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Study on the Role of Multi-Sensor Ocean Color Satellite Data Merging in Improving the Quality of Observation Data
Pages: 30-35
Year: Issue:  3
Journal: Ocean Technology

Keyword:  optimization techniquesoptical merging methodsaveraging methodsdata merging;
Abstract: Multi-sensor ocean color satellite data merging is of great significance in improving the temporal and spatial coverage and reliability of ocean color data. This study uses MODIS, MERIS and VIIRS multi-sensor ocean color satellite merging data to compare with in-situ data, and analyze the role of the two merging methods(averaging methods and optical merging methods based on optimization techniques) in improving the quality of observation data. The results show that the average absolute percentage error( MAPE) measured by MERIS,MODIS, VIIRS, averaging methods and optical merging methods based on optimization techniques is 18.5%,13.4%, 18.2%, 12.8% and 9.6%, respectively, compared with in-situ data. It means that both merging methods can effectively reduce the measurement error, and the quality of the merging products can be significantly improved through data merging. It also proves that the optical merging methods based on optimization techniques have better performance.
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