干旱区生态环境知识资源中心(Arid): Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data

Arid

DOI	10.1016/j.isprsjprs.2021.11.017
	Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data
	Si, Menglin; Li, Zhao-Liang; Nerry, Francoise; Tang, Bo-Hui; Leng, Pei; Wu, Hua; Zhang, Xia; Shang, Guofei
通讯作者	Li, ZL
来源期刊	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN	0924-2716
EISSN	1872-8235
出版年	2022
卷号	183 页码:321-335
英文摘要	In this study, the global surface urban heat island (SUHI) for 1711 cities during 2003-2019 was quantified by the dynamic urban-extent (DUE) scheme with the land surface temperature datasets from Moderate Resolution Imaging Spectroradiometer Terra and Aqua through the Google Earth Engine platform. The global pattern and regional contrasts of SUHI intensity (SUHII), and the interannual changing rate of SUHII (dSUHII) were revealed at the annual, summer, and winter scales. Further, the associated driving factors for long-term SUHII were explored from a temporal perspective. The main findings are as follows: (1) Globally, the global mean SUHII over 2003-2019 for annual daytime (1.32 degrees C) and annual nighttime (1.09 degrees C) by DUE are generally higher than that by previous simplified urban-extent (SUE) scheme. Accordingly, the summer daytime and nighttime SUHIIs are 1.98 degrees C, 1.05 degrees C, while the winter daytime and nighttime SUHIIs are 0.76 degrees C, and 1.10 degrees C. (2) The annual, summer, and winter dSUHIIs are 0.11 degrees C/decade, 0.27 degrees C/decade, and -0.06 degrees C/decade, respectively, at daytime, and 0.07 degrees C/decade, 0.09 degrees C/decade, and 0.10 degrees C/decade, respectively, at nighttime. (3) The global SUHII and dSUHII demonstrates evident regional contrast. The warm temperate and snow zones show distinct seasonal variations from summer to winter for daytime SUHII. Specifically, the negative daytime SUHII is detected for the arid zone, which exhibits the highest day-night variation and shows decreasing trend. (4) The global SUHII and dSUHII indicate distinct latitudinal variations, and an additional flip-flop (daytime SUHII < nighttime SUHII) region is detected between 10 degrees S and 20 degrees S. (5) The long-term daytime SUHII are negatively regulated by the urban-rural difference on evaporative cooling of vegetation; while at nighttime, it is negatively affected by the urban-rural difference on surface thermophysical properties. It implies the urban greening and surface properties should be specifically concerned to increase the evaporation cooling and reduce the heat retention in SUHII mitigation.
英文关键词	Global surface urban heat island Long-term trend MODIS Google Earth Engine
类型	Article
语种	英语
开放获取类型	Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000782583200001
WOS关键词	LOCAL BACKGROUND CLIMATE ; LAND-COVER ; INTENSITY VARIATIONS ; TEMPORAL TRENDS ; UNITED-STATES ; TEMPERATURE ; CITIES ; INDIANAPOLIS ; VARIABILITY ; CHINA
WOS类目	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393240
推荐引用方式 GB/T 7714	Si, Menglin,Li, Zhao-Liang,Nerry, Francoise,et al. Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data[J],2022,183:321-335.
APA	Si, Menglin.,Li, Zhao-Liang.,Nerry, Francoise.,Tang, Bo-Hui.,Leng, Pei.,...&Shang, Guofei.(2022).Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,183,321-335.
MLA	Si, Menglin,et al."Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 183(2022):321-335.