A multi-sensor algorithm is applied to MODIS and MERIS satellite data in order to quantify suspended particulate matter (SPM) in the Yangtze River plume (East China Sea). Several atmospheric correction methods are tested; a simple but operational method is finally selected as appropriate for MODIS, MERIS and GOCI satellite data. As most of the methods for atmospheric corrections of satellite data fail over such highly turbid waters, an adaptation of the black pixel assumption is used to correct for the aerosol contribution. The retrieved seawater reflectance at red wavebands appears as the most sensitive to SPM concentrations but tends to saturate at concentrations beyond 100 mg.l(-1). By opposition the near-infrared seawater reflectance does not saturate even at extremely high concentrations of 1000 mg.l(-1). Overall, the most robust relationship between the SPM concentration and seawater reflectance is obtained considering a spectral ratio between the near-infrared (e. g., 850 nm) and visible (e. g. 550 nm). This relationship is applied to atmospherically corrected ocean color satellite data to retrieve SPM concentrations in the Yangtze River plume. Results show that ocean color satellite data can be used to study the seasonal dynamics of SPM and better understand the role played by the main physical processes involved (river discharge, tidal cycles, wind and regional circulation).