One of the greatest issues nowadays is that of the urban heat island effect on the thermal conditions inside cities. The air temperature inside the city core is warmer than that in suburbs, thus deteriorating the quality of life for citizens and making outdoor spaces uncomfortable in terms of thermal comfort. This phenomenon is usually assessed in large scale cities worldwide and less often in medium-sized towns. The current study aimed to investigate the urban heat island effect and, therefore, to assess the outdoor thermal comfort conditions in a medium-sized city. More specifically, the methodology of the current study includes: (i) the combination of different monitoring techniques to quantify the urban heat island effect in a medium-sized Mediterranean city. Both in situ measurements and remote sensing techniques were applied to assess the urban heat island effect in terms of both the canopy layer (CUHI) and the surface (SUHI); (ii) the identification of the parameters that affect thermal comfort and the identification of the most appropriate bioclimatic indices that determine outdoor thermal comfort in the city of interest. Both questionnaire survey and in situ measurements took place on a sidewalk in the city of Xanthi, Northern Greece, during the summer. The CUHI effect was obvious, especially in the morning and afternoon. Downscaled MODIS satellite images also showed that the intensity of SUHI was higher in the morning and afternoon. Apart from air temperature, important differences in the values of most microclimatic parameters were recorded between the meteorological station placed inside the urban area and those gathered from a nearby meteorological station. The narrow roads, the thermal properties of construction materials, and the absence of greenery characterized the area of interest and may be the key factors creating these differences in climate. Concerning the thermal comfort assessment, the most significant parameters were the air temperature and solar radiation, although, both empirical and direct indices were found to describe the comfort values well. According to the results, downscaling techniques are also important for the SUHI effect to be investigating in detail in medium-sized urban environments.

The trend of urbanization nowadays has caused serious issues related to climate. One of the most important ones is that of the ‘Urban Heat Island (UHI)’ and it occurs in major cities throughout the world. The most important categories, and therefore the most studied ones, are the canopy urban heat island (CUHI) and surface heat island (SUHI). The aim and the novelty of the current study was to assess different remote sensing approaches to detect the thermal environment of an open area inside a large city. The study was undertaken in an urban area with green spaces, in the Bosco Verticale area in the city of Milan, during the spring and summer period of 2021. The area is characterized by different types of cover materials, which were investigated in terms of surface temperature under shaded and non-shaded conditions. Both field measurements and remote sensing techniques were applied. Remote sensing techniques included downscaling techniques and the usage of different split-window algorithms applied on the Landsat8 satellite sensor data. The land surface temperature (LST) extracted from remote sensing methods was compared with the surface temperature derived from in situ measurements. For the needs of the study, both in situ measurements and the collection of meteorological data from different fixed meteorological stations throughout the city of Milan were carried out. The results revealed the significance of greenery presence inside the urban environment, as a comparison of the meteorological data across the urban area of Milan showed that the areas with a low presence of greenery were found to be warmer than those with a higher presence of green elements. Concerning the field measurements in the study area, the results showed a significant reduction in both surface and air temperature in shaded places. On the other hand, the presence of conventional artificial materials in sunny areas led to relatively high values of both surface and air temperature. The downscaling method showed satisfying results in terms of average LST values; however, some discrepancies appeared in terms of the RMSE index. The application of split-window algorithms has shown that some forms of the ‘Generalized split-window algorithm’ and some forms of the ‘Jimenez-Munoz algorithm’ presented better performance among the studied algorithms. Comparing the LST values derived from the most representative algorithm, the ‘Du, Wan algorithm’, with those derived from downscaling methods, it was found to be quite close. However, under shaded conditions, the results derived from the ‘Split-window algorithm’ were found to be more precise. The application of remote sensing techniques in microscale in urban regions should be further studied in future, as they could be an essential tool for observing microclimatic conditions in urban areas and on building scale.