This study examines the relationship between air temperature and urban environment indices, mainly focusing on sky view factor (SVF) in Seoul, Korea. We use air temperature data observed from 295 automatic weather stations (AWS) during the day and night in Seoul. We conduct a spatial regression analysis to capture the effect of spatial autocorrelation in our data and identify changes in the effects of SVF on air temperature, while conducting the regression model for each dataset according to the floor area ratio (FAR). The findings of our study indicate that SVF negatively affects air temperature during both day and night when other effects are controlled through spatial regression models. Moreover, we address the environmental indices associated with day-time and night-time air temperatures and identify the changing effects of SVF on air temperature according to the areal floor area ratio of the analysis datasets. This study contributes to the literature on the relationship between SVF and air temperature in high-density cities and suggests policy implications for improving urban thermal environments with regard to urban design and planning.