A Long-Term Analysis of the Dependency of Land Surface Temperature on Land Surface Indexes

Abstract

This study attempted to analyze the long-term dependency of land surface temperature (LST) on four land surface indexes—namely modified normalized difference water index (MNDWI), normalized difference bareness index (NDBaI), normalized difference built-up index (NDBI), and normalized difference vegetation index (NDVI)—in Imphal City, India, using the summer and winter Landsat satellite data for 1991, 1996, 2001, 2006, 2011, 2016, and 2021. These land surface indexes have a different response to LST variation in the city. The results show that the LST–NDVI correlation (r = –0.40 in summer, −0.36 in winter) and LST–MNDWI correlation (r = –0.31 in summer, −0.51 in winter) are moderately negative. In contrast, the LST–NDBaI correlation (r = 0.38 in summer, 0.49 in winter) and LST–NDBI correlation (r = 0.56 in summer, 0.69 in winter) are moderately positive. The correlation is less variable in winter. A gradually increasing trend is observed in the winter correlation, whereas the summer image does not have the same type of relationship trend. The study reflects an application of remote sensing on land surface features.

Keywords:

• Land surface temperature
• modified normalized difference water index
• normalized difference bareness index
• normalized difference built-up index
• normalized difference vegetation index

Acknowledgments

The authors are indebted to the U.S. Geological Survey (USGS).

Data availability statement

The data that support the findings of this study are openly available on the USGS Earth Explorer Web site at https://earthexplorer.usgs.gov/.