From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands

People residing near stable urban heat islands (UHIs) experience a high long-term heat exposure, and the health consequences of such islands may be more severe than those of an expanding UHI; however, these areas are hidden in the overall heat island and not focused on. We developed a novel approach...

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Auteurs principaux:	Qi Liu, Miaomiao Xie, Rongrong Wu, Qian Xue, Bin Chen, Zhaoyang Li, Xinyu Li
Format:	article
Langue:	EN
Publié:	Elsevier 2021
Sujets:	Urban heat island Land surface temperature Warming factor Cooling factor Land use type Building density Ecology QH540-549.5
Accès en ligne:	https://doaj.org/article/b9111ad235244e9b9b2a750a2c69418c
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spelling	oai:doaj.org-article:b9111ad235244e9b9b2a750a2c69418c2021-12-01T04:58:26ZFrom expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands1470-160X10.1016/j.ecolind.2021.108046https://doaj.org/article/b9111ad235244e9b9b2a750a2c69418c2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21007111https://doaj.org/toc/1470-160XPeople residing near stable urban heat islands (UHIs) experience a high long-term heat exposure, and the health consequences of such islands may be more severe than those of an expanding UHI; however, these areas are hidden in the overall heat island and not focused on. We developed a novel approach to identify the locations and ranges of stable UHIs by considering multiple frequency urban heat islands (MFUHIs). The MFUHIs were identified through multi-temporal remote sensing data and morphological spatial pattern analysis (MSPA), and the approach was applied in the case area of Beijing, the capital city of China. Specifically, the MFUHIs in Beijing were classified according to the landscape characteristics, based on the field survey and remote sensing data. The landscape indicators included land-use types, biophysical parameters (normalised difference vegetation index (NDVI), proportion of water areas, and impervious surface area (ISA)) and 3-D metrics (building density and building heights), which were considered causative factors. The relationship between the land surface temperature and landscape indicators was examined using ordinary least-squares (OLS) regressions and the Area Weighted Contribution Index (AWCI). The results showed that the MFUHIs in Beijing have four key zones, in which the surface temperature is more than 9 ℃ higher than the average temperature of the urban area, and the air temperature is 3.3–8.5 ℃ higher than the built-up temperature in the non-UHI area. The OLS regression and spatial statistics of the landscape indicators and surface temperature indicated that the regions in which area where MFUHIs occur could be characterised by a relatively high degree of impervious surface coverage, lack of green space and water area, and presence of low-rise and high-density buildings. The average number of building-floors in MFUHIs was between 1.93 and 2.64, and the number of floors in the entire study area was less than 3.6. Moreover, the building-densities in the MFUHIs were 16.25% to 27.62% higher than that in the whole study area. According to the result of the AWCI and field survey, the MFUHIs were classified into transportation, historical block, commercial, and city village high-temperature centre. The main findings indicated that certain regions between the city centre and rural areas, in which sound planning is not implemented, are the hotspots of UHI mitigation and risk elimination regions. The proposed approach can help policymakers develop targeted mitigation strategies in urban planning.Qi LiuMiaomiao XieRongrong WuQian XueBin ChenZhaoyang LiXinyu LiElsevierarticleUrban heat islandLand surface temperatureWarming factorCooling factorLand use typeBuilding densityEcologyQH540-549.5ENEcological Indicators, Vol 130, Iss , Pp 108046- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Urban heat island Land surface temperature Warming factor Cooling factor Land use type Building density Ecology QH540-549.5
spellingShingle	Urban heat island Land surface temperature Warming factor Cooling factor Land use type Building density Ecology QH540-549.5 Qi Liu Miaomiao Xie Rongrong Wu Qian Xue Bin Chen Zhaoyang Li Xinyu Li From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
description	People residing near stable urban heat islands (UHIs) experience a high long-term heat exposure, and the health consequences of such islands may be more severe than those of an expanding UHI; however, these areas are hidden in the overall heat island and not focused on. We developed a novel approach to identify the locations and ranges of stable UHIs by considering multiple frequency urban heat islands (MFUHIs). The MFUHIs were identified through multi-temporal remote sensing data and morphological spatial pattern analysis (MSPA), and the approach was applied in the case area of Beijing, the capital city of China. Specifically, the MFUHIs in Beijing were classified according to the landscape characteristics, based on the field survey and remote sensing data. The landscape indicators included land-use types, biophysical parameters (normalised difference vegetation index (NDVI), proportion of water areas, and impervious surface area (ISA)) and 3-D metrics (building density and building heights), which were considered causative factors. The relationship between the land surface temperature and landscape indicators was examined using ordinary least-squares (OLS) regressions and the Area Weighted Contribution Index (AWCI). The results showed that the MFUHIs in Beijing have four key zones, in which the surface temperature is more than 9 ℃ higher than the average temperature of the urban area, and the air temperature is 3.3–8.5 ℃ higher than the built-up temperature in the non-UHI area. The OLS regression and spatial statistics of the landscape indicators and surface temperature indicated that the regions in which area where MFUHIs occur could be characterised by a relatively high degree of impervious surface coverage, lack of green space and water area, and presence of low-rise and high-density buildings. The average number of building-floors in MFUHIs was between 1.93 and 2.64, and the number of floors in the entire study area was less than 3.6. Moreover, the building-densities in the MFUHIs were 16.25% to 27.62% higher than that in the whole study area. According to the result of the AWCI and field survey, the MFUHIs were classified into transportation, historical block, commercial, and city village high-temperature centre. The main findings indicated that certain regions between the city centre and rural areas, in which sound planning is not implemented, are the hotspots of UHI mitigation and risk elimination regions. The proposed approach can help policymakers develop targeted mitigation strategies in urban planning.
format	article
author	Qi Liu Miaomiao Xie Rongrong Wu Qian Xue Bin Chen Zhaoyang Li Xinyu Li
author_facet	Qi Liu Miaomiao Xie Rongrong Wu Qian Xue Bin Chen Zhaoyang Li Xinyu Li
author_sort	Qi Liu
title	From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
title_short	From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
title_full	From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
title_fullStr	From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
title_full_unstemmed	From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands
title_sort	from expanding areas to stable areas: identification, classification and determinants of multiple frequency urban heat islands
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/b9111ad235244e9b9b2a750a2c69418c
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_version_	1718405685256912896

From expanding areas to stable areas: Identification, classification and determinants of multiple frequency urban heat islands

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