Retrieval of land surface temperature from FY3D MERSI-II based on re-fitting Split Window Algorithm. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Dejun, Zhang; Shiqi, Yang; Liang, Sun; Xiaoran, Liu; Shihao, Tang; Hao, Zhu; Qinyu, Ye; Xinyu, Zhang
• Is Part Of: European journal of remote sensing. Volume 55:Issue 1(2022)
• Page Start: 1
• Page End: 18
• Publication Date: 2022-12-31
• Subjects: FY3D -- MERSI- II -- split-window -- land surface temperature; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2022.2133016
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: Medium Resolution Spectral Imager II (MERSI-II) is one of the core sensors mounted on the FengYun-3D (FY3D) satellite. Two adjacent 250 m long-wave thermal infrared (TIR) channels provide a considerable opportunity for retrieving Land Surface Temperature (LST) with high spatiotemporal resolution. In this paper, Thermodynamic Initial Guess Retrieval (TIGR) dataset and MODTRAN 4.0 model were used to re-fit the parameters of the Split-Window (SW) algorithm suitable for MERSI-II TIR channels, and then the daily 250 m resolution MERSI-II LST product was retrieved. The Radiance-based (R-based) method results showed that the bias value between L S T s simulated by MODTRAN4.0 and the input L S T t is 0.16 K, and the MAE value is 0.38 K. Inter-comparison method results showed that the MERSI-II LST and MODIS LST products were consistent in spatial distribution, but there were certain differences between MODIS LST and MERSI-II LST at different land cover types. T-based method results showed that R values between the site-observed LST and MERSI-II LST retrieved by SW algorithm exceeded 0.92, the bias value was between 3.6 K and 4.4 K, and the MAE value was between 2.6 K and 4.5 K. The above results indicating that the SW algorithm proposed in this study has good accuracy and applicability.