Abstract
This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature (LST) with some spectral indices like NDVI, NDWI, NDBI, and NDBaI by using a series of Landsat images for 1991–92, 1995–96, 1999–00, 2004–05, 2009–10, 2014–15, and 2018–19. The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI (0.71) and NDBaI (0.52) while it builds a negative correlation with NDVI (−0.44). The LST-NDWI correlation is insignificant. The best correlation is noticed in the post-monsoon period, while the least correlation is observed in the winter season. This study can support the environmental planning to build a sustainable city under a similar environment.
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