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

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 (R 2 =0.99, N=58). The algorithm can be extrapolated throughout the region of shipboard sampling for more detailed coverage and analysis.

Optical techniques for remote and in-situ characterization of particles pertinent to GEOTRACES

“…Correlation-based algorithms are used to map chlorophyll (O'Reilly et al, 1998), POC (Son et al, 2009;Stramski et al, 1999Stramski et al, , 2008, PM (Vantrepotte et al, 2011), PIC (Balch et al, 2007), and phytoplankton functional groups (Alvain et al, 2005;IOCCG, 2014). They tend to work best in open ocean conditions where the assumptions that phytoplankton and associated constituents co-vary and primarily modulate ocean color are valid.…”

Remote Sensing Observation of Particulate Organic Carbon in the Pearl River Estuary

“…Although POC generally represents only around 4-5 × 10 9 t C of total carbon in marine surface waters, it plays an important role in the global carbon cycle [2]. POC is important in regards to its role in sequestering carbon, scavenging associated elements and compounds, and sinking to the bottom as part of "the biological pump" [1][2][3]. Moreover, compared with POC stock in the ocean surface, the flux from DIC to POC has been estimated at about 50 × 10 9 t C·yr −1 [2].…”

“…Suspended particles can scatter light back to space, with backscattered light being able to be received by remote sensing sensors. Some researchers have reported on relationships between POC concentration and particle backscattering light [5][6][7], and it has been suggested that POC concentrations in oceanic surface waters can be estimated from ocean color remote sensing data [2,3,[5][6][7][8]. However, the spectral variability of the backscattering coefficients of suspended particles increases the difficulty in calculating POC from satellite data.…”

“…However, the spectral variability of the backscattering coefficients of suspended particles increases the difficulty in calculating POC from satellite data. At present, many remote sensing POC algorithms are based on the green band or green-to-blue ratio [3,5,9]; besides, many studies use the decreasing trend of bb with wavelength [5,7,9]. In 1999, Stramski et al [9] firstly published an algorithm for estimating POC concentration in the Southern Ocean from SeaWiFS data based on the correlation between the particle backscattering coefficient, bbp(λ), and POC concentration and the dependence of spectral reflectance, Rrs(λ), on the total backscattering coefficient, bb(λ) [9].…”

“…However, for waters along coastal zones, especially estuaries, POC is derived not only from phytoplankton but also from terrestrial ecosystems [12]. The variable particle assemblages (many mineral particles for example) and high concentrations of optically important dissolved organic matter (DOM) in coastal waters mean that open ocean POC algorithms do not perform well [3]. Although they account for less than 10% of the world's ocean area, coastal oceans play an important role in the global carbon cycle.…”