Modelling urban cooling island impact of green space and water bodies on surface urban heat island in a continuously developing urban area

2018 ◽  
Vol 4 (2) ◽  
pp. 501-515 ◽  
Author(s):  
Sasanka Ghosh ◽  
Arijit Das
Keyword(s):  
Urban Heat Island ◽  
Urban Area ◽  
Green Space ◽  
Water Bodies ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Urban Cooling Island

scholarly journals A Methodology for Comparing the Surface Urban Heat Island in Selected Urban Agglomerations Around the World from Sentinel-3 SLSTR Data

2020 ◽  
Vol 12 (12) ◽  
pp. 2052 ◽  
Author(s):  
José Antonio Sobrino ◽  
Itziar Irakulis
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Urban Area ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Heat Island ◽  
Urban Agglomerations ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island

Retrieval of land surface temperature (LST) from satellite data allows to estimate the surface urban heat island (SUHI) as the difference between the LST obtained in the urban area and the LST of its surroundings. However, this definition depends on the selection of the urban and surroundings references, which translates into greater difficulty in comparing SUHI values in different urban agglomerations across the world. In order to avoid this problem, a methodology is proposed that allows reliable quantification of the SUHI. The urban reference is obtained from the European Space Agency Climate Change Initiative Land Cover and three surroundings references are considered; that is, the urban adjacent (Su), the future adjacent (Sf), and the peri-urban (Sp), which are obtained from mathematical expressions that depend exclusively on the urban area. In addition, two formulations of SUHI are considered: SUHIMAX and SUHIMEAN, which evaluate the maximum and average SUHI of the urban area for each of the three surrounding references. As the urban population growth phenomenon is a world-scale problem, this methodology has been applied to 71 urban agglomerations around the world using LST data obtained from the sea and land surface temperature radiometer (SLSTR) on board Sentinel-3A. The results show average values of SUHIMEAN of (1.8 ± 0.9) °C, (2.6 ± 1.3) °C, and (3.1 ± 1.7) °C for Su, Sf, and Sp, respectively, and an average difference between SUHIMAX and SUHIMEAN of (3.1 ± 1.1) °C. To complete the study, two additional indices have been considered: the Urban Thermal Field Variation Index (UFTVI) and the Discomfort Index (DI), which proved to be essential for understanding the SUHI phenomenon and its consequences on the quality of life of the inhabitants.

scholarly journals Investigating Spatiotemporal Patterns of Surface Urban Heat Islands in the Hangzhou Metropolitan Area, China, 2000–2015

2019 ◽  
Vol 11 (13) ◽  
pp. 1553 ◽  
Author(s):  
Fei Li ◽  
Weiwei Sun ◽  
Gang Yang ◽  
Qihao Weng
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Urban Heat Island ◽  
Metropolitan Area ◽  
Green Space ◽  
Utilization Efficiency ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
Surface Urban Heat Island

Rapid urbanization has resulted in a serious urban heat island effect in the Hangzhou Metropolitan Area of China during the past decades, negatively impacting the area’s sustainable development. Using Landsat images from 2000 to 2015, this paper analysed the spatial-temporal patterns in a surface urban heat island (SUHI) and investigated its relationship with urbanization. The derived land surface temperature (LST) and surface urban heat island intensity (SUHII) were used to quantify the SUHI effect. Spatial analysis was employed to illustrate the spatial distribution and evolution of a SUHI. The geographically weighted regression (GWR) model was implemented to identify statistically significant factors that influenced the change of SUHII. The results show that hot and very hot spot areas increased from 387 km2 in 2000 to 615 km2 in 2015, and the spatial distribution changed from a monocentric to a polycentric pattern. The results also indicate that high-LST clusters moved towards the east, which was consistent with urban expansion throughout the study period. These changes mirrored the intensive development of three satellite towns. The statistical analysis suggests that both population density (e.g., changes in population density, CPOPD) and green space (e.g., changes in green space fraction, CGSF) strongly affected the changes in SUHII at different stages of the urbanization process. Increasing in population density has a lastingly effect on elevating the SUHII, whereas increasing green space has a constantly significant effect in mitigating the SUHII. These findings suggest that urban planners and policymakers should protect the cultivated lands in suburbs and exurbs, and make efforts to improve the utilization efficiency of construction land by encouraging the migrating population to live within the existing built-up regions.

scholarly journals The Impact of the Land Cover Dynamics on Surface Urban Heat Island Variations in Semi-Arid Cities: A Case Study in Ahmedabad City, India, Using Multi-Sensor/Source Data

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3701 ◽  
Author(s):  
Pir Mohammad ◽  
Ajanta Goswami ◽  
Stefania Bonafoni
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Urban Area ◽  
Rural Area ◽  
Heat Island ◽  
Source Data ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact ◽  
Semi Arid

This study examines the behavior of land surface temperature (LST) and surface urban heat island (SUHI) from MODIS data over Ahmedabad city, Gujarat state (India), from 2003 to 2018. Summer and winter LST patterns were analyzed, both daytime and nighttime. Ahmedabad, one of the fastest growing metropolitan cities in India, is characterized by a semi-arid climate. The investigation focuses on the SUHI variations due to warming or cooling trends of both urban and rural areas, providing quantitative interpretations by means of multi-sensor/source data. Land cover maps, normalized differential vegetation index, surface albedo, evapotranspiration, urban population, and groundwater level were analyzed across the years to assess their impact on SUHI variations. Moreover, a field campaign was carried out in summer 2018 to measure LST in several rural and urban sites. During summer daytime, the rural zone exhibits a higher average LST than the urban area, resulting in a mean negative SUHI, typical of arid cities, while a slight positive SUHI (mean intensity of 0.4 °C) during winter daytime is present. An evident positive SUHI is found only during summer (1.8 °C) and winter nighttime (3.2 °C). The negative SUHI intensity is due to the low vegetation presence in the rural area, dominated by croplands turning into bare land surfaces during the pre-monsoon summer season. Higher LST values in the rural area than in the urban area are also confirmed by the field campaign, with an average difference of about 5 °C. Therefore, the impact of the rural LST in biasing the SUHI is evident, and a careful biophysical interpretation is needed. For instance, within the urban area, the yearly intensity of the summer daytime SUHI is not correlated with the evapotranspiration, while the correspondent summer daytime LST exhibits a significant negative correlation (−0.73) with evapotranspiration. Furthermore, despite the city growth across the years, the urban area does not generally reveal a temporal increase of the magnitude of the heat island but an enlargement of its spatial footprint.

LCZ scheme for assessing Urban Heat Island intensity in a complex urban area (Beirut, Lebanon)

Urban Climate ◽  
2021 ◽  
Vol 37 ◽  
pp. 100846
Author(s):  
Nada Badaro-Saliba ◽  
Jocelyne Adjizian-Gerard ◽  
Rita Zaarour ◽  
Georges Najjar
Keyword(s):  
Urban Heat Island ◽  
Urban Area ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Urban Heat

The impact of COVID-19 lockdowns on surface urban heat island changes and air-quality improvements across 21 major cities in the Middle East

2021 ◽  
pp. 117802
Author(s):  
Ahmed M. El Kenawy ◽  
Juan I. Lopez-Moreno ◽  
Matthew F. McCabe ◽  
Fernando Domínguez-Castro ◽  
Dhais Peña-Angulo ◽  
...  
Keyword(s):  
Air Quality ◽  
Middle East ◽  
Urban Heat Island ◽  
Heat Island ◽  
Quality Improvements ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

Quantifying the response of surface urban heat island to urban greening in global north megacities

2021 ◽  
pp. 149553
Author(s):  
Fengqi Cui ◽  
Rafiq Hamdi ◽  
Xiuliang Yuan ◽  
Huili He ◽  
Tao Yang ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Heat Island ◽  
Urban Greening ◽  
Global North ◽  
Urban Heat ◽  
Surface Urban Heat Island

scholarly journals Disproportionate exposure to urban heat island intensity across major US cities

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Angel Hsu ◽  
Glenn Sheriff ◽  
Tirthankar Chakraborty ◽  
Diego Manya
Keyword(s):  
Urban Heat Island ◽  
Census Tract ◽  
Demographic Data ◽  
Heat Exposure ◽  
Poverty Line ◽  
Built Environments ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Us Cities

AbstractUrban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.

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