Urban heat island is one of the most vital environmental risks in urban areas. The advent of remote sensing technology provides better visibility due to the integrated view, low-cost, fast and effective way to study and monitor environmental and humanistic changes. The aim of this study is a spatiotemporal evaluation of land use changes and the heat island in the time period of 1985-2015 for the studied area in the city of Babol. For this purpose, multi-temporal Landsat images were used in this study. For calculating the land surface temperature (LST), single-channel and maximum likelihood algorithms were used, to classify Images. Therefore, land use changes and LST were examined, and thereby the relationship between land-use changes was analyzed with the normalized LST. By using the average and standard deviation of normalized thermal images, the area was divided into five temperature categories, inter alia, very low, low, medium, high and very high and then, the heat island changes in the studied time period were investigated. The results indicate that land use changes for built-up lands increased by 92%, and a noticeable decrease was observed for agricultural lands. The Built-up land changes trend has direct relation with the trend of normalized surface temperature changes. Low and very low-temperature categories which follow a decreasing trend, are related to lands far away from the city. Also, high and very high-temperature categories whose areas increase annually, are adjacent to the city center and exit ways of the town. The results emphasize on the importance of attention of urban planners and managers to the urban heat island as an environmental risk.

Urban heat island is one of the most vital environmental risks in urban areas. The advent of remote sensing technology provides better visibility due to the integrated view, low-cost, fast and effective way to study and monitor environmental changes. The aim of this study is a spatial-temporal evaluation of heat island intensity in the period of 1985-2015 and prediction of heat island intensity variations for the specific studied area in the city of Babol. For this purpose, multi-temporal Landsat images were used in this study. For calculating the land surface temperature, Single channel algorithm were used, and Maximum likelihood algorithm was also utilized to classify Images. Therefore, land use changes and land surface temperatures (LST) were examined, and thereby the relationship between land-use changes was analyzed with the normalized land surface temperature. By using the mean and standard deviation of normalized thermal images, the area was divided into five thermal categories. Then, by applying the heat island intensity index, the heat island changes in the studied period of time was investigated. Land use changes for the future studies was investigated by using Markov model and then, the heat island intensity changes were anticipated. The results indicate that land use changes for built-up lands increased by 92%, and a noticeable decrease was observed for agricultural lands. The Built-up land changes trend has an inverse relation with the trend of FVC and follows the same trend as normalized surface temperature changes. High and very high-temperature categories whose area increases annually, are adjacent to the city core and exit ways of the town. The index ratio of heat island during this period has an increasing trend and the amount of index was altered from 0/5 in 1985 to 0/67 in 2015. Land use changes anticipation and the process of heat island intensity variations for the studied area show alarming results.