Cologically stressed zones. In a different study, Bokaie et al. [27] MK-2206 Epigenetic Reader Domain employed Landsat Thematic Mapper (TM) information to map the SUHIs of Tehran in 2010 and investigate its relationship together with the Land Use/Land Cover (LULC) map and Normalized Distinction Vegetation Index (NDVI) image. They reported complete compliance in between typical LST values and LULC classes as well as a moderate unfavorable correlation involving LST and NDVI values, which was also in accordance with other research [28]. Likewise, several other scholars incorporated multi-temporal remote sensing information to map the spatio-temporal variability of SUHI patterns [291]. By way of example, de Faria Peres et al. [32] explored the trend of SUHI evolution over 30 years and compared the results with LULC maps. The outcomes recommended that the key cause for the 2 C rise of SUHI intensity in Rio de Janeiro was related with urban expansion because of the significant development of LST in urban areas. Moreover, Nadizadeh Shorabeh et al. [33] employed 5 Landsat images involving 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 definitely the biggest and most populated metropolitan in Iran, and as the central hub (i.e., political, economic, social) in the country, it has skilled huge population growth and substantial urbanization [34]. Quite a few research had been carried out to study and monitor SUHI and LST variations throughout the city [351]. Even so, the SUHIs were nevertheless extracted by a single image in these studies, to ensure that they could not be regarded as as a thorough description of U0126 Technical Information annual or seasonal SUHI. This can be for the reason that Using timeseries remote sensing images produces a more detailed and persuasive understanding from the complexity of SUHI in comparison with analyzing this phenomenon with limited images [42,43]. Additionally, the thermal environmental situation of Tehran has not been analyzed in preceding research. To the finest of our knowledge, no comprehensive study was dedicated to investigating three decades of SUHI and UTFVI patterns in Tehran by means of time-series data. In addition, Tehran is struggling with severe air pollution [44], and thus, itRemote Sens. 2021, 13,3 ofis needed to appraise the relationship in between air pollutants and SUHI intensities, which has not been performed in Tehran. Actually, the contradictory reports from the connection amongst air pollutants and SUHI intensities in various areas necessitate performing these analyses for Tehran [458]. These investigations would deliver profound info in regards to the environmental condition of Tehran, major to helpful decision-making to get a sustainable city. Contemplating the foregoing, this paper aims to extend previous studies and supply relevant details from new elements by investigating the spatio-temporal variability of SUHI and thermal comfort and appraising the relationship of SUHI intensities and air pollutant concentrations in Tehran. Especially, the present study follows 3 objectives: (1) Investigating the SUHI adjustments more than the past three decades and examining its intraannual variations, delivering the SUHI magnitudes and footprints; (two) exploring the spatial alterations of the environmental condition of Tehran more than the final three decades employing the UTFVI; and (3) identifying the connection amongst SUHI intensities and various air pollutants concentration for Teh.
