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The main purpose of this study is to monitor the impacts of seasonal urban heat island based on the relationship between seasonal land surface temperature and Land Use/ Cover (LU/LC) fluctuations in Kabul city, the capital of Afghanistan in 2020.To do this, areas affected by Urban Heat Island (UHI) were detected. The relationship between UHI spatiotemporal fluctuations and LULC classes was also evaluated. The composition of Synthetic Aperture Radar (SAR) and optical Landsat 8 OLI images were used to extract the LU/LC type of the study area with higher accuracy for all seasons. Random forest supervised classifier was used to classify Kabul city into four different LU/LC classes (vegetation, water body, built-up, and bare land). Landsat 8 thermal bands were used to derive land surface temperature (LST) change patterns. The outputs revealed that the UHIs created in Kabul city have distinct causes depending on the type of LU/LC classes. The mean land surface temperature of the four LU/LC classes in different seasons demonstrated that the distribution mode of UHIs in the city was in line with the type of LU/LC. Based on overall assessments, the results revealed that nine districts in Kabul city (D-19, D-15, D-21, D-16, D-20, D-17, D-6, D-9, and D-1) are highly affected by urban heat islands. The UHIaffected regions in Kabul city, mostly consist of industrial parks, factories, the airport, industrial complexes, brick kilns, high volume of daily traffic congestion, densely populated, crush plant stations, and residential settlements. To validate the results, daytime and nighttime MODIS LST maps were generated. The daytime LST map similarly demonstrated that the spatial distribution of UHIs is related to the types of LU/LC. On the other hand, the results from nighttime LST maps revealed that nighttime heat islands are more intense than daytime heat islands, with the main concentrations of UHIs spreading towards the most populated areas in the central and eastern portion of Kabul city. This is due to the absorption of solar radiation throughout the day and emission during the nighttime. Remote sensing techniques were shown to be productive and economic, particularly in terms of minimizing the time for the evaluation of urban heat island variations based on the relationship between land surface temperature and LU/LC changes. Precise and updated remote sensing assessments of UHIs will pave the way for urban planners and land management organizations in addressing challenges related to the phenomenon. [ABSTRACT FROM AUTHOR]