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Abstract:
Unprecedented infrastructure creation and unchecked migration from rural areas have caused considerable warming of Dehradun’s urban environment. Estimating the distribution of high and low surface temperature (ST) and thermal comfort level (TCL) clusters over space and time through satellite-derived measurements is needed to formulate a heat mitigation strategy for the long-term sustenance of the rapid development of this northwestern Himalayan city. Thirty-one cloud-free Landsat-5 and 8 images have been used herein to retrieve ST for winter, summer, monsoon and post-monsoon seasons of 1991, 1998, 2008 and 2018. Using the Anselin Local Moran's I and optimized Getis-Ord GI* statistics, ST hotspots and coldspots have been determined, whereas land surface temperature variation index (LSTVI) has been used to estimate the TCL. Findings indicate an increase of over 9 °C in the average ST per season during these twenty-seven years. The number of hotspots and the area under them has increased consistently from 1991 to 2018. Predominant in the city core, these hotspots have spread with the city’s southward expansion in the southwest-southest direction, while coldspots are retained in the isolated densely vegetated pockets of the north, west and east. A seasonal impact on the ST’s intensity is evident in the hotspots and coldspots with extremes in summer and winter. LSTVI categorization puts more than 50% of the city area under worst TCL conditions, with a continuous areal increment in the considered timeframe. These observations necessitate immediate overhauling of recent policies on developmental activities in the identified areas to prevent future hydroclimatological disasters.
