Merging of multi-temporal SST data at South China Sea

Abstract

The sea surface temperature (SST) mapping could be performed with a wide spatial and temporal extent in a reasonable time limit. The space-borne sensor of AVHRR was widely used for the purpose. However, the current SST retrieval techniques for infrared channels were limited only for the cloud-free area, because the electromagnetic waves in the infrared wavelengths could not penetrate the cloud. Therefore, the SST availability was low for the single image. To overcome this problem, we studied to produce the composite of three day's SST map. The diurnal changes of SST data are quite stable through a short period of time if no abrupt natural disaster occurrence. Therefore, the SST data of three consecutive days with nearly coincident daily time were merged in order to create a three day's composite SST data. The composite image could increase the SST availability. In this study, we acquired the level 1b AVHRR (Advanced Very High Resolution Radiometer) images from Malaysia Center of Remote Sensing (MACRES). The images were first preprocessed and the cloud and land areas were masked. We made some modifications on the technique of obtaining the threshold value for cloud masking. The SST was estimated by using the day split MCSST algorithm. The cloud free water pixels availability were computed and compared. The mean of SST for three day's composite data were calculated and a SST map was generated. The cloud free water pixels availability were computed and compared. The SST data availability was increased by merging the SST data.