Spatiotemporal Characteristics of the Surface Urban Heat Island and Its Driving Factors Based on Local Climate Zones and Population in Beijing, China

Zhang, Yatong; Li, Delong; Liu, Laibao; Liang, Ze; Shen, Jincheng; Wei, Feili; Li, Shuangcheng

doi:10.3390/atmos12101271

Cited by 29 publications

(21 citation statements)

References 61 publications

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“…LCZ solutions can be classified into different types based on surface materials, ground cover, and the influence of human activities. A study by Zhang et al ( 67 ) on the temporal and spatial variability of UHI and urbanization in Beijing showed that LCZ conversion had a significant impact on surface UHII. In addition, Quan et al ( 68 ) conducted an LCZ classification of Beijing, combining MODIS data with wind and cloud data at 100 m; the results showed significant differences in the LCZ diurnal thermal response with seasonal changes.…”

Section: Discussionmentioning

confidence: 99%

Exploring seasonal diurnal surface temperature variation in cities based on ECOSTRESS data: A local climate zone perspective

Shi

Yang

Wang

et al. 2022

Front. Public Health

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High urban temperatures affect city livability and may be harmful for inhabitants. Analyzing spatial and temporal differences in surface temperature and the thermal impact of urban morphological heterogeneity can promote strategies to improve the insulation of the urban thermal environment. Therefore, we analyzed the diurnal variation of land surface temperature (LST) and seasonal differences in the Fifth Ring Road area of Beijing from the perspective of the Local Climate Zone (LCZ) using latest ECOSTRESS data. We used ECOSTRESS LST data with a resolution of 70 m to accurately interpret the effects of urban morphology on the local climate. The study area was dominated by the LCZ9 type (sparse low-rise buildings) and natural LCZ types, such as LCZA/B (woodland), LCZD (grassland), and LCZG (water body), mainly including park landscapes. There were significant differences in LST observed in different seasons as well as day and night. During daytime, LST was ranked as follows: summer > spring > autumn > winter. During night-time, it was ranked as follows: summer > autumn > spring > winter. All data indicated that the highest and lowest LST was observed in summer and winter, respectively. LST was consistent with LCZ in terms of spatial distribution. Overall, the LST of each LCZ during daytime was higher than that of night-time during different seasons (except winter), and the average LST of each LCZ during the diurnal period in summer was higher than that of other seasons. The LST of each LCZ during daytime in winter was lower than that of the corresponding night-time, which indicates that it is colder in the daytime during winter. The results presented herein can facilitate improved analysis of spatial and temporal differences in surface temperature in urban areas, leading to the development of strategies aimed at improving livability and public health in cities.

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Section: Discussionmentioning

confidence: 99%

Exploring seasonal diurnal surface temperature variation in cities based on ECOSTRESS data: A local climate zone perspective

Shi

Yang

Wang

et al. 2022

Front. Public Health

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“…In addition, only [38] used another LCZ land cover class as a reference, which used class B, which means scattered trees with mostly pervious land. However, only using LCZ classes to improve the SUHI calculation is considered an improvement in the research's articles [5,39].…”

Section: Surface Urban Heat Island (Suhi) Calculationmentioning

confidence: 99%

“…Climate Zones (LCZ) arranges the different urban and rural areas in more detail. In addition, the LCZ has been increasingly used in urban heat islands studies [5]. It was initially proposed in 2012 when regional climate zones were divided into several local climate zones within cities according to different LULC surface types, consequently allowing the correlation between climate information and urban planning [6].…”

Section: Introductionmentioning

confidence: 99%

Local Climate Zones to Identify Urban Surface Heat Islands: a Systematic Review

Fernandes¹,

Nascimento²,

Freitas³

et al. 2022

Preprint

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The Land Surface Temperature (LST) is an essential indicator for analyzing the Surface Urban Heat Island (SUHI). A factor contributing to its occurrence is the reflections of the different materials in urban and rural areas, which significantly affect the energy balance near the surface. Therefore, recent studies have increasingly used the Local Climate Zones (LCZ) classification system to discriminate those urban areas. Therefore, our study aims to do a systematic review using the PRISMA method of LCZ classification applied to understand the LST and the SUHI phenomenon. At first, it was found in the scientific literature 10,403 articles which, after passing through filtering stages, resulted in 51 that were further analyzed. Our results showed that these articles were very recent, beginning in 2016. However, presenting an increasing trend. China was the country with more studies. Landsat and TERRA/AQUA sensors appeared in 82% of the studies. The method that appears the most to LCZ definitions is from the World Urban Database. Finally, considering the current climatic changes, this systematic review can help new studies on SUHI identification through LCZ in different world areas using remote sensing data to estimate the LST.

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“…The surface UHI (SUHI) is monitored via land surface temperature values obtained from satellites such as LANDSAT 8 [6]. The UHI based on air temperatures (AUHI) is monitored using a network of ground-based temperature sensors from weather stations in urban and rural areas [7].…”

Section: Introductionmentioning

confidence: 99%

Determination of Air Urban Heat Island Parameters with High-Precision GPS Data

et al. 2022

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The urban heat island (UHI) effect can contribute to extreme heat exposure. This can be detrimental to human health. In this paper, we propose a method to estimate air temperature to evaluate the spatial distribution and to monitor the intensity of the air urban heat island (AUHI) from existing GPS infrastructure. The proposed algorithm is based on the relationship between the refractivity of the troposphere and environmental variables, as well as the relationships between the zenith tropospheric delay (ZTD), a by-product of the precise point positioning technique, and the refractivity of the troposphere. The advantage of GPS data is its high temporal resolution and the availability of embedded GPS receivers. In this paper, GPS-derived ZTD data from stations in the Hong Kong Special Administrative Region (HKSAR) of China and Tokyo in Japan are processed to estimate the hourly AUHI intensity. The results derived from this technique are validated using meteorological data in the same cities. Mean absolute error values of 0.79 °C in Hong Kong and 0.22 °C in Tokyo are found from data from the summer. Moreover, an overall accuracy of 0.51 °C is found.

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Spatiotemporal Characteristics of the Surface Urban Heat Island and Its Driving Factors Based on Local Climate Zones and Population in Beijing, China

Cited by 29 publications

References 61 publications

Exploring seasonal diurnal surface temperature variation in cities based on ECOSTRESS data: A local climate zone perspective

Exploring seasonal diurnal surface temperature variation in cities based on ECOSTRESS data: A local climate zone perspective

Local Climate Zones to Identify Urban Surface Heat Islands: a Systematic Review

Determination of Air Urban Heat Island Parameters with High-Precision GPS Data

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