. findings study highlight several key points. First, challenge large-scale, efficient, accurate mapping persists issue Despite challenge, universality, simplicity, objectivity make promising tool wide range applications future, especially realm In conclusion, makes substantial contribution advancement advocates broader adoption foster sustainable development. Furthermore, offers valuable insights practitioners engaged field.

Language: Английский

Citations

11

Investigating the effects of local climate zones on land surface temperature using spectral indices via linear regression model: a seasonal study of Sapanca Lake DOI
Öznur Işınkaralar, Emmanuel Yeboah, Kaan Işınkaralar

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(3)

Published: Feb. 7, 2025

Language: Английский

Citations

1

Spatial effect of urban morphology on land surface tempature from the perspective of local climate zone DOI
Xinyue Wang, Jun Yang, Wenbo Yu

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 36, P. 101324 - 101324

Published: Aug. 18, 2024

Language: Английский

Citations

4

Seasonal variation in vegetation cooling effect and its driving factors in a subtropical megacity DOI

Jianbiao Luo,

Tao Xu,

Chunhua Yan

et al.

Building and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 112065 - 112065

Published: Sept. 1, 2024

Language: Английский

Citations

4

Local climate zone framework: seasonal dynamics of surface urban heat island and its influencing factors in three Chinese urban agglomerations DOI Creative Commons
Haojian Deng, Jiali Feng, Kai Liu

et al.

GIScience & Remote Sensing, Journal Year: 2025, Volume and Issue: 62(1)

Published: April 16, 2025

Language: Английский

Citations

0

Impact of blue spaces on urban microclimate in different climate zones, daytimes and seasons – a systematic review DOI Creative Commons
Lukas Fricke, Rupert Legg, Nadja Kabisch

et al.

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: unknown, P. 128528 - 128528

Published: Oct. 1, 2024

Language: Английский

Citations

2

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

Characterization of hydrogeochemical elements in determining the ground water quality for irrigation potential and its correlation with climatological parameters of chennai basin aquifer system, southern india DOI

Sivakumar Muthu,

T. Subramani,

Vishnuvardan Narayanamurthi

et al.

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(11)

Published: Oct. 4, 2024

Language: Английский

Citations

1

Evaluating the natural cooling potential of waterbodies in dense urban landscape: A case study of Bengaluru, India DOI

Arpit Verma,

Sonam Agrawal

Urban Climate, Journal Year: 2024, Volume and Issue: 58, P. 102200 - 102200

Published: Nov. 1, 2024

Language: Английский

Citations

1

Exploring River Cooling Effects in a Mountainous City: A Study Across Normal and Extreme Summer Weather Conditions DOI

Yifei Zhou,

Rongfei Zhang,

Fei Xu

et al.

Published: Jan. 1, 2024

Although urban rivers are considered to have a mitigating effect on the extreme heat stress, influences of topographical characteristics still remain poorly understood, particularly under extremely hot weather conditions. Taking mountainous city Chongqing as an example, this research focuses river cooling effects surrounding environment during normal and summer days based 3 indices: River Cooling Intensity (RCI), Distance (RCD) Cumulative (CRCI). Employing Boosted Regression Tree (BRT) model, impacts environmental variables been explored. The findings underscore pronounced intensification day, with Index (RCI) not only rising from average 5.5°C day 6.4°C but also exhibiting broader range variability, reflected by increase in standard deviation 2.4°C 3.1°C. Topographical exhibited strong effects, relative importance for RCI being 27.6% 31.5% respectively. Moreover, elevation slope ascent descent patterns their cooling, while patch density width were relatively fluctuating, showing whole. These can provide foundation planners managers develop strategies aimed at improving thermal riverside areas.

Language: Английский

Citations

0