Land Surface Temperature Retrieval from Sentinel-3A Sea and Land Surface Temperature Radiometer, Using a Split-Window Algorithm

Abstract

Land surface temperature (LST) is a crucial parameter in the interaction between the ground and the atmosphere. The Sentinel-3A Sea and Land Surface Temperature Radiometer (SLSTR) provides global daily coverage of day and night observation in the wavelength range of 0.55 to 12.0 μm. LST retrieved from SLSTR is expected to be widely used in different fields of earth surface monitoring. This study aimed to develop a split-window (SW) algorithm to estimate LST from two-channel thermal infrared (TIR) and one-channel middle infrared (MIR) images of SLSTR observation. On the basis of the conventional SW algorithm, using two TIR channels for the daytime observation, the MIR data, with a higher atmospheric transmittance and a lower sensitivity to land surface emissivity, were further used to develop a modified SW algorithm for the nighttime observation. To improve the retrieval accuracy, the algorithm coefficients were obtained in different subranges, according to the view zenith angle, column water vapor, and brightness temperature. The proposed algorithm can theoretically estimate LST with an error lower than 1 K on average. The algorithm was applied to northern China and southern UK, and the retrieved LST captured the surface features for both daytime and nighttime. Finally, ground validation was conducted over seven sites (four in the USA and three in China). Results showed that LST could be estimated with an error mostly within 1.5 to 2.5 K from the algorithm, and the error of the nighttime algorithm involved with MIR data was about 0.5 K lower than the daytime algorithm.

Evaluation of Land Surface Temperature Retrieval from Landsat 8/TIRS Images before and after Stray Light Correction Using the SURFRAD Dataset

“…The CWV was divided into five subranges (0 < CWV ≤ 2.5 g/cm 2 , 2 < CWV ≤ 3.5 g/cm 2 , 3 < CWV ≤ 4.5 g/cm 2 , 4 < CWV ≤ 5.5 g/cm 2 , and CWV > 5.0 g/cm 2 ). This method was also applied on Sentinel-3A [30] and improved by dividing the simulation data into temperature subranges. We refined these algorithm coefficients as Zheng et al [30] did in two ways to make the evaluation more precise.…”

“…This method was also applied on Sentinel-3A [30] and improved by dividing the simulation data into temperature subranges. We refined these algorithm coefficients as Zheng et al [30] did in two ways to make the evaluation more precise. First, the largest difference between the bottom air temperature (T air ) and LST used in the simulation dataset was increased from 20 K in the study of Du et al [14] to 35 K for a barren or desert surface that probably has high surface temperature.…”

Global Sensitivity Analysis of the SCOPE Model in Sentinel-3 Bands: Thermal Domain Focus

“…Both products have been available since 19 April 2016. The calculation of LST from BT is carried out with the modified split-window algorithm for bands S8 and S9 following Equation (4) [60,61]. The algorithm includes atmospheric correction:…”

BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

“…Second, BESS-STAIR in this study uses CDL data which are only available in the United States. Fortunately, BESS does not require specific crop types, but only C 3 /C 4 distributions, and the separation of the major C 4 crop maize from other crops is practical using time-series satellite data (Cai et al, 2018;Zhong et al, 2016). It is noted that misclassification of C 3 and C 4 crops is likely to cause a large bias in GPP but a relatively small bias in ET (Figs.…”