Satellite remote sensing has been successfully employed to monitor and detect the increasing incidence of harmful algal
blooms (HABs) under various water conditions. In this study, to establish a comprehensive monitoring system of HAB
outbreaks (particularly Cochlodinium polykrikoides blooms) in the southern coast of Korea (SCK), we tested the several
proposed red-tide detection methods using SeaWiFS and MODIS ocean color data. Temporal and spatial information of
red tide events from 2002 to 2013 were obtained from the National Fisheries Research and Development of Korea
(NFRDI), which were matched with synchronously obtained satellite-derived ocean color data.
The spectral characteristics of C. polykrikoides red tides were that increased phytoplankton absorption at 443 nm and
pigment backscattering 555 nm resulted in a steeper slope between 488 and 555 nm with a hinge point at 488 (or 490)
nm. On the other hand, non-red tide water, typically were presented by broader radiance spectra between the blue and
green bands were associated with reduced pigment absorption and backscattering. The analysis of ocean color imageries
that captured C. polykrikoides red tide blooms showed discolored waters with enhanced pigment concentrations, high
chlorophyll, fluorescence, absorption at 443 nm. However, most red tide detection algorithms found a large number of
false positive but only a small number of true positive areas. These proposed algorithms are not useful to distinguish true
red tide water from complex non-red tide water. Our proposed method substantially reduces the false signal rate (false
positive) from strong absorption at short wavelengths and provide a more reliable and robust detection of C.
polykrikoides blooms in the SCK from the space.
Total suspended matter concentration (TSM) algorithms for ocean color sensors use empirical relationship between
satellite-retrieved remote sensing reflectances and TSM. However the estimated-TSM has no enough accuracy because
the reflectance at visible bands has error after atmospheric correction in high turbid area. The purpose of this study is to
estimate simultaneously total suspended matter concentration, aerosol optical thickness and Angstrom exponent using
three bands at near infrared from MODIS/Aqua and SeaWiFS data. We applied this scheme to MODIS/Aqua and
SeaWiFS data, and satellite-derived TSM were compared with ship-observed TSM dataset in Yellow Sea and East China
Sea. RMSE of TSM was 0.338 in log-log coordinates and correlation coefficient was 0.850. The scheme was better than
Clark’s or Tassan’s TSM algorithm.
KEYWORDS: Particle filters, Satellites, Signal attenuation, Magnesium, Data analysis, Temperature metrology, Photosynthesis, Error analysis, Data modeling, Luminescence
Despite some efforts to get better estimation of the primary production of the Yellow Sea, there is still uncertainty in
the estimates. Extreme range of the environmental factors through seasons makes the estimation difficult. The high
variability in environmental characteristics calls for using satellite data for better estimation of the primary
production of the Yellow Sea. To achieve the goal with reasonable accuracy using satellite data, there are many
problems to resolve such as retrieval of chlorophyll and diffuse attenuation coefficient of PAR, and estimation of
physiological parameters and vertical structure of chlorophyll in water column. Here we analyzed 66 vertical
profiles of chlorophyll-a obtained during March-August in 1994-2001 period. Using some relationships among
parameters, we attempt to retrieve subsurface chlorophyll profiles only from KPAR (downwelling attenuation
coefficient of PAR) and surface chlorophyll-a values. Although uncertainty was high in predicting accurate shape of
the profiles (e.g., exact depth of subsurface chlorophyll maximum), fairly accurate estimation of depth-integrated
primary production was made given appropriate P-I parameters. We also compared the estimates with those from
VGPM (vertically generalized production model). VGPM gave much higher estimates than simulated in-situ depthintegrated
primary production. The reason of the discrepancy seems that PoptB from VGPM formulation were higher
than estimated in-situ PoptB . Adjusted VGPM gave better
results than original VGPM. But the depth-resolved model was better than the adjusted VGPM in terms of
fitness and bias.
Conference Committee Involvement (5)
Remote Sensing of the Marine Environment II
31 October 2012 | Kyoto, Japan
Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment
13 October 2010 | Incheon, Korea, Republic of
Remote Sensing of Inland, Coastal, and Oceanic Waters
18 November 2008 | Noumea, New Caledonia
Active and Passive Remote Sensing of the Oceans
8 November 2004 | Honolulu, Hawai'i, United States
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