Sea surface temperature extraction and spatial distribution pattern based on long time series MODIS remote sensing data

Sea surface temperature is one of very important environmental parameters. Clear and cloudless MODIS data during each month in 2010 were taken as data sources. Pre-processions such as bowtie correction, geometric correction, and image resize were performed accordingly. Then, spatial distribution information of sea surface temperature in every month, 2010 was extracted by applying nonlinear sea surface temperature (NLSST) algorithm. Pixel temperatures in warm drainage region of Tianwan nuclear power plant were noted in detail. Research results were indicated that sea surface temperature from offshore to sea decreased gradually during the time ranging from March to September. Whereas, the spatial distribution pattern of sea surface temperature during the time ranging from October to February was oppositional. In addition, pixel temperatures in warm drainage region of Tianwan nuclear power plant were generally higher than average temperature. The research would be of reference significance for further discussing the extent of thermal pollution.