Urbanization has created significant changes in the environment compared to natural conditions, as a result of these changes various microclimates form in urban areas. In order to determine water requirement of urban green spaces, it is necessary to estimate vegetation evapotrairation influenced by urban microclimates. The main objective of this study is to compare and evaluate evapotrairation across Isfahan city and non-urban areas. This study was conducted in two different periods. In the first period, 2010-2014, air temperature and relative humidity were measured in five different sites and in the second period, 2018-2020, air temperature, relative humidity, wind speed, air pressure and rainfall were measured in three different sites across the city of Isfahan. In addition, weather data were obtained from weather stations installed surrounding the city (ISFN) in the same period. Reference evapotrairation was computed using seven different equations for urban and non-urban sites. Using 23 Landsat 8 images, the land surface temperature was retrieved using single-channel algorithm and evapotrairation was estimated using SEBAL algorithm. The results for the first timespan showed that the Valiantzas equation had the best performance with the highest coefficient of correlation and the lowest error in both ISFN (RMSE = 0.47 mm/day, MBE = 0.31 mm/day, R2 = 0.98) and AP (RMSE = 0.29 mm/day, MBE = 0.05 mm/day, R2 = 0.98). The results for the second period indicated that wind speed measured at urban sites was significantly lower than the non-urban site. The daily data set of ET 0 was statistically significantly different at the 0.05 significance level when compared between STN1 (an urban park) and ISFN from March to October. But there were no statistically significant differences in daily ET 0 between STN2 (installed next to a highway and street) and ISFN. Air temperature and wind speed were dominant drivers of ET 0 in all sites. The maximum ET 0 difference between ISFN and STN1 was 4.4 mm/day that was observed in July. Accumulated ET 0 in STN1 was 20.9% lower than in ISFN and in STN2 was 7.6% lower than the accumulated ET 0 in ISFN. In other words, the amount of water to irrigate 1 m 2 green space in STN1 was 248.3 liters and in STN2 was 90.5 liters less than the amount of water to irrigate 1 m 2 green space in ISFN during 215 consecutive days, which shows using climatic data measured at weather stations located in urban surrounding open space areas to compute ET 0 in urban environments could lead to over-irrigation in urban green spaces. Monthly microclimate coefficient (ET 0 ) in STN1 was lower in hot months than cold months and varied between 0.77 to 0.99. In STN2, monthly microclimate coefficient (ET 0 ) varied between 0.92 to 1.04 and was lower than 1 in all months of the year (except in December, January and February). The urban cool island was observed in STN1 during summer, while STN2 was recognized as a urban heat island (UHI) during all seasons in Isfahan city. A significant correlation was observed between UHI and ET 0 . In STN1 an increase in UHI intensity resulted in decreasing ET 0 , while in STN2 an increase in UHI intensity led to increasing ET 0 . The surface urban heat island (SUHI) intensity was always less than zero in STN1 and STN2 that shows forming a surface urban cool island. Comparing ET estimated by SEBAL algorithm and landscape ET in STN1 showed that SEBAL has good accuracy to estimate ET in a large and continuous urban park (RMSE=0.67 mm/day, MBE= 0.43 mm/day, while SEBAL algorithm cannot be used to estimate ET in small and scattered urban green spaces. The results of this study indicate the necessity of accurate estimation of ET in urban areas, considering the importance of urban microclimates, in order to water resource management and urban green space development. Key Words Microclimate coefficient, Landscape water requirement, Land use, SEBAL algorithm, Urban heat island.