Multispectral remote-sensing algorithms for particulate organic carbon (POC): The Gulf of Mexico uri icon

abstract

  • To greatly increase the spatial and temporal resolution for studying carbon dynamics in the marine environment, we have developed remote-sensing algorithms for particulate organic carbon (POC) by matching in situ POC measurements in the Gulf of Mexico with matching SeaWiFS remote-sensing reflectance. Data on total particulate matter (PM) as well as POC collected during nine cruises in spring, summer and early winter from 1997-2000 as part of the Northeastern Gulf of Mexico (NEGOM) study were used to test algorithms across a range of environments from low %POC coastal waters to high %POC open-ocean waters. Finding that the remote-sensing reflectance clearly exhibited a peak shift from blue-to-green wavelengths with increasing POC concentration, we developed a Maximum Normalized Difference Carbon Index (MNDCI) algorithm which uses the maximum band ratio of all available blue-to-green wavelengths, and provides a very robust estimate over a wide range of POC and PM concentrations (R2 = 0.99, N = 58). The algorithm can be extrapolated throughout the region of shipboard sampling for more detailed coverage and analysis. 2008 Elsevier Inc.

published proceedings

  • REMOTE SENSING OF ENVIRONMENT

author list (cited authors)

  • Son, Y. B., Gardner, W. D., Mishonov, A. V., & Richardson, M. J.

citation count

  • 58

complete list of authors

  • Son, Young Baek||Gardner, Wilford D||Mishonov, Alexey V||Richardson, Mary Jo

publication date

  • January 2009