Abstract

Urbanization experiences different speeds and forms under diverse development stages across the globe. However, urbanization-induced impacts on long-term surface urban heat island intensity (I_s) trends across global cities and the regulators of such impacts remain understudied. Here we estimate interannual trends in daytime I_s (i.e., urban-rural differences in surface temperatures) across 511 major cities for 1985 –2020 using annual averages calculated by using reconstructed land surface temperature data derived from more than >250,000 Landsat thermal images. Our study reveals that the global mean I_s growth rate is 0.156 °C/decade. We further examine I_s change associated with per 1% impervious land growth (denoted as ß) in each city throughout the research period and during different periods. The global mean ß is 0.018 ± 0.025 °C/% (mean ± 1 standard deviation) for the whole period, with greater values in humid than in arid climates; and the ß may change during different periods, e.g., it has more than tripled when urban impervious land exceeds 30%, indicating the spatiotemporally divergent impacts of urbanization on Is trends across global cities. The spatial variations in ß across global cities are well correlated with rural vegetation abundance and precipitation but not with urban population. Among these threemore » factors, rural vegetation abundance possesses the greatest standardized regression coefficient of partial least-squares model, signifying the critical role of biome background in regulating ß. Furthermore, the finding implies that future urbanization over densely vegetated regions should be more carefully and strategically planned due to the greater urbanization-induced surface warming effect.« less

Authors:

Li, Long ^[1]; Zhan, Wenfeng ^[2]; Hu, Leiqiu ^[3]; Chakraborty, Tirthankar ^[4]; Wang, Zhihua ^[5]; Fu, Peng ^[6]; Wang, Dazhong ^[1]; Liao, Weilin ^[7]; Huang, Fan ^[1]; Fu, Huyan ^[1]; Li, Jiufeng ^[1]; Liu, Zihan ^[1]; Du, Huilin ^[1]; Wang, Shasha ^[1]

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+ Show Author Affiliations

1. Nanjing University, Jiangsu (China)
2. Nanjing University, Jiangsu (China); Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (China)
3. University of Alabama in Huntsville, AL (United States)
4. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
5. Arizona State University, Tempe, AZ (United States)
6. Harrisburg University of Science and Technology, PA (United States)
7. Sun Yat-sen University, Guangdong (China)

Publication Date:

Thu Jun 01 00:00:00 EDT 2023

Research Org.:

Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:

1998055

Report Number(s):

PNNL-SA-185887
Journal ID: ISSN 0034-4257

Grant/Contract Number:  

AC05-76RL01830

Resource Type:

Accepted Manuscript

Journal Name:

Remote Sensing of Environment

Additional Journal Information:

Journal Volume: 295; Journal ID: ISSN 0034-4257

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES; Surface urban heat island; Thermal remote sensing; Land surface temperature; Data reconstruction; Landsat data