###### Abstract
For example, research indicates that one of the thermal effects of vehicles is the substitution of atmospheric downwelling infrared radiation (IR) with IR emissions from the underside of the vehicle. Of particular significance are the IR emissions from the heated engine, transmission, and exhaust system directed towards the road surface [15; 16; 17]. Regarding land area, [PERSON] et al. [18], analyzed 5000 cities and determined that city size has the strongest influence on the intensity of the SUHI; larger, more compact, and less sprawled cities tend to exhibit stronger SUHI effects. In Europe, the intensity of UHIs in urban agglomerations shows a size dependency, typically reaching a maximum of approximately 3 \({}^{\circ}\)C in summer and 0.5 \({}^{\circ}\)C in winter [19]. Population density, built density, and vegetation can also directly or indirectly contribute to the formation of SUHIs [20]. A study analyzing 65 cities in North America found that the average annual daytime and nighttime UHI are positively correlated with precipitation and the logarithm of the population, respectively [21]. Research conducted in five cities in Bangladesh, utilizing the LST, determined that the SUHI effect is higher during the day than at night, with a long-term increasing trend [22]. The construction materials used in facades, roofs, and pavements play a vital role in the thermal balance of cities. Pavements predominantly absorb shortwave solar radiation during the day and, depending on their temperature, re-emit longwave radiation into the atmosphere [4]. This process causes the increase in air temperature near the surface during the day to be mainly attributable to turbulent sensible heat flux, specifically through the divergence of said flux. Attention has been paid to albedo in urban construction, as areas with a higher reflectance index, such as reflective permeable surfaces and reflective pavements, present potential strategies for UHI mitigation [23]. A study in Xi'an, the largest city in northwestern China, found that the density of impervious surfaces had a more significant impact on the LST than green space, with a Pearson correlation coefficient ranging from 0.59 to 0.97 [8]. Similarly, in Turin, Italy's largest metropolitan area, it was calculated that, for every 10% increase in highly impervious surfaces with low tree cover in the metropolitan core, the SUHI increased by 4.0 \({}^{\circ}\)C [24]. The loss of soil moisture through direct evaporation and transpiration from vegetation is crucial to the modification of surface temperatures [25]. Changes in vegetation density, height, and surface coverage directly affect the soil surface temperature [26]. The presence of vegetation in urban areas reduces temperatures through evapotranspiration and shading, while paved areas contribute to increased temperatures through radiation heat transfer to the urban atmosphere [27] Using thermal remote sensing, the Normalized Difference Vegetation Index (NDVI) can be calculated from spectrometric data collected in two specific bands: red and near-infrared, which assesses vegetation quality values ranging from \(-1\) to \(1\). This index has been applied in urban planning to estimate the active photosynthetic biomass density and its impact on normalized urban temperatures [28]. This study utilizes satellite remote sensing methodology to analyze land surface temperature (LST) in seven coastal cities over two days--one in July 2019 and the other in July 2020--focusing on local and spatial temperature variations during the daytime. These cities are located between 18\({}^{\circ}\) and 22\({}^{\circ}\) latitude and 106\({}^{\circ}\) and 91\({}^{\circ}\) longitude. Variables such as the land area, population, types of pavements, vegetation, and anthropogenic activities, including mobility, are examined in terms of their impact on the LST. This research highlights how human behavior influences urban climate, which is crucial for urban planning and environmental management.