Assessing the effect of covid-19 lockdown on surface urban heat island for different land use /cover types using remote sensing

Abstract

Rapid urbanization significantly affects the near-surface temperature for major cities worldwide. A greater understanding of spatial-temporal changes of the near-surface temperature has given better insights into global issues such as climate change, thermal discomfort, and energy consumption. This remote sensing-based study aims to investigate the spatial-temporal variations of land surface temperature before and after the lockdown, implemented in response to the spread of COVID-19, for three major Indian cities located in different climate zones viz., i) New Delhi (inland), ii) Hyderabad (inland), and iii) Mumbai (coastal). The land surface temperature variation is assessed for 2015-2020 on different land cover types, i.e., buildings, barren land, roads, vegetation, and water. Landsat 8 OLI/TIRS images are employed to classify land use/cover types using Normalized Difference Vegetation Index, Normalized Difference Built-up Index, and Land Surface Temperature maps. Results show that for New Delhi, Hyderabad, and Mumbai, the mean land surface temperature decreases by 5°C, 1.9°C, and 0.26°C, respectively, in April 2020 (after lockdown) in comparison with April 2019. Results for Mumbai do not vary significantly compared to the other two cities. Overall, the performed analysis presents evidence of the impact produced by the COVID-19 lockdown on the surface urban heat island for different land use/cover types.

Keywords

• Built environment
• COVID-19 pandemic
• Land surface temperature (LST)
• Satellite imagery
• Urban overheating
• India