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      Investigating the Effect of Lockdown During COVID-19 on Land Surface Temperature: Study of Dehradun City, India

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          Abstract

          Urban environment imposes challenges due to its dynamics and thermodynamic characteristics of the built environment. The present study aims to study the effect of lockdown during COVID-19 on the spatio-temporal land surface temperature (LST) patterns in Dehradun city. The TIRS sensor data of 14 April 2020 (post-lockdown), 28 April 2019, 25 April 2018 and 08 May 2017 were downloaded, and LST was retrieved using radiative transfer equation. The wardwise change in LST, urban hot spots and thermal comfort was studied as a function of built-up density. It was observed that there was an overall decrease in LST values in Dehradun city in post-COVID lockdown period. Wards with high built-up density had minimum decrease in LST; on the contrary, wards with large proportion of open spaces and having low, medium built-up density had the maximum decrease in LST. Hot spot analysis was carried out using Getis Ord GI* statistic, and the level of thermal comfort was found using the urban thermal field variance index. It was observed that there was an increase in number of hot spots accompanied by a decrease in thermal comfort level post-lockdown. The methodology proposed in the present study can be applied to other Indian cities which exhibit similar growth patterns and will provide a tool for rational decision making.

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          The energetic basis of the urban heat island

          T. Oke (1982)
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            Effect of restricted emissions during COVID-19 on air quality in India

            The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM10, PM2.5, CO, NO2, ozone and SO2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM2.5, PM10, CO, and NO2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O3 and negligible changes in SO2. The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by ~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented.
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              Land surface temperature retrieval from LANDSAT TM 5

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                Author and article information

                Contributors
                maithanis99@gmail.com
                garimanautiyal065@gmail.com
                doonarchana@gmail.com
                Journal
                J Indian Soc Remote Sens
                Journal of the Indian Society of Remote Sensing
                Springer India (New Delhi )
                0255-660X
                0974-3006
                5 September 2020
                : 1-15
                Affiliations
                [1 ]GRID grid.466780.b, ISNI 0000 0001 2225 2071, Urban and Regional Studies Department, , Indian Institute of Remote Sensing, ; Dehradun, India
                [2 ]GRID grid.449113.a, ISNI 0000 0004 1774 1235, School of Environment and Natural Resources, , Doon University, ; Dehradun, India
                Author information
                http://orcid.org/0000-0002-3395-886X
                Article
                1157
                10.1007/s12524-020-01157-w
                7473830
                cf98fee6-a112-4938-834f-3c8f6c98a5b3
                © Indian Society of Remote Sensing 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 30 June 2020
                : 24 August 2020
                Categories
                Research Article

                land surface temperature,thermal infrared sensor,radiative transfer equation,hot spot,land surface emissivity,urban thermal field variance index

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