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.

中文翻译：

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调查 COVID-19 期间封锁对地表温度的影响：印度德拉敦市的研究

城市环境因其建筑环境的动力学和热力学特性而带来挑战。本研究旨在研究 COVID-19 期间封锁对德拉敦市时空地表温度 (LST) 模式的影响。下载了 2020 年 4 月 14 日（锁定后）、2019 年 4 月 28 日、2018 年 4 月 25 日和 2017 年 5 月 8 日的 TIRS 传感器数据，并使用辐射传输方程检索了 LST。LST、城市热点和热舒适度的病房变化作为建筑密度的函数进行了研究。据观察，在 COVID 后封锁期间，德拉敦市的 LST 值总体下降。建筑密度高的病房LST下降幅度最小；反之，开放空间比例大的病房，中等建筑密度的 LST 下降幅度最大。使用Getis Ord GI*统计量进行热点分析，使用城市热场方差指数确定热舒适度。据观察，在封锁后，热点数量增加，同时热舒适度下降。本研究中提出的方法可以应用于表现出类似增长模式的其他印度城市，并将为理性决策提供工具。