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- W2387496779 abstract "The monthly mean images of surface chlorophyll-a concentration in the Northern South China Sea(NSCS)were derived from the data preprocessing of the MODIS chlorophyll a(CHL-a) concentration Level 2 products(from January 2007 to December 2010). And then not only does the study implement the reconstruction of missing data in the monthly mean CHL-a image using Data Interpolating Empirical Orthogonal Functions(DIEOF), based on space-time correlation of data, but also evaluate the reconstructed result by analyzing the difference between data before and after the reconstruction, verifying the temporal and spatial variability, and calculating the precision index. The study shows that the complete MODIS CHL-a images, which are reconstructed using DIEOF, characterize the temporal and spatial variability of CHL-a in NSCS. The multiple correlation coefficient of the reconstruction result is 0.98, and the mean absolute error is less than 0.01. As it allows the calculation of missing data without requiring a prior knowledge about the error covariance structure, the DIEOF can be also successfully applied to the reconstruction of missing data in a large area or in a high proportion." @default.
- W2387496779 created "2016-06-24" @default.
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- W2387496779 date "2014-01-01" @default.
- W2387496779 modified "2023-09-23" @default.
- W2387496779 title "Reconstruction of missing remote sensing data of sea surface chlorophyll-a using DIEOF" @default.
- W2387496779 hasPublicationYear "2014" @default.
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