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.
Geostationary Ocean Color Imager(GOCI) is one of three payloads on board the Communication, Ocean, and
Meteorological Satellite(COMS) launched 27th, June, 2010. For understanding GOCI imaging performance, we
constructed the Integrated Ray Tracing model consisting of the Sun model as a light source, a target Earth model,
and the GOCI optical system model. We then combined them in Monte Carlo based ray tracing computation.
Light travels from the Sun and it is then reflected from the Earth section of roughly 2500km * 2500km in
size around the Korea peninsula with 40km in spatial resolution. It is then fed into the instrument before reaching to the detector plane. Trial simulation runs for the GOCI imaging performance were focused on the combined slot images and MTF. First, we used modified pointing mirror mechanism to acquire the slot images, and then mosaiced them. Their image performance from the GOCI measurement were compared to the ray tracing simulation results. Second, we investigated GOCI in-orbit MTF performance with the slanted knife edge method applied to an East coastline image of the Korea peninsula covering from 38.04N, 128.40E to 38.01N, 128.43E. The ray tracing simulation results showed 0.34 in MTF mean for near IR band image while the GOCI image obtained 9th Sep, 2010 and 15th Sep, 2010, were used to produce 0.34 at Nyquist frequency in MTF. This study results prove that the GOCI image performance is well within the target performance requirement, and that the IRT end-to-end simulation technique introduced here can be applicable for high accuracy simulation of in-orbit performances of GOCI and of other earth observing satellite instruments.
Geostationary Ocean Color Imager (GOCI), a payload of the Communication, Ocean and Meteorology Satellite
(COMS), is the world's first ocean color observation satellite in geostationary orbit. It was launched at Kourou Space
Center in French Guiana in June 2010. The detector array in GOCI is custom CMOS Image sensor about 2 Mega-pixels,
featuring rectangular pixel size to compensate for the Earth oblique projection.
This satellite is being operated on geostationary orbit about 36,500km far from the earth; hence it can be more influenced
by sun activities than the other on low Earth orbit. Especially, the detector is sensitive of heat and it may give rise to
increasing the defective pixels. In this paper, radiometric performance variations have been analyzed through the time
series analysis, using the offset parameters and detector temperature estimated in GOCI radiometric model. It is essential
to monitor the overall sensitivity of GOCI sensor, and it will helpful to the radiometric calibration.
In the result, we notified there was no great variation in time series of offset parameters after operating the GOCI in July
2010, but we monitored an anomaly by an operational event. One of them related to thermal electron showed slightly
increasing trend and the diurnal variation by the sun energy. Although sun interferences are occurred sometimes, any
significant anomaly isn't found. With these results of characterization, we find that GOCI has been carrying out stably in
the aspect of radiometric performance, and expect that it will be kept during the mission life.
KEYWORDS: Image processing, Satellites, Infrared countermeasures, Spectrum analysis, System on a chip, Analytical research, Imaging systems, Data conversion, Data processing, Data backup
The world's first space-borne ocean color observation geostationary satellite was launched on June 27, 2010. Systems
and Korea Ocean Satellite Center was established for receiving, processing and distributing images captured
Geostationary Ocean Color Imager (GOCI) since 2005. Trials test of the systems had been conducted continuously for
stabilized operation since 2009. Systems in KOSC were set up to operate from receiving image to distributing data
nonstop. Because this means that stabilized operation of each system and relation of them is important, it is crucial to
figure out problem when anomaly occurred and analyze effect on each system. Also it is very significant to figure out
additional unexpected problem during in-orbit test period, analyze it and then propose solutions to it, because operation
of geostationary satellite for ocean is the first in the world.
In conclusion, we artificially make emergencies and propose solutions responding to them before lunching satellite. Also
we analyze anomalies which are occurred during in-orbit test period, then seek solutions responding them for setting up
stabilized operation. The results drawing from the paper will good source to KOSC which operate system of GOCI and
agencies concerned for 7 years from now.
Global warming has significant effect on the sea surface temperature. Sea surface temperature is
an important parameter for the quantitative studies of monitoring the Earth's environment changes.
Determination and analysis of sea surface temperature from satellite data has been the main focus in
oceanographic research and thus needs quantitative analysis in its retrievals. We used EOF method
applying SST. Seasonal and interannual variability of Sea surface temperature (SST) and Land
surface temperature (LST) concentration in the korea Sea was examined using Empirical Orthogonal
Function (EOF) analysis of data obtained by the NOAA from 1999 to 2009.
In the result of SST, The first EOF mode explains 55.7% of the variability, the second EOF mode
explains 21.5%, and the third EOF mode explains 21.5%. As a result of LST, The first EOF mode
explains 99.7% of the variability, the second EOF mode explains 2.5%, and the third EOF mode
explains 0.9. It shows commom tendency of interannual variability with the period of 3-4 years at
most of the locations. SST was higher in the 2004's and early 2006's and lower in the 2003. The
pattern of the interannual variability of SST was similar to that of air temperature. Increasing trend
of SST was obvious that it was larger eastern more than western. In the Future, we expect to analyse,
collect with a various satellite data and in situ data for long time.
Studying the light field of sea water is important in Ocean Color Remote Sensing (OCRS) because it brings immense
information concerning the ocean environmental properties. This magnitude of the Apparent Optical Properties (AOPs)
emerges from the sea-surface after incidence light energy has been absorbed and scattered by sea water constituents. In
this process, the amount of scattering is a lot smaller than that of absorption relatively. So the understanding of Inherent
Optical Properties (IOPs), especially absorption, is very important in OCRS. Many studies have been accomplished in
various seas around the world. In optically more complex waters around Korea, we have found only a few investigations
on the IOP and AOP. Thus, in this study we analyze the absorption coefficient of sea water constituents, phytoplankton,
Suspended Sediment (SS) and Dissolved Organic Matter (DOM) for the IOPs and the remote sensing reflectance for the
AOPs. About 1300 water samples have been collected in the Korean waters from 1998 to 2010. It should be noted that
sea areas around the Korea have different characteristics separately. So we analyzed the optical properties of each
separated sea waters and compared each other results. The absorption spectral shape of SS and DOM showed
exponentially decreasing pattern. Each graph's slope includes information of absorption characteristics. Using this
results, in the future, we will prompt to develop the ocean environmental algorithms for ocean color satellite images,
especially GOCI (Geostationary Ocean Color Imager) which will be launched on June 2010, around the Korean ocean.
The data processing software system of Geostationary Ocean Color Imager (GOCI) is composed of the image preprocessing
system (IMPS) and the GOCI data processing system (GDPS). IMPS generate GOCI level 1B from raw
satellite data and GDPS is the post-processing system to generate GOCI level 2.
IMPS have a radiometric correction module as IRCM and a geometric correction module named as INRSM. The former
is focused on equipment's mechanical noise reduction and radiometric accuracy and the latter image navigation and
image registration accuracy by landmark matching method and image mosaic method.
GDPS have the atmospheric correction algorithms, as the spectral shape matching method (SSMM) and the sun glint
correction algorithm (SGCA), and BRDF algorithm to solve bi-directional problem. Several Case-II water analytical
algorithms, like chlorophyll concentration, suspended sediment and dissolved organic matter, are contained in GDPS.
Also, GDPS will generate the value added product like water quality, fishery ground information, water current vector,
etc.
During in-orbit test period planned six months after successful launch of satellite, IMPS and GDPS will be verified with
respect to those requirements and algorithms and functionality and accuracy by pre-defined test procedure like test,
inspection, demonstration. And then those configuration parameters will be modified and the algorithm descriptions will
be updated. In this paper, we will present the preliminary analyzed results of data processing system test and update
planning during in-orbit test.
The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS)
requires accurate atmospheric correction for the purpose of qualified ocean remote sensing. Since its eight bands are
affected by atmospheric constituents such as gases, molecules and atmospheric aerosols, understanding of aerosolradiation
interactions is needed. Aerosol optical properties based on
sun-photometer measurements are used to analysis
aerosol optical thickness (AOT) under various aerosol type and loadings. It is found that the choice of aerosol type
makes little different in AOT retrieval for AOT<0.2. These results will be useful for aerosol retrieval of COMS/GOCI
data processing.
The instrument level ground test of the Geostationary Ocean Color Imager(GOCI) has been completed and integrated
onto the Communication, Ocean and Meteorological Satellite(COMS) which is scheduled for launch in late 2009.
In order to monitor the short-term biophysical phenomena with better temporal and spatial resolution, The GOCI has
developed with eight VNIR bands, 500m GSD, and 2500km×2500km coverage centered at 36°N and 130°E. The GOCI
planned to observe the full coverage region by every hour in daytime, and provide 8 images in daytime during single day.
The GOCI ground test campaign for characterization and calibration has been performed by Korea Aerospace Research
Institute(KARI), Korea and EADS Astrium, France. Korea Ocean Research & Development Institute(KORDI) has
verified that test results satisfy all the GOCI performance requirements(Ex. MTF, SNR, Polarization, etc.) requested by
KORDI.
The GOCI has been sufficiently characterized under both of ambient and thermal-vacuum environments in order to
develop the on-orbit radiometric calibration algorithm. GOCI radiometric model has been finalized with 3rd order
polynomial. Because solar calibration is the on-orbit radiometric calibration method of the GOCI, Solar Diffuser made
of fused silica and Diffuser Aging Monitoring Device(DAMD) are implemented as on-board calibration system.
Diffusion factor of the Solar Diffuser and DAMD with respect to the solar incident angle, wavelength, and pixel location
has been successfully characterized. Diffuser aging factor has been calculated for the compensation of the diffuser
degradation by space environment. Diffusion factor of Solar Diffuser and DAMD, and diffuser aging factor
characterized during prelaunch ground test are implemented into the GOCI radiometric calibration S/W developed by
KORDI.
The World's first Ocean Color Observation Satellite, the GOCI (Geostationary Ocean Color Imager) equipped with is
scheduled to be launched on Communication, Ocean and Meteorological Satellite (COMS) in November 2009. Korea
Ocean Research & Development Institute (KORDI) has developed GOCI Data Processing System (GDPS) which
produces ocean environment analysis data such as chlorophyll concentration, TSS, CDOM, Red-Tide, water current
vector, etc. In order to retrieve water-leaving radiance more precisely, atmospheric and BRDF (Bi-Directional
Reflectance Distribution Function) correction algorithms optimized for the environment of the GOCI coverage area and
COMS satellite orbit characteristics have been developed and implemented into the GDPS. GOCI operational
atmospheric correction algorithm has a capability to retrieve water-leaving radiance in the presence of aerosols with high
optical thickness (i.e. Asian Dust). At-sensor radiance which is affected by relative change of the Sun and satellite
position is corrected by the GOCI BRDF Correction algorithm. GOCI L2 data which is the product of the GDPS is
provided with 8 VNIR band images with 4967 x 5185 pixel resolution on the GOCI coverage area. As GOCI main
operation center, Korea Ocean Satellite Center (KOSC) has been established by KORDI. Main operational functions of
KOSC are the acquisition, processing, and storage of the GOCI data and distribution service of ocean satellite standard
products generated from the GOCI data. Operational systems of KOSC are GDAS(GOCI Data Acquisition System),
IMPS(Image Pre-processing System), GDPS, DMS(Data Management System), and GDDS(GOCI Data Distribution
System). After the launch, KOSC has a plan to provide the GOCI data for the real time ocean environment and marine
bio-physical phenomena variability monitoring.
SeaWiFS RCA-Chl along with sea surface height variations/geostrophic currents, sea surface temperature, wind
speed/direction and field observation data, are used to first describe comprehensively the occurrences of various
hazardous algal blooms (HABs) and their underlying mechanisms and link to nutrient enrichment during the summer in
shelf-slope waters off the Northwest Pacific (NWP). These datasets provide a coherent view of the summertime
evolution of HABs and related physical processes in four common dynamic regions: coastal cold/estuary water zones,
upwelling zones next to the coast, repeated meanders/eddies, and frontal regimes induced by the Kuroshio and its
tributaries. High blooms coincided with the coastal upwelling and cyclonic eddy regimes that followed SST minimum
and large negative SSH along with favorable phase of winds. By contrast, relatively low mean RCA were consistent with
the fronts and anticyclonic meanders revealing moderate-high SSH fields along with variable winds blown off the NWP
coast. These anticyclonic meanders, on some occasions, when nutrient-containing coastal water setoff higher chlorophyll
biomass and major currents gained force in August, straddled the continental margin, entraining high chlorophyll water
from the coast and from the adjacent cyclonic eddies located nearby into their outer rings that formed a conveyer-belt
system of transport to inject coastal blooms into the deep-sea (e.g., East Sea) region of the NWP. The above findings
based on satellite data combined with field hydrographic/ bloom observation data evidently illustrated richness of the
response of summer HABs to the surface circulation and nutrient enrichment processes in shelf-slope waters off the
NWP coast.
In the Saemangeum coastal area as a study area, the tidal dyke of 33 km-long has been constructed for over 10 years.
This large scale of coastal engineering work has influenced the environment around the Saemangeum tide embankment.
Especially the construction has induced in the changes of ocean circulation system, so that the re-suspension and
movement of the Suspended Sediments (SS) were changed. The Suspended Sediments Concentration (SSC) is an
important factor for understanding of the Saemangeum oceanic environmental change because SSC directly affect to the
primary production by phytoplankton in the ocean. Accordingly we investigated and monitored the SS and chlorophyll
concentration change using time-series multi-sensor satellite data. We used Landsat TM/ETM+ for the SS and
chlorophyll monitoring respectively. As a result, it was found that the northern sea area of Gogunsan Islands had
significantly become clear after the completion of 4th embankment in the end of 2003 whereas the southern sea area was
getting a high amount of incoming flux of SS through 2 dyke gates that were still under construction. Chlorophyll
concentration around the 4th embankment showed an increasing pattern after dyke construction.
The spatial and temporal distributional patterns of suspended sediments (SS) in the East China Sea (ECS) and Yellow
Sea (YS) were investigated by using satellite ocean color data from SeaWiFS and by using in-situ data. Except for the
Southeastern YS, the overall distribution patterns of SS revealed a general, cross-shelf decreasing trend along the
sediment dispersal system away from the rivers, closely consistent with the previous classification of SS - Infant stage,
Younger stage, Mature stage and Old stage. We hypothesize that the mature stage plays an important role in transporting
enormous amount of fine-grained sediments to the down streamside of China. Such transport of SS during this stage is
much higher than those during other stages and most of these sediments are supplied from the resuspended mudsediments
of the ECS, with origins mainly in Yangtze River. This study suggests that the resuspension and outflow of the
sediment plume is primarily caused by intensive mixing and existence of the coastal and offshore circulation features
during the mature stage of the SS evolution.
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.
Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 x 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. To achieve these mission objectives, it is necessary to develop an atmospheric correction technique which is capable of delivering geophysical products, particularly for highly turbid coastal regions that are often dominated by strongly absorbing aerosols from the adjacent continental/desert areas. In this paper, we present a more realistic and cost-effective atmospheric correction method which takes into account the contribution of NIR radiances and include specialized models for strongly absorbing aerosols. This method was tested extensively on SeaWiFS ocean color imagery acquired over the Northwest Pacific waters. While the standard SeaWiFS atmospheric correction algorithm showed a pronounced overcorrection in the violet/blue or a complete failure in the presence of strongly absorbing aerosols (Asian dust or Yellow dust) over these regions, the new method was able to retrieve the water-leaving radiance and chlorophyll concentrations that were consistent with the in-situ observations. Such comparison demonstrated the efficiency of the new method in terms of removing the effects of highly absorbing aerosols and improving the accuracy of water-leaving radiance and chlorophyll retrievals with SeaWiFS imagery.
Accurate detection of highly toxic red tide algal blooms in coastal turbid waters has been challenging with currently existing spectral and bio-optical methods applied to satellite ocean color imagery, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. In the present study, we have presented a new red tide index (RI) technique to effectively identify the highly toxic dinoflagellate Cochlodinium polykrikoides (p) blooms in the Korean South Sea and neighboring waters. The effectiveness of this technique was evaluated using in-situ bio-optical observations and SeaWiFS ocean color imagery acquired during two bloom episodes on 19 September 2000 and 28 September 2003. The findings revealed that chlorophyll-a estimated through the application of OC-4 bio-optical algorithm to the SeaWiFS imagery falsely identified Cochlodinium.p blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents around coastal areas and river mouths. In contrast, red tide index was found to provide more accurate and comparable spatial Cochlodinium.p patterns consistent with in-situ observations, proving to be the best method for providing improved capability of detecting, predicting and monitoring of Cochlodinium.p bloom dynamics in clear oceanic waters and high scattering and absorbing waters off the Korean coast.
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