Correlation analysis of land surface temperature on landsat-8 data of Visakhapatnam Urban Area, Andhra Pradesh, India

The Correlation Analysis was carried out in this study by considering Pearson Correlation Methodology for the Land Surface Temperature (LST). In this different Spectral Indices such as Normalised Difference Urban Index(NDBI), Normalised Difference Vegetation Index(NDVI) and Normalised Difference Water Index (NDWI) were carried out for correlation on Landsat-8 (TIRS and OLI)data of three seasons in one calendar year. The Land Use Land Cover (LULC) classification done following on-screen visual interpretation technique using Sentinel-2A and 2B satellite data for the comparison of LST. The LST variation on LULC depends upon the surface type of the classes. Some classes like the built-up area and the bare land supports the increase of LST where as the Vegetation cover and the water body classes reduce the LST values. It is concluded that the NDBI shows a positive correlation with LST i.e. R 2 = 0.985, 0.986 & 0.973 in January, April and October, 2018 irrespective of the seasons. In case of NDVI and NDWI negative correlation observed i.e., R 2 = 0.940, 0.914, 0.977 and 0.934, 0.886, 0.95 for all three seasons respectively. NDVI reveals a seasonal vegetation effect upon the correlation with LST as we can observe R 2 = 0.914 in summer season. Also the case with NDWI whose R 2 value is strongly correlated when compared to other seasons i.e., 0.977 in the month of October. Study revealing that the scatter plot and the R coefficient played a vital role in examining and retrieving the correlation results. The rising temperature is the causative factor for global warming, vector borne diseases and ecological changes, etc.on Earth. LST can best be studied using different wavelength regions of satellite data products in urban areas for human comforts.