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

2019 2nd International Conference of Green Buildings and Environmental Management

生态环境科学

Fu, Jiaoqi^1 ; Chen, Chao^1 ; Ren, Huazhong^2 ; Zhang, Yuhuan^3 ; Chu, Yanli^4

Marine Science and Technology College, Zhejiang Ocean University, Zhoushan, China^1

Institute of Remote Sensing and GIS, Peking University, Beijing

100871, China^2

Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing

100094, China^3

School of Port and Transportation Engineering, Zhejiang Ocean University, Zhoushan, China^4

关键词: Atmospheric profile;    Atmospheric water vapor;    High quality surface;    High spatial resolution;    Inversion algorithm;    Radiation transfer equations;    Sea surface temperature (SST);    Thermal infrared remote sensing;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/310/3/032067/pdf
DOI  :  10.1088/1755-1315/310/3/032067

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

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.