An Estimation of the Land Surface Temperature, Derived from the Landsat Satellite, for the Major Cities in Sindh Province, Pakistan

Abstract

Thermal infrared remote sensing data are used to make estimates of the land surface temperature (LST) by recording the radiant energy emitted by the surface of the Earth. Satellite data and image processing software also allow for LST estimation. Since its launch, two thermal infrared bands aboard the Landsat satellite have been used to continuously observe Earth, providing data for the estimation of LST and the normalized difference vegetation index (NDVI). Due to the significant uncertainty in data from both Landsat 5 thematic mapper (TM) thermal band 6, which has a wavelength of 10.40–12.50 m, and Landsat 8 thermal infrared sensor (TIRS) Band 11, as indicated by USGS calibration notifications, it was advised to use TIRS Band 10 data as a single spectral band for LST estimation. For LST estimation from Landsat 5 and Landsat 8, the mono-window (MW) approach was used with TM and TIRS Bands 6, 10, and data with a resolution of 120 and 100 m. (Path-152 and Row-40, 41, 42, and 43). The emission coefficient was calculated using the operational land imager (OLI) Bands 4 and 5 (30 m resolution) and the normalized difference vegetation index (NDVI) proportion of vegetation method. Based on the results, the LST was higher in the arid regions, whereas the NDVI was higher in the less arid parts. Also, the LST findings were compared to the air temperature data, both data were found to be consistent with one another. The approach of MW algorithm could be a useful tool for estimating LST from TM data acquired from Landsat 5 and Landsat 8 TIRS Bands 6 and 10.