Assessment of Land Surface Temperature from the Indian Cities of Ranchi and Dhanbad during COVID-19 Lockdown: Implications on the Urban Climatology

Abstract

An apparent increase in average global temperature is evident globally, and India is no exception. With the recent decade (2011–2020) arguably being the warmest, significant challenges due to rapid climate change have gained attention. However, notable spatial-temporal changes, especially with regard to land surface temperature (LST), were observed during the COVID-19 pandemic lockdown period, when a comparatively cooler climate was experienced in many urban centers. Assessment of LST, crucial in many heat-balance, land use, and climate change models research studies, depicts the near-surface hotness of the Earth’s temperature at a given location. Thus, this study utilizes satellite remote-sensing data to investigate the spatial-temporal variations of LST pre and post-lockdown imposed during the COVID-19 outbreak. Unlike many existing research studies on the metropolitans of India, the study considers developing Indian cities, Ranchi and Dhanbad, as its study area. Accurate LST computation was performed using existing LANDSAT-8 OLI/TIRS images and judged using other parameters (NDVI, LSE) obtained directly from the thermal infrared bands. The LST assessment successfully estimated temperature variations in Ranchi and Dhanbad, depicting a significant drop in temperature coinciding with the lockdown period and subsequent increase in urban temperature post-pandemic, indicating a meaningful relationship between human activities and urban surface temperature.

Investigating Surface Urban Heat Island (SUHI) Effect for a Hill City

“…Lower LST during Covid-19 period signifies that the anthropogenic activity is correlated to LST. The year 2022 became the hottest year for Ranchi when mercury rose to 44.5°C in the urban centres (Qadri et al, 2023). For a single day observation and inference from satellite data, areas with industrial activities, mining sites, urban settlements, and agricultural lands consistently exhibit higher temperatures, while waterbodies and vegetation consistently display lower temperatures throughout the entire area of Ranchi (Rengma & Yadav, 2024).…”

Land Surface Temperature and Thermal Comfort in the Cities of Punjab, India: Assessment Based on Remote Sensing Data

“…Table 1 shows the specifications of the data used in this study. https://www.indjst.org/ NDVI (Normalized Difference Vegetation Index) is a useful method to extract vegetation cover information from the land surface (15) . Theoretically, the value of NDVI ranges from -1 to +1, where negative values indicate water features; the 0 value indicates bare soil while the positive value indicates vegetation cover.…”