Land surface temperature retrieval from Landsat-8 data

Abstract

This work presents Land Surface Temperature (LST) retrieval from Landsat-8 data using the Generalized Split-Window (GSW) algorithm. First, radiative transfer modeling experiments were conducted using the moderate spectral resolution atmospheric transmittance algorithm and computer model (MODTRAN) 4.0 fed with SeeBor V5.0 atmospheric profile database to simulate the brightness temperatures in Thermal InfraRed Sensor (TIRS) bands 10 (centered at 10.9 μm) and 11 (centered at 12.0 μm) related to Land Surface Emissivities (LSEs) and Total Precipitable Water (TPW). Then, the unknown coefficients of the GSW algorithm were obtained through multi-variable regressions, in which the simulated data were grouped into several subranges to improve fitting accuracy. Next, LSTs were derived from the clear-sky TIRS/Landsat-8 data in 2015, where LSEs were estimated from Operational Land Imager (OLI) measurements using the Normalized Difference Vegetation Index (NDVI) Based Emissivity Method (NBEM), and TPWs were extracted from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data. Finally, the derived LSTs were validated with MOD11_L2 V5 product. The results show that the GSW algorithm developed in this work can accurately retrieve LST from the Landsat-8 data, and the relative error is 0.18±0.68 K against the MOD11_L2 V5 product.