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 Evaluation of Urban Heat Island (UHI) Using Satellite Images in Densely Populated Cities of South Asia

Earth ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 86-110
Author(s):  
Manisha Maharjan ◽  
Anil Aryal ◽  
Bijay Man Shakya ◽  
Rocky Talchabhadel ◽  
Bhesh Raj Thapa ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
South Asia ◽  
Land Surface ◽  
Urban Areas ◽  
Well Being ◽  
Heat Island ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
The Impact

Rapid Urbanization, and other anthropogenic activities, have amplified the change in land-use transition from green space to heat emission in built-up areas globally. As a result, there has been an increase in the land surface temperature (LST) causing the Urban Heat Island (UHI) effect, particularly in large cities. The UHI effect poses a serious risk to human health and well-being, magnified in large developing cities with limited resources to cope with such issues. This study focuses on understanding the UHI effect in Kathmandu Valley (KV), Delhi, and Dhaka, three growing cities in South Asia. The UHI effect was evaluated by analyzing the UHI intensity of the city with respect to the surroundings. We found that the central urban area, of all three cities, experienced more heat zones compared to the peri-urban areas. The estimated average surface temperature ranged from 21.1 ∘C in March 2014 to 32.0 ∘C in June 2015 in KV, while Delhi and Dhaka experienced surface temperature variation from 29.7 ∘C in June 2017 to 40.2 ∘C in June 2019 and 23.6 ∘C in March 2017 to 33.2 ∘C in March 2014, respectively. Based on magnitude and variation of LST, highly built-up central KV showed heat island characteristics. In both Delhi and Dhaka, the western regions showed the UHI effect. Overall, this study finds that the UHI zones are more concentrated near the urban business centers with high population density. The results suggest that most areas in these cities have a rising LST trend and are on the verge of being UHI regions. Therefore, it is essential that further detailed assessment is conducted to understand and abate the impact of the temperature variations.

scholarly journals URBAN HEAT ISLAND UNDER IMPACT OF URBANIZATION IN HOCHIMINH CITY FROM REMOTE SENSING DATA

2010 ◽  
Vol 13 (3) ◽  
pp. 103-117
Author(s):  
Van Thi Tran
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Human Health ◽  
Rural Areas ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Impact Of Urbanization ◽  
The Impact

This paper presents the formation of urban heat island under the impact of urbanization in Hochiminh City in 1989-2006. Urbanization with increasing impervious surfaces impacted the common temperature background over the city by the warm rising trend. The results of applying remote sensing method extracting urban surface temperature defined the magnitude and space extension of “Surface urban heat island”, where the differences of surface temperature between urban and rural areas on 2006 image were about 11oC – 12oC. The magnitude of surface urban heat island increased in 6 to 26 times, particularly the biggest heat island was concentrated in the inner city with the area about 29.000ha. Urban heat island greatly influences the environment and the human health. Therefore, it is necessary to act on reducing the temperature of heat island in order to make our city more friendly to environment, to ensure human health, to decrease the energy demand and waste of water by sustainable development goal.

scholarly journals Comparasion of NDBI and NDVI as Indicators of Surface Urban Heat Island Effect in Landsat 8 Imagery: A Case Study of Iasi

2017 ◽  
Vol 11 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Paul Macarof ◽  
Florian Statescu
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Sensing Technology ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This study compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island effects in Landsat-8 OLI imagery by investigating the relationships between the land surface temperature (LST), NDBI and NDVI. The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural areas due to urbanization. With the development of remote sensing technology, it has become an important approach to urban heat island research. Landsat data were used to estimate the LST, NDBI and NDVI from four seasons for Iasi municipality area. This paper indicates than there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI varies by season. This paper suggests, NDBI is an accurate indicator of surface UHI effects and can be used as a complementary metric to the traditionally applied NDVI.

scholarly journals Climate change over UK cities: the urban influence on extreme temperatures in the UK climate projections

2021 ◽  
Author(s):  
William J. Keat ◽  
Elizabeth J. Kendon ◽  
Sylvia I. Bohnenstengel
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Model ◽  
Climate Projections ◽  
Heat Island ◽  
Night Time ◽  
Urban Heat ◽  
The Uk

AbstractIncreasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981–2000) and future (2061–2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to $$4~^{\circ }$$ 4 ∘ C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.

scholarly journals Quantification of Urban Heat Island-Induced Contribution to Advance in Spring Phenology: A Case Study in Hangzhou, China

2021 ◽  
Vol 13 (18) ◽  
pp. 3684
Author(s):  
Yingying Ji ◽  
Jiaxin Jin ◽  
Wenfeng Zhan ◽  
Fengsheng Guo ◽  
Tao Yan
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Heat Island ◽  
Spring Phenology ◽  
Urban Heat ◽  
The Difference

Plant phenology is one of the key regulators of ecosystem processes, which are sensitive to environmental change. The acceleration of urbanization in recent years has produced substantial impacts on vegetation phenology over urban areas, such as the local warming induced by the urban heat island effect. However, quantitative contributions of the difference of land surface temperature (LST) between urban and rural (ΔLST) and other factors to the difference of spring phenology (i.e., the start of growing season, SOS) between urban and rural (ΔSOS) were rarely reported. Therefore, the objective of this study is to explore impacts of urbanization on SOS and distinguish corresponding contributions. Using Hangzhou, a typical subtropical metropolis, as the study area, vegetation index-based phenology data (MCD12Q2 and MYD13Q1 EVI) and land surface temperature data (MYD11A2 LST) from 2006–2018 were adopted to analyze the urban–rural gradient in phenology characteristics through buffers. Furthermore, we exploratively quantified the contributions of the ΔLST to the ΔSOS based on a temperature contribution separation model. We found that there was a negative coupling between SOS and LST in over 90% of the vegetated areas in Hangzhou. At the sample-point scale, SOS was weakly, but significantly, negatively correlated with LST at the daytime (R2 = 0.2 and p < 0.01 in rural; R2 = 0.14 and p < 0.05 in urban) rather than that at nighttime. Besides, the ΔSOS dominated by the ΔLST contributed more than 70% of the total ΔSOS. We hope this study could help to deepen the understanding of responses of urban ecosystem to intensive human activities.

scholarly journals Evaluating the roles of green and built-up areas in reducing a surface urban heat island using remote sensing data

Urbani izziv ◽  
2019 ◽  
Vol 2 (30) ◽  
pp. 105-112
Author(s):  
Gordana Kaplan
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Heat Island ◽  
Negative Effects ◽  
Rapid Urbanization ◽  
Green Areas ◽  
Urban Heat ◽  
Surface Urban Heat Island

Rapid urbanization has several negative effects on both the environment and human health. Urbanization has also become an important contributor to global warming. One of these effects is the urban heat island (UHI), which is caused by human activities and defined as the temperature difference between urban and surrounding rural areas. With rapid urbanization in the past few decades, Skopje has experienced remarkable UHI effects. To investigate the roles of built-up and green areas in a surface UHI, this article uses satellite data from Landsat ETM+ to analyse the land surface temperature and high-resolution Planet Scope DOVE data to analyse built-up and green areas. For geostatistical analyses, seventeen randomly selected subareas in Skopje were used. The results show a significant correlation between the UHI and built-up areas, and strong correlation between green areas and areas not affected by the UHI, indicating that the UHI effect can be significantly weakened with additional green areas. One of the significant findings in the study is the ideal proportion of built-up (40%) and green areas (60%), where the UHI effect is weak, or in some cases prevented. For future studies, investigating other factors that may contribute to the UHI phenomenon is suggested.

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 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.

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