• Title of article

    Retrieval of total suspended matter concentration in the Yellow and East China Seas from MODIS imagery

  • Author/Authors

    Zhang، نويسنده , , Minwei and Tang، نويسنده , , Junwu and Dong، نويسنده , , Qing and Song، نويسنده , , QingTao and Ding، نويسنده , , Jing، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    12
  • From page
    392
  • To page
    403
  • Abstract
    A retrieval algorithm, of total suspended matter (TSM) concentration in the Yellow Sea (YS) and East China Sea (ECS) was developed using observations made in the 2003 Spring and Autumn cruises over the YS and the ECS. Analysis of the in-situ backscattering coefficients of the suspended particles (bbp) indicates that the accuracy becomes worse when the concentration of TSM (CTSM) is higher than 20 mg/l. The accuracy of the bbp is improved by using a bio-optical model in which bbp is optimized with a non-linear least-square Levenberg–Marquardt method. The remote sensing reflectance (Rrs) is obtained by means of the optimization. The optimized Rrs for waters with CTSM higher than 20 mg/l, together with the measured Rrs for waters with CTSM lower than 20 mg/l, are used to establish the relationships between Rrs(748), Rrs(869) and Rrs(645), which are used in the iterative method for atmospheric correction. Two atmospheric correction algorithms are switched according to the water turbidity. The shortwave infrared wavelengths (SWIR) method is used for waters with high-turbidity, and the iterative method is used otherwise. Results of the atmospheric correction were then applied to the Tassan model modified in this paper to compute the CTSM. Comparison between the retrieval results from MODIS imagery and the in-situ measurements indicates that the algorithms described in this paper can provide a reliable estimation of the CTSM distributions in the YS and ECS.
  • Keywords
    Concentration of total suspended matter , Atmospheric correction , Yellow and East China Seas , Aqua-MODIS
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2010
  • Journal title
    Remote Sensing of Environment
  • Record number

    1629604