Land Surface Temperature Retrieval from LANDSAT data using Emissivity Estimation

Land surface temperature (LST) is an essential factor in many areas like global climate change studies, urban land use/land cover, geo-/biophysical and also a key input for climate models. LANDSAT 8, the latest satellite from LANDSAT series, has given lot of possibilities to study the land processes using remote sensing. In this study an attempt has been made to estimate LST over Chittoor district, Andhra Pradesh, India, using LANDSAT 8 – Operational Line Imager & Thermal Infrared Sensor (OLI & TIRS) satellite data. The variability of retrieved LSTs has been investigated with respect to Normalized Difference Vegetation Index (NDVI) values for different land use/land cover (LU/LC) types determined from the Landsat visible and NIR channels. The Land Surface Emissivity (LSE) values needed in order to apply the method have been estimated from a procedure that uses the visible and near infrared bands. The present study focuses on developing an ERDAS IMAGINE image processing method using the LANDSAT 8 thermal imagery of band 10 data. The difference between retrieved LST and Automatic Weather Station (AWS) data indicates that the technique works by giving an error of ±3C.