Abstract
Urban Heat Island effects is mainly caused by differences in urban and rural thermal behavior associated with differences in artificial heat, air pollution, urban density, and population density emitted by urban heat and urban geometry. This phenomenon appears to be prominent in the rapidly urbanized cities and is an important variable for the study of urban microclimate due to climate change. In this paper was collected climate data from 54 locations of Automatic weather station in 2014 and collected urban geometry data such as land cover data to understand climate change and urban heat island intensity (UHI) in Seoul. And based on these collected data, developed a deep learning prediction model to predict urban heat island intensity and analyze the effect of urban geometry on urban heat island effects.
