The application of Emissivity Estimation to retrieval of land surface temperature from LANDSAT data

Abstract

Land Surface Temperature (LST) is an important component in many fields, including global climate change research, urban land use/land cover, geo-biophysical investigations, and as a vital input for climate models. The objective of this research is to develop image processing method of retrieving land surface temperature from LANDSAT data using ArcGISPro. In this study an attempt has been made to estimate LST over Vavuniya district, Sri Lanka, using LANDSAT 5 TM and LANDSAT 8 (OLI & TIRS) satellite data. Two images taken by Landsat-5 TM and Landsat 8- OLI&TIRS satellites were used as the basic data source. These raw images were taken in 1997, and 2021, respectively. First, the raw images were radiometrically and geometrically corrected within the scope of the research. Then, to determine the dimension of the LST variations, LST and Normalized Difference Vegetation Index (NDVI) maps were produced. The variability of retrieved LSTs has been investigated in relation to NDVI values for various land use/land cover (LU/LC) types determined from the Landsat visible and NIR bands. The difference between retrieved LST and the average temperature data from Meteorological station Vavuniya indicates that the technique works by giving an error of about 0.50C. This proposed method of image processing using ArcGISPro has proved as a dynamic tool to estimate LST using imageries of LANDSAT 5 and LANDSAT 8 and Land surface emissivity. Also, it can be used to understand the impacts of urban development on the environment.