Journal of Earth System Science

, Volume 118, Issue 1, pp 1–10 | Cite as

Model-based remote sensing algorithms for particulate organic carbon (POC) in the Northeastern Gulf of Mexico

  • Young Baek Son
  • Wilford D. Gardner
  • Alexey V. Mishonov
  • Mary Jo Richardson
Article

Abstract

Hydrographic data, including particulate organic carbon (POC) from the Northeastern Gulf of Mexico (NEGOM) study, were combined with remotely-sensed SeaWiFS data to estimate POC concentration using principal component analysis (PCA). The spectral radiance was extracted at each NEGOM station, digitized, and averaged. The mean value and spurious trends were removed from each spectrum. De-trended data included six wavelengths at 58 stations. The correlation between the weighting factors of the first six eigenvectors and POC concentration were applied using multiple linear regression. PCA algorithms based on the first three, four, and five modes accounted for 90, 95, and 98% of total variance and yielded significant correlations with POC with R2 = 0.89, 0.92, and 0.93. These full waveband approaches provided robust estimates of POC in various water types.

Three different analyses (root mean square error, mean ratio and standard deviation) showed similar error estimates, and suggest that spectral variations in the modes defined by just the first four characteristic vectors are closely correlated with POC concentration, resulting in only negligible loss of spectral information from additional modes. The use of POC algorithms greatly increases the spatial and temporal resolution for interpreting POC cycling and can be extrapolated throughout and perhaps beyond the area of shipboard sampling.

Keywords

Particulate organic carbon principal component analysis remote sensing algorithm 

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References

  1. Bailey S W, McClain C R, Werdell P J and Schieber B D 2000 Normalized water-leaving radiance and chlorophyll a match-up analyses; NASA Technical Memorandum, vol. 206892, Greenbelt, USA.Google Scholar
  2. Bailey S W and Werdell P J 2006 A multi-sensor approach for the on-orbit validation of ocean color satellite data products; Remote Sens. Environ. 102 12–23.CrossRefGoogle Scholar
  3. Baith K, Lindsay R, Fu G and McClain C R 2001 Data analysis system developed for ocean color satellite sensors; EOS 82 202.CrossRefGoogle Scholar
  4. Bernal C E 2001 Spatial and Temporal Distributions of Particulate Matter and Particulate Organic Carbon, Northeast Gulf of Mexico; M.S. Thesis, Texas A&M University, USA.Google Scholar
  5. Cho K W, Reid R O and Nowlin W D 1998 Objectively mapped stream function fields on the Texas-Louisiana shelf based on 32 months of moored current meter data; J. Geophys. Res. 103 10377–10390.CrossRefGoogle Scholar
  6. DiMarco S F and Reid R O 1998 Characterization of the principal tidal current constituents on the Texas-Louisiana shelf; J. Geophys. Res. 103 3093–3109.CrossRefGoogle Scholar
  7. Fischer J 1985 On the information content of multispectral radiance measurements over an ocean; Int. J. Remote Sens. 6 773–786.CrossRefGoogle Scholar
  8. Fischer J, Doerffer R and Grassl H 1986 Factor analysis of multispectal radiance over coastal and open ocean water based on radiative transfer calculations; Appl. Opt. 25 448–456.CrossRefGoogle Scholar
  9. Gardner W D, Mishonov A V and Richardson M J 2006 Global POC concentrations from in-situ and satellite data; Deep-Sea Res. II 53 718–740.CrossRefGoogle Scholar
  10. Gordon Jr D C 1969 Examination of methods of particulate organic carbon analysis; Deep-Sea Res. 16 661–665.Google Scholar
  11. Gower J F R, Lin S and Borstad G A 1984 The information content optical spectral ranges for remote chlorophyll estimation in coastal waters; Int. J. Remote Sens. 5 349–364.CrossRefGoogle Scholar
  12. IOCCG 2000 Remote sensing of ocean colour in coastal and other optically-complex waters; In: Report of the International Ocean-Color Coordination Group, No. 3, (ed.) Sathyendranath S, Dartmouth, 140 pp.Google Scholar
  13. JGOFS 1996 Protocols for the Joint Global Ocean Flux Study (JGOFS) core measurements, Report #19, Intergovernmental Oceanographic Commission, Bergen, Norway, 170 pp.Google Scholar
  14. Lohrenz S E, Dagg M J and Whitledge T E 1990 Enhanced primary production at the plume-oceanic interface of the Mississippi River; Cont. Shelf Res. 10 639–664.CrossRefGoogle Scholar
  15. Loisel H, Boss E, Stramski D, Oubelkheir K and Deschamps P-Y 2001 Seasonal variability of the backscattering coefficient in the Mediterranean Sea based on Satellite SeaWiFS imagery; Geophys. Res. Lett. 28 4203–4206.CrossRefGoogle Scholar
  16. McClain C R, Feldman G C and Hooker S B 2004 An overview of the SeaWiFS project and strategies for producing a climate research quality global ocean bio-optical time series; Deep-Sea Res. II 51 5–42.CrossRefGoogle Scholar
  17. Mishonov A V, Gardner W D and Richardson M J 2003 Remote sensing and surface POC concentration in the South Atlantic; Deep-Sea Res. II 50 2997–3015.CrossRefGoogle Scholar
  18. Mueller J L 1976 Ocean color spectra measured off the Oregon coast: Characteristic vectors; Appl. Opt. 15 394–402.CrossRefGoogle Scholar
  19. Neumann A, Krawczyk H and Walzel T 1995 A complex approach to quantitative interpretation of spectral high resolution imagery; In: Proc. Third Thematic Conf. Remote Sens. Mar. Coast. Environ. pp. II–641 & II-652.Google Scholar
  20. Ohlmann J C and Niiler P P 2005 Circulation over the continental shelf in the northern Gulf of Mexico; Prog. Oceanogr. 64 45–81.CrossRefGoogle Scholar
  21. Rabalais N N, Turner R E, Justic D, Dortch Q, Wiseman W J and Sen Gupta B K 1996 Nutrient changes in the Mississippi River and system responses on the adjacent continental shelf; Estuaries 19 386–407.CrossRefGoogle Scholar
  22. Redalje D G, Lohrenz S E and Fahnenstiel G L 1994 The relationship between primary production and the vertical export of particulate organic carbon matter in a river-impacted coastal system; Estuaries 17 829–838.CrossRefGoogle Scholar
  23. Sathyendranath S, Prieur L and Morel A 1989 A three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal water; Int. J. Remote Sens. 10 1373–1394.CrossRefGoogle Scholar
  24. Sharp J H 1974 Improved analysis for “particulate“ organic carbon and nitrogen from seawater; Limnol. Oceanogr. 19 984–989.Google Scholar
  25. Son Y B 2006 POC algorithms based on spectral remote sensing data and its temporal and spatial variability in the Gulf of Mexico; Ph.D. Thesis, Texas A&M University, USA.Google Scholar
  26. Son Y B, Gardner W D, Mishonov A V and Richardson M J 2009 Multispectral remote sensing algorithms for particulate organic carbon (POC): The Gulf of Mexico; Remote Sens. Environ. 113 50–61.CrossRefGoogle Scholar
  27. Stramska M and Stramski D 2005 Variability of particulate organic carbon concentration in the north polar Atlantic based on ocean color observation with Sea-viewing Wide Field-of-view Sensor (SeaWiFS); J. Geophys. Res. 110 C10018, doi:10.1029/2004JC002762.Google Scholar
  28. Stramski D, Reynolds R A, Babin M, Kaczmarek S, Lewis M R, Röttgers R, Sciandra A, Stramska M, Twardowski M S and Claustre H 2008 Relationship between the surface concentration of particulate organic carbon and optical properties in the eastern South Pacific and eastern Atlantic Oceans; Biogeosciences 5 171–201.CrossRefGoogle Scholar
  29. Stramski D, Reynolds R A, Kahru M and Mitchell B G 1999 Estimation of particulate organic carbon in the ocean from satellite remote sensing; Science 285 239–242.CrossRefGoogle Scholar
  30. Twomey S 1977 Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements, (New York: Elsevier) p. 243.Google Scholar
  31. Vastano A C, Barron Jr C N and Shaar E W 1995 Satellite observations of the Texas current; Cont. Shelf Res. 15 729–754.CrossRefGoogle Scholar
  32. Walker N D 1996 Satellite assessment of Mississippi River plume variability: Causes and predictability; Remote Sens. Environ. 58 21–35.CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2009

Authors and Affiliations

  • Young Baek Son
    • 1
    • 2
  • Wilford D. Gardner
    • 1
  • Alexey V. Mishonov
    • 3
  • Mary Jo Richardson
    • 2
  1. 1.Department of FisheriesNagasaki UniversityNagasakiJapan
  2. 2.Department of OceanographyTexas A&M UniversityCollege StationUSA
  3. 3.National Oceanographic Data CenterSilver SpringUSA

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