The influence of different data and method on estimating the surface urban heat island intensity

Yao, Rui; Wang, Lunche; Huang, Xin; Niu, Ying; Chen, Yisen; Niu, Zigeng

doi:10.1016/j.ecolind.2018.01.044

Cited by 110 publications

(46 citation statements)

References 56 publications

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“…HI and T in an urban area are calculated by averaging all stations located within its 25‐km buffering extent (see Figure S3), and with population density larger than 500 persons per km 2 . The selection of 25 km as the extent of the buffer zone is in conformity with previous studies (Mishra et al, ; Yao et al, ; Zhou et al, ). For a given urban area, the HI and T in its surrounding rural areas are estimated by averaging all rural stations located in the outer zone extending between 25 and 100 km from the urban area in question (as illustrated in Figure S3), and with a population density of less than 200 persons per km 2 .…”

Section: Methodssupporting

confidence: 86%

Increasing Heat Stress in Urban Areas of Eastern China: Acceleration by Urbanization

Luo

Lau

2018

Geophysical Research Letters

155

100

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A combination of hot temperature and high humidity (high heat stress) has severe impacts on environment, society, and public health, especially in urban areas where the majority of the world's population lives. This study investigates the changes of heat stress in urban areas of eastern China and urbanization effects. Data for 242 urban areas and records from a dense network of nearly 2,000 stations are examined. All urban areas have experienced substantial increases in mean heat stress and the frequencies of extreme heat stress days and events during 1971–2014. The increases in human‐perceived heat stress are even stronger than air temperature. Urban areas experience more intense heat stress than the surrounding rural areas. We estimate that urbanization accounts for nearly 30% of the increase in mean and extreme heat stress. Urbanization effects are more prominent in the major urban conglomerates such as Beijing‐Tianjin‐Hebei and the Yangtze and Pearl river deltas.

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Section: Methodssupporting

confidence: 86%

Increasing Heat Stress in Urban Areas of Eastern China: Acceleration by Urbanization

Luo

Lau

2018

Geophysical Research Letters

155

100

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“…The UHI magnitude is important to thermal comfort and stress for residents in cities (Aflaki et al 2017;Deilami et al 2018), and is often responsible for death during summer heatwaves (Burke et al 2018;Ward et al 2016). The UHI effects have been intensifying with rapid urbanization (Aoyagi et al 2012;Koomen and Diogo 2017;Mohajerani et al 2017;Gaur et al 2018) under changed climate, leading to numerous studies investigating the spatiotemporal variation of UHI (Cao et al 2016;Gao et al 2018;Peng et al 2011), the driving factors of urban heat effect (Cao et al 2016;Mohajerani et al 2017;Yao et al 2018a) and mitigation strategies at different scales and different regions (Aflaki et al 2017; Kyriakodis and Santamouris 2018;Li et al 2014;Sharma et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Efficacy of Possible Strategies to Mitigate the Urban Heat Island Based on Urbanized High-Resolution Land Data Assimilation System (u-HRLDAS)

Gao

Chen

Shen

et al. 2019

Journal of the Meteorological Society of Japan

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Summer heat waves pose a great threat to public health in China. This paper took Wuhan (one of the four hottest furnaces cities in China) as an example to explore several strategies for mitigating the surface urban heat island (UHI) measured by the land surface temperature, including the use of green roofs, cool roofs, bright pavements, and alternations in urban building patterns. The offline urbanized High-Resolution Land Data Assimilation System (u-HRLDAS) was employed to conduct 1-km resolution numerical simulations, which also accounts for the effects of abundant lakes in Wuhan on UHI evolution with a dynamic lake model. The diurnal cycle and spatial distribution of simulated UHI were analyzed under different mitigation strategies. Results show that considering lake effects reduces the daytime (nighttime) UHI intensity by about 1.0 K (0.5 K). Employing green roofs and cool roofs are more effective in mitigating daytime UHI than the use of bright pavements. The maximum UHI reduction is about 2.1 K at 13:00 local time by replacing 80% of conventional roofs with green roofs. The UHI mitigation efficiency increases with larger fractions of green roofs, and increased albedo of roofs and roads. In contrast to the green roofs, cool roofs and bright pavements which are ineffective in nighttime, changing urban building pattern to mitigate the UHI is effective throughout the day. "Height-driven building structure changing" (raising the building height, and meanwhile changing the fraction of impervious surface in 3 each grid to keep the total building volume intact) can reduce the surface UHI intensity by 0.4-0.9 K, and "density-driven building structure changing" (distributing building density uniformly and the building height are modified to make the total building volume unchanged) reduces UHI by 1.2-2.6 K. These results showed new insights in mitigating the urban heat islands for a mega city like Wuhan and provides a practical guideline for policymakers to offer a more habitable city.

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“…Hu used nine urban design factors to construct the Sky View Factor (SVF), studied high-density urban areas with high UHI and low SVF as the research object, and tested the possibility of UHI by optimizing the urban-form SVF [24].Remote sensing technology, as an accurate and timely means to obtain macroscopic information on the Earth's surface, has been widely used in many fields [25]. Thermal infrared remote sensing technology is a common means of monitoring LST [26,27]. Using remote sensing images to extract UBD information is also a fast and effective method to make up for the shortcomings of traditional manual mapping methods.…”

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confidence: 99%

“…Remote sensing technology, as an accurate and timely means to obtain macroscopic information on the Earth's surface, has been widely used in many fields [25]. Thermal infrared remote sensing technology is a common means of monitoring LST [26,27]. Using remote sensing images to extract UBD information is also a fast and effective method to make up for the shortcomings of traditional manual mapping methods.…”

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confidence: 99%

Correlation Analysis between UBD and LST in Hefei, China, Using Luojia1-01 Night-Time Light Imagery

et al. 2019

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The urban heat island (UHI) is one of the essential phenomena of the modern urban climate. In recent years, urbanization in China has gradually accelerated, and the heat island effect has also intensified as the urban impervious surface area and the number of buildings is increasing. Urban building density (UBD) is one of the main factors affecting UHI, but there is little discussion on the relationship between the two. This paper takes Hefei as the research area, combines UBD data estimated by Luojia1-01 night-time light (NTL) imagery as the research object with land surface temperature (LST) data obtained from Landsat8 images, and carries out spatial correlation analysis on 0.5 × 0.5 km to 2 × 2 km resolution for them, so as to explore the relationship between UBD and UHI. The results show the following: (1) Luojia1-01 data have a good ability to estimate UBD and have fewer errors when compared with the actual UBD data; (2) At the four spatial scales, UBD and LST present a significant positive correlation that increases with the enlargement of the spatial scale; and (3) Moreover, the fitting effect of the Geographically Weighted Regression (GWR) model is better than that of the ordinary least squares (OLS) regression model. Appl. Sci. 2019, 9, 5224 2 of 20 absorbing heat faster and the specific heat capacity being smaller gives rise to limited heat release. In this way, the average LST in the area gradually increases with the spatial distribution of the UHI area to become more continuous and concentrated, forming a high-temperature area centered on artificial buildings in the city [1,9,10]. However, our comprehensive literature research found that past studies focused on the analysis of seasonal, daily, and annual variations of the UHI, which revealed the temporal and spatial variation of the UHI, the distribution characteristics of the horizontal and vertical directions, etc., while there has been less quantitative analysis of the single factors of UHIs, especially discussion of the ubiquitous relationship between impervious surfaces and UHI in the city.As an integral part of the urban impervious surface percentage, the urban building density (UBD) (percentage of built area) can directly reflect the degree of intensification and land-use efficiency in cities to some extent [11]. It is also an essential comprehensive social indicator that can function as an urban planning layout measure [12,13], resource utilization efficiency measure [14,15], and assessment of the urban ecological environment and livability [16][17][18][19]. Some researchers have pointed out that UBD is a crucial indicator to reduce the UHI effect [20] and proved a positive correlation between UBD and LST or UHI [21][22][23]. Additionally, researchers have tried to use a variety of urban design factors to study the relationships of UHIs, including UBD information. For example, Yang studied the summer heat island intensity of three high-rise residential districts in Shanghai, based on the three indices of building layout, density, and greeni...

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The influence of different data and method on estimating the surface urban heat island intensity

Cited by 110 publications

References 56 publications

Increasing Heat Stress in Urban Areas of Eastern China: Acceleration by Urbanization

Increasing Heat Stress in Urban Areas of Eastern China: Acceleration by Urbanization

Efficacy of Possible Strategies to Mitigate the Urban Heat Island Based on Urbanized High-Resolution Land Data Assimilation System (u-HRLDAS)

Correlation Analysis between UBD and LST in Hefei, China, Using Luojia1-01 Night-Time Light Imagery

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