Land surface temperature analysis in densely populated zones from the perspective of spectral indices and urban morphology

There is a relationship between spectral indices, urban morphology, and spatial patterns with land surface temperature (LST). In this paper, LST and spectral indices in Tehran have been calculated using Landsat satellite images from 2000 to 2019. LST was improved and the results were evaluated using synoptic stations in Tehran. Pearson correlation coefficient and mean root error are used to evaluate the accuracy of temperature difference. The spatial variables affecting LST are examined including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Digital Elevation Model (DEM), Building Density (BD), and Road Density (RD). The rise in the temperature of the land surface temperature, which causes the formation of heat islands, is continuously increasing over time and can be seen in some parts of the city. The findings indicate that LST relative accuracy was 0.98 and the root-mean-square error is 2.65 °C. The distance pattern based on the Pearson correlation test showed an effective relationship between LST and the examined indicators. Spots prone to heat islands were identified. Each of the heat island areas of Tehran was studied according to population centers (dense areas using residential, commercial, and industrial lands). The built-up and barren areas index had the highest correlation with surface temperature in most areas. The results showed that regions 9, 13, 18, 21, and especially region 22, which has the most barren land, have the highest surface temperature compared to the surrounding areas. The findings of this study can be used in future urban planning and policy-making.