Publications

Jiang, LL; Guo, XY; Wang, L; Sathyendranath, S; Evers-King, H; Chen, YL; Li, BN (2020). Validation of MODIS ocean-colour products in the coastal waters of the Yellow Sea and East China Sea. ACTA OCEANOLOGICA SINICA, 39(1), 91-101.

Abstract
An extensive study collected in situ data along the Yellow Sea (YS) and East China Sea (ECS) to assess the radiometric properties and the concentration of the water constituents derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Thirteen high quality match-ups were obtained for evaluating the MODIS estimates of R-rs(lambda), chlorophyll a (Chl a) and concentrations of suspended particulate sediment matter (SPM). For MODIS R-rs(lambda), the mean absolute percentage difference (APD) was in the range of 20%-36%, and the highest uncertainty appeared at 412 nm, whereas the band ratio of R-rs(lambda) at 488 nm compared with that at 547 nm was highly consistent, with an APD of 7%. A combination of near-infrared bands and shortwave infrared wavelengths atmosphere correction algorithm (NIR-SWIR algorithm) was applied to the MODIS data, and the estimation accuracy of Rrs were improved at most of the visible spectral bands except 645 nm, 667 nm and 678 nm. Two ocean-colour empirical algorithms for Chl a estimation were applied to the processed data, the results indicated that the accuracy of the derived Chl a values was obviously improved, the four-band algorithms outperformed the other algorithm for measured and simulated datasets, and the minimum APD was 35%. The SPM was also quantified. Two regional and two coastal SPM algorithms were modified according to the in situ data. By comparison, the modified Tassan model had a higher accuracy for the application along the YS and ECS with an APD of 21%. However, given the limited match-up dataset and the potential influence of the aerosol properties on atmosphere correction, further research is required to develop additional algorithms especially for the low Chl a coastal water.

DOI:
10.1007/s13131-019-1522-3

ISSN:
0253-505X