Sea surface temperature retrieval from landsat8 thermal infrared remote sensing data in coastal waters

Abstract

Since the launch of landsat8, high-quality surface observation data have been acquired. But the corresponding sea surface temperature (SST) products have not been seen. Moreover, the existing SST inversion algorithm do not carefully consider the effect of water vapor on the accuracy. In this study, a new method is proposed for the retrieve of SST from Landsat 8 Thermal Infrared Remote Sensing (TIRS) data based on the variation of atmospheric water vapor content. The steps are briefly described as follows: 1) constructing the SST retrieval model of thermal infrared remote sensing by using the radiation transfer equation with atmospheric profile data (air temperature and pressure); 2) retrieving SST of Zhoushan sea area, China from Landsat 8 TIRS Data; 3) evaluating the accuracy of proposed model by simulation data and AVHRR SST product. The bias and RMSE based on the simulation data are within 0.4 K. The bias and RMSE based on AVHRR SST product are 1.6063 K and 1.8507 K, respectively. The results show that the accurate SST with high spatial resolution could be obtained by using the method.