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The study focuses on evaluating the relationship between land surface temperature (LST) with four land use/land cover (LULC) indices (MNDWI, NDBaI, NDBI, and NDVI) in Hyderabad City of India using four Landsat 8 data from the winter season of 2020–21. Pearson’s linear correlation coefficient method is applied in determining the correlation analysis. The results represent a stable status of the indices in the winter season as the range of the mean is significantly low (0.04 for MNDWI, 0.04 for NDBaI, 0.02 for NDBI, and 0.05 for NDVI). All the LULC indices are very stable with each other. Moreover, these indices also build a stable relationship with LST. The indices respond differently to the change of LST. LST builds a neutral relationship with NDVI (average r = −0.07), a moderate negative relationship with MNDWI (average r = −0.57), and a moderate positive relationship with NDBaI (average r = 0.48) and NDBI (average r = 0.55). The dry winter season affects the vegetation life and generates a neutral relationship between LST and NDVI. Built-up and bare land surfaces enhance the LST while water surface reduces the LST. The study is suitable for a stable land use planning system.
Guha et al. (Mon,) studied this question.