2026-10-13T00:24:40Z https://www.scidb.cn/oai

10.11922/sciencedb.01066 2022-08-03T10:33:10Z

2022-08-03 SCSDCT: South China Sea Full-coverage Daily 4-km Surface Chlorophyll-a Remote Sensing Reconstruction Dataset from Discrete Cosine Transform 2005-2019 doi:10.11922/sciencedb.01066 en A discrete cosine transform approach was applied to the OCCCI ocean color chlorophyll products, yielding a 15-year full-coverage daily 4-km CHL product over the South China Sea. Against the cross-validation set (5% of original data preserved) and an independent observational dataset collected from 34 cruises, evaluations suggest that DCT‑PLS has outperformed the widely applied classical data-interpolating empirical orthogonal function method. Besides, the DCT‑PLS method is characterized by more efficient computation. For the cross-validation set, the R2 is larger than 0.98, while root-mean-square error is 0.09 mg m-3. For the in-situ observation, root-mean-square error is 0.15 mg m-3. This dataset was successfully applied to study the intra-seasonal variability in the adjacent Luzon Strait (https://ieeexplore.ieee.org/document/9393603), suggesting its stronger capability compared with original gapped OCCCI data. Ocean Color; Chlorophyll; Remote Sensing Reconstruction; South China Sea; Discrete Cosine Transform Tianhao Wang Peng Yu Zelun Wu Wenfang Lu Xin Liu Qian P. Li Bangqin Huang PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.1109/TGRS.2021.3067646 Science Data Bank