Study On Sea Surface Temperature Retrieval From Landsat 8 Thermal Infrared Remote Sensing Data

Sea surface temperature(SST)is an important marine environmental parameter to reflect the state of marine thermal radiation.It plays an important role in studying the air-sea interaction and describing the state of marine structure.Extracting information from thermal infrared remote sensing data is a common method to retrieve SST.However,atmospheric water vapor has a significant attenuation effect on thermal infrared information,which will reduce the accuracy of SST inversion.And the effect of atmospheric water vapor on the inversion accuracy is not considered carefully in the existing SST inversion algorithm.In this study,a new method is proposed for retrieving SST from Landsat 8 Thermal Infrared Remote Sensing(TIRS)data based on the variation of atmospheric water vapor content(WVC).The sea area near Zhoushan,Zhejiang was taken as the research area to carry out the verification experiment.The study can be divided into three parts:(1)Constructing the SST retrieval model of thermal infrared remote sensing based on WVC by using the principle of the split window algorithm.In order to study the influence of water vapor on the accuracy of SST inversion,the study also proposed an SST inversion method without considering the variation of atmospheric WVC.The simulated data are used to compare the inversion accuracy of the two split window algorithms.The results show that the root mean square error(RMSE)of the algorithm with WVC is 0.3961 K,which is smaller than the RMSE of the algorithm without WVC.It shows that the method proposed in the paper can improve the accuracy of SST retrieval by using split window algorithm.(2)Analyzing the accuracy of SST retrieval model based on the AVHRR SST products.The results show that the average bias and RMSE of the inversion results of the algorithm considering WVC are smaller than the results without considering WVC.It shows that the algorithm proposed in this study has improved results compared with the previous split window algorithm which does not consider the change of water vapor.(3)The Landsat 8 SST inversion process is compiled by IDL and the ENVI function is extended.The results show that the Landsat 8 SST inversion module can stably and efficiently retrieve SST,and the spatial resolution of the inversion results is consistent with the original image.In this study,a SST inversion model is developed based on the variation of WVC.The model can not only improve the accuracy of SST inversion,but also improve the operational level of SST inversion.