An Operational Land Surface Temperature Retrieval Methodology for Chinese Second-Generation Huanjing Disaster Monitoring Satellite Data

Abstract

The Chinese second-generationHuanjing disaster monitoring satellite (HJ-2A) was launched on September 27, 2020, and underutilized due to the lack of accurate operational methodologies for land surface temperature (LST) retrieval.In this article, an operational LST retrieval method is proposed to retrieve LSTs from HJ-2A thermal infrared observations. The LST retrieval methodology involves two main steps. The land surface emissivities (LSEs) over all land cover types are obtained with the improved normalized difference vegetation index-based threshold method, and then the LST is retrieved operationally from the adjacent infrared bands.The algorithm coefficients for LST retrieval are from regression analysis of radiative transfer simulations, and LSTs could be retrieved based on thermal images without any additional auxiliary data. The simulation results demonstrated that the root-mean-square errors (RMSEs) of LST retrieval were less than 2.4 K in all subranges, and the minimum RMSE for the two emissivity groups (high- (low-) emissivity group) was 0.16 K (0.20 K) and appeared in the tractable subrange with water vapor content (WVC) varying from 0 to 1.5 g/cm² and view zenith angle (VZA) being 0°. Furthermore, an error analysis was performed, the results showed that the LSE, NEΔT, and atmospheric water vapor uncertainty of 1%, 0.2 K, and 20% caused the LST retrieval errors with 0.88–1.21 K (0.84–1.19 K), 0.1 K (0.09 K), and 0.006 K (0.008 K) for the high- (low-) emissivity group, respectively, with WVC∊[0–1.5] g/cm² and VZA = 0°. Finally, the retrieved LSTs were applied to seven images of the Wuhai, Geermu, Dunhuang, and Baotou sites from January to March and cross validated by the moderate resolution imaging spectroradiometer (MODIS) LST products. From the cross-validated results, it can be found that the RMSEs of the retrieved LSTs and the MODIS LST products were between 2.3 and 3.7 K, and the mean RMSE value was 2.89 K.