Quantifying the main and interactive effects of the dominant factors on the diurnal cycles of land surface temperature in typical urban functional zones

被引:9
作者
Chen, Jike [1 ,2 ,3 ]
Wang, Kaixin [1 ]
Du, Peijun [4 ]
Zang, Yufu [1 ,2 ,3 ]
Zhang, Peng [5 ]
Xia, Junshi [6 ]
Chen, Cheng [7 ]
Yu, Zhaowu [8 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
[2] Minist Nat Resources, Technol Innovat Ctr Integrat Applicat Remote Sensi, Nanjing 210044, Peoples R China
[3] Jiangsu Engn Ctr Collaborat Nav Positioning & Smar, Nanjing 210044, Peoples R China
[4] Nanjing Univ, Sch Geog & Ocean Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Key Lab Land Satellite Remote Sensing Applicat,Min, Nanjing 210023, Jiangsu, Peoples R China
[5] Anhui Univ, Sch Artificial Intelligence, Hefei 230601, Peoples R China
[6] RIKEN, RIKEN Ctr Adv Intelligence Project, Tokyo 1030027, Japan
[7] Jiangsu Prov Surveying & Mapping Engn Inst, Nanjing 210019, Peoples R China
[8] Fudan Univ, Dept Environm Sci & Engn, 2005 Songhu Rd, Shanghai 200438, Peoples R China
关键词
Land surface temperature; Urban functional zone; Diurnal difference; Interaction effect; Urban morphology; Socio-economics; SPACEBORNE THERMAL EMISSION; REFLECTION RADIOMETER ASTER; LOCAL CLIMATE ZONE; SKY VIEW FACTOR; HEAT-ISLAND; CITY; COVER; DYNAMICS; IMPACT; CONFIGURATION;
D O I
10.1016/j.scs.2024.105727
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The urban heat island (UHI) effect exists both during daytime and nighttime and varies with urban characteristics, such as 2D/3D urban morphology and socio-economics. However, there is a lack of quantitative understanding of the roles of these characteristics in influencing land surface temperature (LST) variations in different urban functional zones (UFZs) throughout the diurnal cycle. In this study, we examined the responses of diurnal LSTs in different UFZs to 2D/3D urban morphology and socio-economic variables. Results showed the following: (1) During daytime, the main drivers of LST varied with not only the UFZs but also the observation times; during nighttime, the LST variations across different UFZs were largely controlled by 3D urban morphology and socio-economic factors. (2) At 10:37, LST declined most rapidly when the percentage of tree cover (PER_Tree) exceeded a certain threshold. The threshold values of PER_Tree were 85%, 70%, 50%, and 60% for the residential, industrial, commercial, and public service zones, respectively. Irrespective of the UFZs, a nighttime cooling effect occurred only when sky view factor (SVF) exceeded 0.8. (3) For locations with high population density (Pop_Den) in the residential zone, whether urban trees induced a cooling effect depended on both the observation time and PER_Tree during daytime; however, a higher SVF tended to result in an increased LST during nighttime. In the public service zone, when Pop_Den exceeded 50, urban trees with high height contributed to nighttime LST cooling, whereas a warming effect occurred with trees with low height. The direct implications of this study suggest that 3D urban morphology and socio-economics are more efficient mitigation strategies for all UFZs at night, and the interactive effects between the dominant drivers of diurnal LSTs should be considered to cool the city most effectively.
引用
收藏
页数:22
相关论文
共 93 条
  • [1] The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): data products for the high spatial resolution imager on NASA's Terra platform
    Abrams, M
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2000, 21 (05) : 847 - 859
  • [2] Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island
    Arnfield, AJ
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2003, 23 (01) : 1 - 26
  • [3] Bringing Ecosystem Services into Economic Decision-Making: Land Use in the United Kingdom
    Bateman, Ian J.
    Harwood, Amii R.
    Mace, Georgina M.
    Watson, Robert T.
    Abson, David J.
    Andrews, Barnaby
    Binner, Amy
    Crowe, Andrew
    Day, Brett H.
    Dugdale, Steve
    Fezzi, Carlo
    Foden, Jo
    Hadley, David
    Haines-Young, Roy
    Hulme, Mark
    Kontoleon, Andreas
    Lovett, Andrew A.
    Munday, Paul
    Pascual, Unai
    Paterson, James
    Perino, Grischa
    Sen, Antara
    Siriwardena, Gavin
    van Soest, Daan
    Termansen, Mette
    [J]. SCIENCE, 2013, 341 (6141) : 45 - 50
  • [4] Spatio-temporal analysis of the relationship between 2D/3D urban site characteristics and land surface temperature
    Berger, C.
    Rosentreter, J.
    Voltersen, M.
    Baumgart, C.
    Schmullius, C.
    Hese, S.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2017, 193 : 225 - 243
  • [5] Investigating the relationship between local climate zone and land surface temperature using an improved WUDAPT methodology - A case study of Yangtze River Delta, China
    Cai, Meng
    Ren, Chao
    Xu, Yong
    Lau, Kevin Ka-Lun
    Wang, Ran
    [J]. URBAN CLIMATE, 2018, 24 : 485 - 502
  • [6] Seasonal and diurnal surface urban heat islands in China: an investigation of driving factors with three-dimensional urban morphological parameters
    Cao, Shisong
    Cai, Yile
    Du, Mingyi
    Weng, Qihao
    Lu, Linlin
    [J]. GISCIENCE & REMOTE SENSING, 2022, 59 (01) : 1121 - 1142
  • [7] Exploring diurnal thermal variations in urban local climate zones with ECOSTRESS land surface temperature data
    Chang, Yue
    Xiao, Jingfeng
    Li, Xuxiang
    Middel, Ariane
    Zhang, Yunwei
    Gu, Zhaolin
    Wu, Yiping
    He, Shan
    [J]. REMOTE SENSING OF ENVIRONMENT, 2021, 263
  • [8] Mapping Urban Land Cover of a Large Area Using Multiple Sensors Multiple Features
    Chen, Jike
    Du, Peijun
    Wu, Changshan
    Xia, Junshi
    Chanussot, Jocelyn
    [J]. REMOTE SENSING, 2018, 10 (06)
  • [9] The Influence of Sky View Factor on Daytime and Nighttime Urban Land Surface Temperature in Different Spatial-Temporal Scales: A Case Study of Beijing
    Chen, Qiang
    Cheng, Qianhao
    Chen, Yunhao
    Li, Kangning
    Wang, Dandan
    Cao, Shisong
    [J]. REMOTE SENSING, 2021, 13 (20)
  • [10] Contribution of urban functional zones to the spatial distribution of urban thermal environment
    Chen, Yang
    Yang, Jun
    Yang, Ruxin
    Xiao, Xiangming
    Xia, Jianhong
    [J]. BUILDING AND ENVIRONMENT, 2022, 216