INTRODUCTION: The dearth of data and accurate climate information has made it difficult to study the relationship between human health and climate change. To study the surface heat island in the urban areas, land surface temperature must be calculated, and since no space sensor is capable of frequent thermal imaging at the required spatial resolution for urban studies, this study aimed to propose a method for urban temperature changing characteristics, and provide the results to the city managers and officials in health domains. METHODS: SADFAT temporal and spatial integration model was used to prepare the data. Following that, changes in the spatial and temporal pattern of surface temperature data in Tehran were studied using exploratory methods of spatial data analysis, and the results were evaluated by classical statistical methods (normalization process, classification, and comparison of temperature classes of images). The heat island ratio index was employed to investigate the temporal changes in the intensity of the heat island. FINDINGS: Temporal changes in the ratio of heat island in Tehran during 2017 showed that from the Julian days 1 to 81 (January 12 to April 2), as well as 153 to 281 (June 12 to October 16), the value of the intensity of the heat island in Tehran was higher than the average (about 0.067) due to changes in vegetation, climate, and air pollution, for 210 days in a year. CONCLUSION: The diagram of periodic and irregular fluctuations of thermal islands showed that it was not logical to compare the spatial pattern of thermal islands without considering the time of location. These daily and weekly fluctuations in the intensity of the heat island, as well as the human exposure to it, cause a wide range of diseases, such as hypothermia, heatstroke, as well as cardiovascular and respiratory diseases, which consequently lead to death.
