Cologically stressed zones. In yet another study, Bokaie et al. [27] employed Landsat Thematic Mapper (TM) information to map the SUHIs of Tehran in 2010 and investigate its partnership together with the Land Use/Land Cover (LULC) map and Normalized Distinction Vegetation Index (NDVI) image. They reported full compliance involving average LST values and LULC Rilmenidine-d4 In stock classes in addition to a moderate unfavorable correlation between LST and NDVI values, which was also in accordance with other studies [28]. Likewise, quite a few other scholars incorporated multi-temporal remote sensing data to map the spatio-temporal variability of SUHI patterns [291]. For example, de Faria Peres et al. [32] explored the trend of SUHI evolution more than 30 years and compared the results with LULC maps. The results suggested that the main explanation for the two C rise of SUHI intensity in Rio de Janeiro was associated with urban expansion because of the considerable growth of LST in urban places. On top of that, Nadizadeh Shorabeh et al. [33] employed 5 Landsat photos in between 1985 and 2017 to study the SUHI variations in Tehran. Later, they applied the Cellular Automata-Markov (CA-M) and Artificial Neural Networks (ANN) model to predict the LULC of 2033 to model the future surface SUHI intensity. Tehran is the largest and most populated metropolitan in Iran, and because the central hub (i.e., political, economic, social) from the nation, it has experienced huge population development and substantial urbanization [34]. Various research were carried out to study and monitor SUHI and LST variations all through the city [351]. Even so, the SUHIs have been nevertheless extracted by a single image in these research, to ensure that they couldn’t be considered as a thorough description of annual or Lumasiran medchemexpress seasonal SUHI. This really is mainly because Using timeseries remote sensing pictures produces a more detailed and persuasive understanding from the complexity of SUHI in comparison with analyzing this phenomenon with limited images [42,43]. Furthermore, the thermal environmental condition of Tehran has not been analyzed in preceding studies. For the most effective of our know-how, no comprehensive study was dedicated to investigating three decades of SUHI and UTFVI patterns in Tehran through time-series information. Additionally, Tehran is affected by serious air pollution [44], and thus, itRemote Sens. 2021, 13,3 ofis essential to appraise the relationship in between air pollutants and SUHI intensities, which has not been performed in Tehran. In truth, the contradictory reports of the partnership between air pollutants and SUHI intensities in distinctive places necessitate performing these analyses for Tehran [458]. These investigations would present profound facts concerning the environmental situation of Tehran, leading to effective decision-making for a sustainable city. Taking into consideration the foregoing, this paper aims to extend previous studies and offer relevant data from new elements by investigating the spatio-temporal variability of SUHI and thermal comfort and appraising the connection of SUHI intensities and air pollutant concentrations in Tehran. Particularly, the present study follows 3 objectives: (1) Investigating the SUHI adjustments more than the previous three decades and examining its intraannual variations, offering the SUHI magnitudes and footprints; (two) exploring the spatial adjustments with the environmental condition of Tehran over the final 3 decades making use of the UTFVI; and (three) identifying the connection between SUHI intensities and distinctive air pollutants concentration for Teh.
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