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Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data
Nechad, B.; Alvera-Azcaràte, A.; Ruddick, K.; Greenwood, N. (2011). Reconstruction of MODIS total suspended matter time series maps by DINEOF and validation with autonomous platform data. Ocean Dynamics 61(8): 1205-1214. http://dx.doi.org/10.1007/s10236-011-0425-4
In: Ocean Dynamics. Springer-Verlag: Berlin; Heidelberg; New York. ISSN 1616-7341; e-ISSN 1616-7228, more
Peer reviewed article  

Available in  Authors 
    VLIZ: Open Repository 241456 [ OMA ]

Keyword
    Marine/Coastal
Author keywords
    Total suspended matter (TSM), MODIS, Data Interpolating Emprirical Orthogonal Functions (DINEOF), Cefas, Optical backscatter, TSM algorithm, TSM time series

Project Top | Authors 
  • BELCOLOUR - Optical remote sensing of coastal waters, more

Authors  Top 
  • Nechad, B., more
  • Alvera-Azcaràte, A., more
  • Ruddick, K., more
  • Greenwood, N.

Abstract
    In situ measurements of total suspended matter (TSM) over the period 2003–2006, collected with two autonomous platforms from the Centre for Environment, Fisheries and Aquatic Sciences (Cefas) measuring the optical backscatter (OBS) in the southern North Sea, are used to assess the accuracy of TSM time series extracted from satellite data. Since there are gaps in the remote sensing (RS) data, due mainly to cloud cover, the Data Interpolating Empirical Orthogonal Functions (DINEOF) is used to fill in the TSM time series and build a continuous daily “recoloured” dataset. The RS datasets consist of TSM maps derived from MODIS imagery using the bio-optical model of Nechad et al. (Rem Sens Environ 114: 854–866, 2010). In this study, the DINEOF time series are compared to the in situ OBS measured in moderately to very turbid waters respectively in West Gabbard and Warp Anchorage, in the southern North Sea. The discrepancies between instantaneous RS, DINEOF-filled RS data and Cefas data are analysed in terms of TSM algorithm uncertainties, space–time variability and DINEOF reconstruction uncertainty.

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