Cross-Validation of Multi-source SST Data Based on Point-to-Point

Now there are many researches on the assessment of sea surface temperature(SST) by remote-sensing at home and abroad, most of which focus on cross-validation of SST data and on-site measured data. For the non-measured waters, it's not easy to carry out assessment of SST, and now most of the assessment are an area average or macroscopic assessment based on the week, month, or specified period, these methods can't provide the assessment products with precision from point to point. This paper proposes a mutual assessment model based on SST data and other fusion data of remote sensing data. For multi-source remote sensing SST, this model could provide us with higher-quality data, including the measurement efficiency, data distribution and credibility and so on.