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Multi-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay



Details

  • Journal Title:
    SPIE Proceedings
  • Personal Author:
  • NOAA Program & Office:
    NESDIS (National Environmental Satellite, Data, and Information Service)
  • Description:
    Standard blue-green ratio algorithms do not usually work well in turbid productive waters because of the contamination of the blue and green bands by CDOM absorption and scattering by non-algal particles. One of the alternative approaches is based on the two- or three band ratio algorithms in the red/NIR part of the spectrum, which require 665, 708, 753 nm bands (or similar) and which work well in various waters all over the world. The critical 708 nm band for these algorithms is not available on MODIS and VIIRS sensors, which limits applications of this approach. We report on another approach where a combination of the 745nm band with blue-green-red bands was the basis for the new algorithms. A multi-band algorithm which includes ratios Rrs(488)/Rrs(551)and Rrs(671)/Rrs(745) and two band algorithm based on Rrs671/Rrs745 ratio were developed with the main focus on the Chesapeake Bay (USA) waters. These algorithms were tested on the specially developed synthetic datasets, well representing the main relationships between water parameters in the Bay taken from the NASA NOMAD database and available literature, on the field data collected by our group during a 2013 campaign in the Bay, as well as NASA SeaBASS data from the other group and on matchups between satellite imagery and water parameters measured by the Chesapeake Bay program. Our results demonstrate that the coefficient of determination can be as high as R2 > 0.90 for the new algorithms in comparison with R2 = 0.6 for the standard OC3V algorithm on the same field dataset. Substantial improvement was also achieved by applying a similar approach (inclusion of Rrs(667)/Rrs(753) ratio) for MODIS matchups. Results for VIIRS are not yet conclusive.
  • Source:
    SPIE Proceedings, 9638, 96380A
  • DOI:
  • ISSN:
    0277-786X
  • Format:
    pdf
  • Publisher:
    SPIE
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha-512:11ef463fe12dca66737d0ce5e46b071644a41adb02207d0f6194d4284d2104080eaa709137dc00dd57bf4d5586af2942862a3f7cb634e44460364264e6ffe353
  • Download URL:
  • File Type:
    Filetype[PDF - 844.97 KB ]
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