Research on Retrieving Landsat8 Sea Surface Temperature Based on Neutral Regression Equations

Abstract

To verify the feasibility of applying Neutral Regression Equations to retrieve Landsat8 sea surface temperature (SST), and compares the retrieval accuracy and difference of the two thermal infrared bands, this paper establishes Neutral Regression Equations based on 32 MODIS SST training points, and uses buoy SST and MODIS SST to validate and compare the retrieval results. The results show that the Landsat8 SST retrieved by these Equations has high accuracy and good consistency with MODIS SST. Buoy SST verification shows that the root mean square error (rmse) of the two bands is less than 0.5°C, and the deviations range is less than 1°C; MODIS SST verification shows that the mean deviation(bias) of the 10th and 11th bands are -0.16°C and -0.22°C, respectively, and their deviations range is basically within ± 1°C; the retrieval accuracy of the 10th band is higher than that of the 11th band. Using Neutral Regression Equations to monitor the thermal discharge from Houshi Power Plant has achieved a wonderful effect, the temperature rise plume is jet-like, and affects a large range with a total area of 1.88km2 and a maximum thermal pollution distance of 2.5km.