Investigating effects of land use and land cover patterns on land surface temperature using landscape metrics in the city of Tehran, Iran

Tehran, the capital of Iran, is the most densely populated city in the country that has been experiencing extensive population growth and urban expansion in the last decades. The land use/cover (LULC) patterns have noticeably been changed to impervious surfaces that led to the changes in the thermal condition and forming heat islands in Tehran. In this study, the relationship of LULC patterns with land surface temperature (LST) was investigated using landscape metrics in the city of Tehran. For this aim, the LULC map of the year 2012 was derived from Landsat 7 images. The spectral mixture analysis (SMA) and proximity likelihood algorithm were used to classify the LULC map. Then, the LST zoning map was produced from the thermal sensor band and was classified based on standard deviation and quartile deviation methods. Finally, the landscape metrics applied to analyze the relationship between the LULC patterns and LST zones. The results showed that the LST had a positive correlation with the impervious surface fraction but negatively correlated with the green vegetation fraction. The result also indicated that the temperature decreased with an increase in landscape percent and mean patch size of green spaces. The findings of this study could be useful for urban plans, land use planning, and sustainable development goals programs.