Exploring the spatiotemporal impacts of urban green space patterns on the core area of urban heat island DOI Creative Commons
Jiachen Liu,

Jianting Wu,

Yong Yang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112254 - 112254

Published: June 17, 2024

Language: Английский

Impacts of Land Use Characteristics on Extreme Heat Events: Insights from Explainable Machine Learning Model DOI
Hangying Su, Zhuoxu Qi,

Q. Wang

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106139 - 106139

Published: Jan. 1, 2025

Language: Английский

Citations

5

Urban green space and albedo impacts on surface temperature across seven United States cities DOI Creative Commons
Ian A. Smith, M. Patricia Fabian,

Lucy R. Hutyra

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 857, P. 159663 - 159663

Published: Oct. 24, 2022

Language: Английский

Citations

47

Cooling Effect of Urban Blue and Green Spaces: A Case Study of Changsha, China DOI Open Access
Xinyi Qiu, Sung–Ho Kil, Hyun-Kil Jo

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2023, Volume and Issue: 20(3), P. 2613 - 2613

Published: Feb. 1, 2023

The cooling effects of blue–green spaces on the urban heat island effect are complex and different. purpose this study is to simulate how space changes with its size shape. 53 green patches 28 water bodies in Changsha were extracted based Landsat images. A surface fitting model was used quantitatively reveal relationship between results show that enhanced increasing size, then would become stable after a certain range (threshold). Certain thresholds identified blue areas (2.98 ha 3.15 ha, respectively) distance, (4.84 4.92 magnitude. In addition, an area 9.08 landscape shape index (LSI) 2.97 could achieve better distance (413.46 m); 29.4 LSI 1.75 magnitude (5.17 °C). These findings provide useful guidelines for planning improving livability other regions terrain climate conditions similar Changsha.

Language: Английский

Citations

37

Effects of 2D/3D urban morphology on land surface temperature: Contribution, response, and interaction DOI Open Access
Bo Yuan, Liang Zhou,

Fengning Hu

et al.

Urban Climate, Journal Year: 2023, Volume and Issue: 53, P. 101791 - 101791

Published: Dec. 26, 2023

Language: Английский

Citations

32

Quantifying threshold and scale response of urban air and surface temperature to surrounding landscapes under extreme heat DOI Open Access
Xinyu Bai, Zhaowu Yu, Benyao Wang

et al.

Building and Environment, Journal Year: 2023, Volume and Issue: 247, P. 111029 - 111029

Published: Nov. 16, 2023

Language: Английский

Citations

27

Assessing the Cooling Effect of Blue-Green Spaces: Implications for Urban Heat Island Mitigation DOI Open Access

Pritipadmaja Pritipadmaja,

Rahul Garg, Ashok Sharma

et al.

Water, Journal Year: 2023, Volume and Issue: 15(16), P. 2983 - 2983

Published: Aug. 18, 2023

The Urban Heat Island (UHI) effect is a significant concern in today’s rapidly urbanising cities, with exacerbating heatwaves’ impact, urban livelihood, and environmental well-being. This study aims to assess the cooling of blue-green spaces Bhubaneswar, India, explore their implications for mitigating UHI effects. Satellite images were processed Google Earth Engine (GEE) produce information on spaces’ land surface temperatures (LST). Normalised Difference Vegetation Index (NDVI) Modified Water (MNDWI) employed quantify presence characteristics these spaces. findings revealed spatial variations LST, higher observed bare built-up areas lower proximity In addition, correlation analysis indicated strong influence index (NDBI) emphasising impact urbanisation local climate dynamics. demonstrated potential reducing Based results, strategic interventions proposed, such as increasing coverage green spaces, optimising access water bodies, integrating water-sensitive design principles into planning enhance effects foster more sustainable resilient environment. highlighted importance leveraging remote sensing GEE analyses. It provides valuable insights policymakers planners prioritise nature-based solutions heat mitigation Bhubaneswar other similar cities. Future research could delve deeper quantitative assessment benefits specific infrastructure socio-economic impacts communities.

Language: Английский

Citations

26

Mitigation of urban heat island in China (2000–2020) through vegetation-induced cooling DOI
Bowei Wu, Yuanyuan Zhang, Yuan Wang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 112, P. 105599 - 105599

Published: June 13, 2024

Language: Английский

Citations

15

Economic value of the hot-day cooling provided by urban green and blue space DOI Creative Commons
Laurence Jones, David Fletcher, Alice Fitch

et al.

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: 93, P. 128212 - 128212

Published: Jan. 23, 2024

Increasing high temperatures due to climate change are exacerbated by urban heat island effects, resulting in a range of human health and economic impacts. The green blue infrastructure (GBI) cities that underpins nature-based solutions (NBS) can help alleviate hot-day temperatures. In this study we bring together multiple data sources evaluate the cooling benefit provided GBI terms avoided losses labour productivity, for eleven City Regions Great Britain, over ten-year period. We defined extent include (woodland, grassland parks, gardens) (rivers canals, lakes ponds) features within cities, derived aggregate factors areas each Region, applying additional buffer zones around larger features. collated gridded meteorology assess number hot-days exceeding 28 °C Wet Bulb Globe Temperature Region period 2008-2017, applied response functions loss worker productivity ten sectors. For (aggregated adjacent >200m2), gardens make up biggest component (26% extent) closely followed parks (24%), with woodland at 6%. factor ranged from 0.64 – 0.89 across Regions. was greatest London, its greater exposure hot days, contribution economy than other hottest year 2015, London £13.97 m. varied considerably one next, depending on meteorology, will increase under change.

Language: Английский

Citations

12

Cooling efficacy of trees across cities is determined by background climate, urban morphology, and tree trait DOI Creative Commons
Haiwei Li, Yongling Zhao, Chenghao Wang

et al.

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Dec. 10, 2024

Abstract Urban planners and other stakeholders often view trees as the ultimate panacea for mitigating urban heat stress; however, their cooling efficacy varies globally is influenced by three primary factors: tree traits, morphology, climate conditions. This study analyzes 182 studies on effects of across 17 climates in 110 global cities or regions. Tree implementation reduces peak monthly temperatures to below 26 °C 83% cities. Trees can lower pedestrian-level up 12 through large radiation blockage transpiration. In tropical, temperate, continental climates, a mixed-use deciduous evergreen open morphology provides approximately 0.5 more than single species approach. arid predominate demonstrate effective within compact morphology. Our offers context-specific greening guidelines harness face warming.

Language: Английский

Citations

9

Spatial Differentiation in Urban Thermal Environment Pattern from the Perspective of the Local Climate Zoning System: A Case Study of Zhengzhou City, China DOI Creative Commons
Jinghu Pan,

Bo Yu,

Yingbiao Zhi

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(1), P. 40 - 40

Published: Jan. 2, 2025

In order to assess the spatial and temporal characteristics of urban thermal environment in Zhengzhou City supplement climate adaptation design work, based on Landsat 8–9 OLI/TIRS C2 L2 data for 12 periods from 2019–2023, combined with lLocal zone (LCZ) classification subsurface classification, this study, we used statistical mono-window (SMW) algorithm invert land surface temperature (LST) classify heat island (UHI) effect, analyze differences distribution environments areas aggregation characteristics, explore influence LCZ landscape pattern temperature. The results show that proportions built natural types Zhengzhou’s main metropolitan area are 79.23% 21.77%, respectively. most common landscapes wide mid-rise (LCZ 5) structures large-ground-floor 8) structures, which make up 21.92% 20.04% study area’s total area, varies seasons, pooling during summer peaking winter, strong or extremely islands centered suburbs a hot cold spots aggregated observable features. As building heights increase, UHI 1–6) increases then reduces spring, summer, autumn decreases winter as increase. Water bodies G) dense woods A) have lowest effects among settings. Building size is no longer primary element affecting LST buildings become taller; instead, connectivity clustering take center stage. Seasonal variations, variations types, responsible area. should see an increase vegetation cover, gaps must be appropriately increased.

Language: Английский

Citations

1