scholarly journals Exploring the Impacts and Temporal Variations of Different Building Roof Types on Surface Urban Heat Island

2021 ◽  
Vol 13 (14) ◽  
pp. 2840
Author(s):  
Yingbin Deng ◽  
Renrong Chen ◽  
Yichun Xie ◽  
Jianhui Xu ◽  
Ji Yang ◽  
...  
Keyword(s):  
Temporal Variations ◽  
Heat Island ◽  
Cool Season ◽  
Building Roof ◽  
Different Types ◽  
Natural Land ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Land Covers ◽  
The Impact

This study examined the impact of different types of building roofs on urban heat islands. This was carried out using building roof data from remotely sensed Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) imagery. The roofs captured included white surface, blue steel, dark metal, other dark material, and residential roofs; these roofs were compared alongside three natural land covers (i.e., forest trees, grassland, and water). We also collected ancillary data including building height, building density, and distance to the city center. The impacts of various building roofs on land surface temperature (LST) were examined by analyzing their correlation and temporal variations. First, we examined the LST characteristics of five building roof types and three natural land covers using boxplots and variance analysis with post hoc tests. Then, multivariate regression analysis was used to explore the impact of building roofs on LST. There were three key findings in the results. First, the mean LSTs for five different building roofs statistically differed from each other; these differences were more significant during the hot season than the cool season. Second, the impact of the five types of roofs on LSTs varied considerably from each other. Lastly, the contribution of the five roof types to LST variance was more substantial during the cool season. These findings unveil specific urban heat retention drivers, in which different types of building roofs are one such driver. The outcomes from this research may help policymakers develop more effective strategies to address the surface urban heat island phenomenon and its related health concerns.

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

Effects of Dubai coastline extreme urbanization in land and sea on local near-surface climate variables patterns

2021 ◽  
Author(s):  
Emily Elhacham ◽  
Pinhas Alpert
Keyword(s):  
Urban Heat Island ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Modis Data ◽  
The World ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Coastal Urbanization ◽  
The Impact

<p>Over a billion people currently live in coastal areas, and coastal urbanization is rapidly growing worldwide. Here, we explore the impact of an extreme and rapid coastal urbanization on near-surface climatic variables, based on MODIS data, Landsat and some in-situ observations. We study Dubai, one of the fastest growing cities in the world over the last two decades. Dubai's urbanization centers along its coastline – in land, massive skyscrapers and infrastructure have been built, while in sea, just nearby, unique artificial islands have been constructed.</p><p>Studying the coastline during the years of intense urbanization (2001-2014), we show that the coastline exhibits surface urban heat island characteristics, where the urban center experiences higher temperatures, by as much as 2.0°C and more, compared to the adjacent less urbanized zones. During development, the coastal surface urban heat island has nearly doubled its size, expanding towards the newly developed areas. This newly developed zone also exhibited the largest temperature trend along the coast, exceeding 0.1°C/year on average.</p><p>Overall, we found that over land, temperature increases go along with albedo decreases, while in sea, surface temperature decreases and albedo increases were observed particularly over the artificial islands. These trends in land and sea temperatures affect the land-sea temperature gradient which influences the breeze intensity. The above findings, along with the increasing relative humidity shown, directly affect the local population and ecosystem and add additional burden to this area, which is already considered as one of the warmest in the world and a climate change 'hot spot'.</p><p> </p><p><strong>References:</strong></p><p>E. Elhacham and P. Alpert, "Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001–2014)", <em>Earth’s Future</em>, 4, 2016. https://doi.org/10.1002/2015EF000325</p><p>E. Elhacham and P. Alpert, "Temperature patterns along an arid coastline experiencing extreme and rapid urbanization, case study: Dubai", submitted.</p>

Urban Informal Housing and Surface Urban Heat Island Intensity

2018 ◽  
Vol 9 (2) ◽  
pp. 158-177 ◽  
Author(s):  
Surabhi Mehrotra ◽  
Ronita Bardhan ◽  
Krithi Ramamritham
Keyword(s):  
Heat Stress ◽  
Spatial Analysis ◽  
Urban Heat Island ◽  
Urban Form ◽  
Spatial Association ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact ◽  
Slum Housing

Urbanization leads to the densification of built-up areas, and thereby increases surface heat island intensity which is one of the growing concerns in the rapidly urbanizing cities. Another notable aspect of cities like Mumbai is the uncontrolled growth of informal slum housing clusters, which have emerged as a significant urban built form in the landscape of cities. This study presents a case of Mumbai that aims to explore the linkages between slum housing—here referred as ‘slum urban form’ (SUF)—and surface urban heat island (SUHI) supported by spatial-statistical analysis. The magnitude of the impact of urban form on SUHI, measured by land surface temperature (LST), is examined using Cohen’s d index, which measures the effect size for two groups—SUF and ‘formal’ housing—on LST. The results confirm a ‘large’ effect indicating a significant difference in mean LST between the two groups. The spatial analysis reveals a statistically significant spatial clustering of LST and SUF ( p-value < 0.05), and bivariate local indicator of spatial association (LISA) confirms that the spatial association of SUF is surrounded by ‘high’ LST (Moran I: 0.49). The exploratory spatial analysis indicates that the contribution of SUF in elevating SUHI intensity is more than the formal housing areas and has increased vulnerability to heat stress. The results were validated on the ground using environmental sensors, which confirms the susceptibility of SUF to heat stress.

scholarly journals Analysis of the Impact of Land Use on Spatiotemporal Patterns of Surface Urban Heat Island in Rapid Urbanization, a Case Study of Shanghai, China

2020 ◽  
Vol 12 (3) ◽  
pp. 1171 ◽  
Author(s):  
Hongyu Du ◽  
Fengqi Zhou ◽  
Chunlan Li ◽  
Wenbo Cai ◽  
Hong Jiang ◽  
...  
Keyword(s):  
Land Use ◽  
Urban Heat Island ◽  
Land Surface ◽  
Agricultural Land ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

In the trend of global warming and urbanization, frequent extreme weather influences the life of citizens seriously. Shanghai, as a typical mega-city in China that has been successful in urbanization, suffers seriously from the urban heat island (UHI) effect. The research concentrates on the spatial and temporal pattern of surface UHI and land use. Then, the relation between them are further discussed. The results show that for the last 15 years, the UHI effect of Shanghai has been increasing continuously in both intensity and area. The UHI extends from the city center toward the suburban area. Along with the year, the ratio in area of Agricultural Land (AL), Wetland (WL), and Bare Land (BL) has decreased. On the contrary, Construction Land (CL) and Green Land (GL) have increased. The average land surface temperature (LST) rankings for each research year from high to low were all CL, BL, GL, AL, and WL. CL contributed the most to the UHI effect, while WL and GL contributed the most to mitigate the UHI. The conclusion provides practical advice aimed to mitigate the UHI effect for urban planning authorities.

scholarly journals Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

2017 ◽  
Author(s):  
Van Tran Thi ◽  
Bao Ha Duong Xuan ◽  
Mai Nguyen Thi Tuyet
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Ho Chi Minh City ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better

scholarly journals The Impact of landscape composition for urban heat island intensity in Addis Ababa City using Landsat data (1986–2016)

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
DMSLB Dissanayake ◽  
Takehiro Morimoto ◽  
Yuji Murayama ◽  
Manjula Ranagalage
Keyword(s):  
Urban Heat Island ◽  
Addis Ababa ◽  
Central Point ◽  
Heat Island ◽  
Multi Temporal ◽  
Urban Rural ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact ◽  
The City

<p><strong>Abstract.</strong> Exploring changes in land use and land cover (LULC) in the city area and its surrounding is important to understand the variation of surface urban heat island (SUHI) and surface urban heat island intensity (SUHII). The SUHII can be calculated based on the local climate zone by using land use and land cover compossition of the city and based on the urban rural zone . The objective of this research is to examine the spatiotemporal changes of LULC and the impact of its composition for the formation of SUHI in Addis Ababa City, Ethiopia based on the urban rural zones.</p><p> The mean center of the central business district of the Addis Ababa City was considered as the central point of the study area. We represented the 30&amp;thinsp;km&amp;thinsp;&amp;times;&amp;thinsp;30&amp;thinsp;km geographical area as a study area with a 15km radius from the central point. As data sources, multi-temporal satellite data provided by the United States Geological Survey (USGS) were used in respect to the years of 1986, 2001, and 2016. In the methodology, we first completed the classification of LULC by using pixel-oriented method for the three years and the validation of the classification has been made. For the classification five LULC classes were identified such as forest, impervious surface, grass land, bare land and crop land. Afterward, land surface temperature (LST) has been computed for three years respectively. Finally, urban rural gradient zones (URGZs) have been generated as a set of polygons with 210m distance in each zone from the central point of the study area. In order to evaluate the SUHII along the URGZs in respect to the LULC, the following analyses were accomplished: (i) the relationship between mean LST and composition of the LULC was computed, (ii) the SUHII was calculated based on the LST variation of main LULC categories and the temperature difference between URGZs, (iii) multi-temporal and multi-directional SUHII was computed, and (iv) linear regression analyses were used to assess the correlations of the mean LST with composition of LULC.</p><p> The results of the analyses show that (i) distribution pattern of SUHII has changed over the study period as results of changes in LULC, and (ii) mean LST gradually declines from city centre to outside of the city , then it can be seen increasing trends due to the effect of bare lands in rural area. This pattern can be seen over the three years as the result of multi-directional approach. The methodology presented will be able to apply other cities which are showing similar growth pattern by making necessary calibration, and our finding can be used as a proxy indicator to introduce appropriate landscape and town planning in a sustainable viewpoint in Addis Ababa City.</p>

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