GOCI, the world’s first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.

Overview of Geostationary Ocean Color Imager (GOCI) and GOCI Data Processing System (GDPS)

A novel method for discriminating Prorocentrum donghaiense from diatom blooms in the East China Sea using MODIS measurements

The raphidophyte Chattonella spp. and diatom Skeletonema spp. are the dominant harmful algal species of summer blooms in Ariake Sea, Japan. A new bio-optical algorithm based on backscattering features has been developed to differentiate harmful raphidophyte blooms from diatom blooms using MODIS imagery. Bloom waters were first discriminated from other water types based on the distinct spectral shape of the remote sensing reflectance R r s (λ) data derived from MODIS. Specifically, bloom waters were discriminated by the positive value of Spectral Shape, SS (645), which arises from the R r s (λ) shoulder at 645 nm in bloom waters. Next, the higher cellular-specific backscattering coefficient, estimated from MODIS data and quasi-analytical algorithm (QAA) of raphidophyte, Chattonella spp., was utilized to discriminate it from blooms of the diatom, Skeletonema spp. A new index b b p − i n d e x ( 555 ) was calculated based on a semi-analytical bio-optical model to discriminate the two algal groups. This index, combined with a supplemental Red Band Ratio (RBR) index, effectively differentiated the two bloom types. Validation of the method was undertaken using MODIS satellite data coincident with confirmed bloom observations from local field surveys, which showed that the newly developed method, based on backscattering features, could successfully discriminate the raphidophyte Chattonella spp. from the diatom Skeletonema spp. and thus provide reliable information on the spatial distribution of harmful blooms in Ariake Sea.

A Novel Method Based on Backscattering for Discriminating Summer Blooms of the Raphidophyte (Chattonella spp.) and the Diatom (Skeletonema spp.) Using MODIS Images in Ariake Sea, Japan

Ocean primary productivity estimation of China Sea by remote sensing

The coast of the East China Sea (ECS) is one of the regions most frequently affected by harmful algal blooms in China. Remote sensing monitoring could assist in understanding the mechanism of blooms and their associated environmental changes. Based on imagery from the Second-Generation Global Imager (SGLI) conducted by Global Change Observation Mission-Climate (GCOM-C) (Japan), the accuracy of satellite measurements was initially validated using matched pairs of satellite and ground data relating to the ECS. Additionally, using SGLI data from the coast of the ECS, we compared the applicability of three bloom extraction methods: spectral shape, red tide index, and algal bloom ratio. With an RMSE of less than 25%, satellite data at 490 nm, 565 nm, and 670 nm showed good consistency with locally measured remote sensing reflectance data. However, there was unexpected overestimation at 443 nm of SGLI data. By using a linear correction method, the RMSE at 443 nm was decreased from 27% to 17%. Based on the linear corrected SGLI data, the spectral shape at 490 nm was found to provide the most satisfactory results in separating bloom and non-bloom waters among the three bloom detection methods. In addition, the capability in harmful algae distinguished using SGLI data was discussed. Both of the Bloom Index method and the green-red Spectral Slope method were found to be applicable for phytoplankton classification using SGLI data. Overall, the SGLI data provided by GCOM-C are consistent with local data and can be used to identify bloom water bodies in the ECS, thereby providing new satellite data to support monitoring of bloom changes in the ECS.

/pdf/assessment-of-gcom-c-satellite-imagery-in-bloom-detection-a-25h0ajrq.pdf

Assessment of GCOM-C Satellite Imagery in Bloom Detection: A Case Study in the East China Sea

The coastal area of East China Sea (ECS) suffers from the harmful algal blooms ( HAB ) frequently every year in the
warm season. The most common causative phytoplankton algal species of HAB in the ECS in recent years are
 Prorocentrum donghaiense (dinoflagellates) , Karenia mikimotoi (dinoflagellates which could produce hemolytic and
ichthyotoxins) and Skeletonema costatum (diatom) . The discrimination between the dinoflagellates and diatom HAB through ocean color remote sensing approach can add the knowledge of HAB events in ECS and help to the precaution. A series of in-situ measurement consisted of absorption coefficient, total scattering and particulate backscattering coefficient was conducted in the southern coast of Zhejiang Province in May 2009, and the estuary of Changjiang River in August 2009 and December 2010, which encountered two HAB events and a moderate bloom. The Inherent Optical
Properties ( IOPs ) of the bloom waters have significant difference between phytoplankton species in absorption and
backscattering properties. The chlorophyll a specific absorption coefficient (a* phy (λ)) for the bloom patches (chlorophyll a concentration >6mg m -3 ) differ greatly from the adjacent normal seawater, with the a* phy (λ) of bloom water lower than 0.03 m 2 mg -1 while the a* phy (λ) of the adjacent normal seawater is much higher (even up to 0.06 m 2 mg -1 ). Meanwhile, the backscattering coefficients at 6 wavebands (420, 442, 470, 510, 590 and 700nm) are also remarkably lower for bloom waters ( -1 ) than the normal seawater (> 0.02 m -1 ). The backscattering coefficient ratio (Rbp(λ)) is much lower for diatom bloom waters than for dinoflagellates types (0.01079 vs. 0.01227). A discrimination model based on IOPs is
established, and several typical dinoflagellates and diatom bloom events including Prorocentrum donghaiense, Karenia mikimotoi and Skeletonema costatum in the ECS are picked out for testing with the MODIS-L2 and L3 ocean color remote sensing products from NASA website. The result proves that the satellite-derived inherent optical properties can be used to HAB detection and the discrimination of HAB species from dinoflagellates and the diatom types in the ECS.

HAB detection based on absorption and backscattering properties of phytoplankton

Since China launched first marine satellite HY-1A in May 2002, the second Chinese ocean color satellite HY-1B
sponsored by the State Oceanic Administration (SOA) was launched by the Long March rocket on April 11, 2007. There
are two sensors in the satellite, one is the Chinese ocean color and temperature scanner (COCTS), and the other is the
Coastal Zone Imager (CZI). So far, more than one thousand five hundred orbits data have been received and analysis for
application study. In this paper, first the properties and characteristics of HY-1B are briefly introduced with comparing
to the SeaWiFS. Second, the data processing technique of COCTS will be discussed in detail, such as satellite cross
radiation calibration, atmospheric correction, etc. Third, the remote sensing products of ocean color and temperature are
mapped by HY-1B to study its application potentiality. The results show that the HY-1B has its latent capability for the
application of marine environment detection. Finally, some suggestion is proposed to modify the next ocean satellite and
sensors, such as adding the properties of tilt scanning case, modification of CZI element uniform and future ocean color
satellite development in China.

The second Chinese ocean color satellite HY-1B and future plans

The spectral diffuse attenuation coefficients of downward irradiance (Kd) and upward radiance (Ku) are calculated
from a profiler spectrometer measured data. Both Kd and Ku are the parameters of apparent optical properties (AOP) and
need to be normalized according to the position of the Sun and sky conditions. Three kinds of sky indices are used to
indicate the atmospheric conditions of clear, overcast and partly cloudy at the time of measurements. The values of
normalized Kd can be compared with the sums of total absorption and backscattering coefficients. The total values from
both measured data and the models fit the normalized Kd with the correlation coefficients of 0.85 and 0.81, respectively.
The accuracy of Kd is also evaluated by the spectral root mean square error (RMSE) less than 0.15 m -1 in the spectral
range from 450 to 700 nm.

Comparison between the spectral diffuse attenuation coefficients and the IOP parameters

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HAB detection based on absorption and backscattering properties of phytoplankton

The second Chinese ocean color satellite HY-1B and future plans

Comparison between the spectral diffuse attenuation coefficients and the IOP parameters