Chuqun Chen
Chinese Academy of Sciences
25 Papers
55 Citations
Chuqun Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Sea surface temperature & Atmospheric correction. The author has an hindex of 9, co-authored 25 publications.
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Papers
Impact of nonlinear mesoscale eddy on phytoplankton distribution in the northern South China Sea
TL;DR: In this article, the influence of a nonlinear, mesoscale eddy on ecological and bio-geochemical processes was investigated using mean sea level anomaly (MSLA) and chlorophyll (Chl) data.
38
A new approach for atmospheric correction of MODIS imagery in turbid coastal waters: a case study for the Pearl River Estuary
Quanjun He,Chuqun Chen +1 more
TL;DR: In this article, a shortwave infrared extrapolation (SWIRE) method is presented for Terra-MODIS data, which is used to correct the NIR bands (0.748 and 0.869 mu m) for sediment scattering and hence estimate the aerosol scattering reflectances in these bands.
28
The phytoplankton variability in the Pearl River estuary based on VIIRS imagery
TL;DR: In this article, a support vector machine (SVM) regression algorithm was developed for estimating the chlorophyll-a concentration (Cchla) in the turbid estuarine waters of the Pearl River estuary (PRE) based on visible infrared imaging radiometer suite (VIIRS) ocean color data.
26
Satellite observations of the small-scale cyclonic eddies in the western South China Sea
TL;DR: In this article, the medium-resolution imaging spectrometer (MERIS) daily 300 m data were used to study small-scale processes in the western South China Sea, and it was indicated that cyclonic eddies with horizontal scales of 10 km are frequently observed during the upwelling season of each year over the 2004-2009 period.
The possibility on estimation of concentration of heavy metals in coastal waters from remote sensing data
Chuqun Chen,Fenfen Liu,Quanjun He,Heyin Shi +3 more
- 25 Jul 2010
TL;DR: The band and band ratio were employed for algorithm development using the symbolic regression method, and the results showed the possiblity to retrieve concentration of heavy metal from remotely-sensed data.