Exploring the effect of COVID-19 pandemic lockdowns on urban cooling: A tale of three cities.

Autor: Mijani N; Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran., Karimi Firozjaei M; Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran., Mijani M; Department of Geography and Urban planning, Faculty of Geography, Payame Noor University of Isfahan, Isfahan, Iran., Khodabakhshi A; Department of Nutrition, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran.; Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran., Qureshi S; Institute of Geography, Humboldt University of Berlin, Rudower Chaussee 16, 12489 Berlin, Germany., Jokar Arsanjani J; Geoinformatics Research Group, Department of Planning and Development, Aalborg University Copenhagen, A.C. Meyers Vænge 15, DK-2450 Copenhagen, Denmark., Alavipanah SK; Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran.
Jazyk: angličtina
Zdroj: Advances in space research : the official journal of the Committee on Space Research (COSPAR) [Adv Space Res] 2023 Jan 01; Vol. 71 (1), pp. 1017-1033. Date of Electronic Publication: 2022 Sep 28.
DOI: 10.1016/j.asr.2022.09.052
Abstrakt: COVID-19 pandemic has had a major impact on our society, environment and public health, in both positive and negative ways. The main aim of this study is to monitor the effect of COVID-19 pandemic lockdowns on urban cooling. To do so, satellite images of Landsat 8 for Milan and Rome in Italy, and Wuhan in China were used to look at pre-lockdown and during the lockdown. First, the surface biophysical characteristics for the pre-lockdown and within-lockdown dates of COVID-19 were calculated. Then, the land surface temperature (LST) retrieved from Landsat thermal data was normalized based on cold pixels LST and statistical parameters of normalized LST (NLST) were calculated. Thereafter, the correlation coefficient (r) between the NLST and index-based built-up index (IBI) was estimated. Finally, the surface urban heat island intensity (SUHII) of different cities on the lockdown and pre-lockdown periods was compared with each other. The mean NLST of built-up lands in Milan (from 7.71 °C to 2.32 °C), Rome (from 5.05 °C to 3.54 °C) and Wuhan (from 3.57 °C to 1.77 °C) decreased during the lockdown dates compared to pre-lockdown dates. The r (absolute value) between NLST and IBI for Milan, Rome and Wuhan decreased from 0.43, 0.41 and 0.16 in the pre-lockdown dates to 0.25, 0.24, and 0.12 during lockdown dates respectively, which shows a large decrease for all cities. Analysis of SUHI for these cities showed that SUHII during the lockdown dates compared to pre-lockdown dates decreased by 0.89 °C, 1.78 °C, and 1.07 °C respectively. The results indicated a high and substantial impact of anthropogenic activities and anthropogenic heat flux (AHF) on the SUHI due to the substantial reduction of huge anthropogenic pressure in cities. Our conclusions draw attention to the contribution of COVID-19 lockdowns (reducing the anthropogenic activities) to creating cooler cities.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2022 COSPAR. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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