Hee-Jeong Han

Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

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.

Initial validation of GOCI water products against in situ data collected around Korean peninsula for 2010–2011

This paper provides initial validation results for GOCI-derived water products using match-ups between the satellite and ship-borne in situ data for the period of 2010–2011, with a focus on remote-sensing reflectance (Rrs). Match-up data were constructed through systematic quality control of both in situ and GOCI data, and a manual inspection of associated GOCI images to identify pixels contaminated by cloud, land and inter-slot radiometric discrepancy. Efforts were made to process and quality check the in situ Rrs data. This selection process yielded 32 optimal match-ups for the Rrs spectra, chlorophyll a concentration (Chl_a) and colored dissolved organic matter (CDOM), and with 20 match-ups for suspended particulate matter concentration (SPM). Most of the match-ups are located close to shore and thus the validation should be interpreted limiting to near-shore coastal waters. The Rrs match-ups showed the mean relative errors of 18–33% for the visible bands with the lowest 18–19% for the 490 nm and 555 nm bands and 33% for the 412 nm band. Correlation for the Rrs match-ups was high in the 490–865 nm bands (R2=0.72–0.84) and lower in the 412 nm band (R2=0.43) and 443 nm band (R2=0.66). The match-ups for Chl_a showed a low correlation (<0.41) although the mean absolute percentage error was 35% for the GOCI standard Chl_a. The CDOM match-ups showed an even worse comparison with R2<0.2. These match-up comparison for Chl_a and CDOM would imply the difficulty to estimate Chl_a and CDOM in near-shore waters where the variability in SPM would dominate the variability in Rrs. Clearly, the match-up statistics for SPM was better with R2=0.73 and 0.87 for two evaluated algorithms, although GOCI-derived SPM overestimated low concentration and underestimated high concentration. Based on this initial match-up analysis, we made several recommendations -1) to collect more offshore under-water measurements of the Rrs data, 2) to include quality flags in level-2 products, 3) to introduce an ISRD correction in the GOCI processing chain, 4) to investigate other types of in-water algorithms such as semianalytical ones, and 5) to investigate vicarious calibration for GOCI data and to maintain accurate and consistent calibration of field radiometric instruments.

Application of the Geostationary Ocean Color Imager (GOCI) to estimates of ocean surface currents

The Geostationary Ocean Color Imager (GOCI) can be utilized efficiently to observe subtle changes in oceanic environments under cloud-free conditions because it receives ocean color images around the Korean Peninsula hourly, for 8 h a day. Here we investigated the applicability of the GOCI for estimating hourly variations in ocean surface currents, which provide significant information on seawater circulation for fisheries, shipping controls, and more. Ocean surface currents were deduced from eight images of GOCI-derived total suspended matter (TSM) from highly turbid coastal waters and images of chlorophyll concentration (CHL) for relatively clear waters. The results showed that GOCI TSM-derived ocean surface currents can effectively estimate and represent fast tidal currents, as well as flood and ebb tides on the west coast of Korea, in comparison with in situ measurements. GOCI-derived CHL scenes successfully illustrated currents moving along boundaries where warm and cold seawaters mix, in addition to mesoscale currents such as the East Korea Warm Current (EKWC) in the East Sea of Korea. Satellite-based sea surface temperature and sea surface height images supported the reliability of GOCI-derived ocean surface currents in the East Sea.

Quantitative estimation of suspended sediment movements in coastal region using GOCI

ABSTRACT Choi, J. K., Hyun Yang, H. J. Han, Ryu, J. H. and Park, Y.J., 2013. Quantitative estimation of the suspended sediment movements in the coastal region using GOCI The Geostationary Ocean Color Imager (GOCI), the worlds first geostationary ocean color observation satellite, is useful for monitoring the temporal dynamics of coastal water turbidity because it can obtain satellite images every hour during the daytime. Temporal variation in turbidity is the key to understanding sediment dynamics in coastal regions. For example, a certain patch of suspended sediment in surface water can be traced every hour by generating a GOCI- derived map of suspended sediment concentration (SSC). By calculating the variations in the position of the patch every hour quantitatively, we can obtain information on the current movement in the region quantitatively. Here, we investigate the applicability of GOCI data to monitoring of the temporal movement of suspended sediment in coastal areas and to the development of algorithms for calculating the current speed and direction. Our study was performed in areas near Gyeonggi Bay on the mid-west coast of the Korean Peninsula. Field work was performed to obtain in situ measurements of SSC and optical properties of the water surface. These data could then be combined to derive an SSC algorithm based on the relationship between the SSC and remote sensing reflectance (Rrs) values. We calculated the suspended sediment movement from hourly SSC images. Current velocity and direction were also measured in the field to validate and identify the calculated movement. GOCI images acquired on the same day as the samples were used to generate a map of turbidity and to estimate the differences in SSC displayed in each image. We found that GOCI could be effectively used to monitor the temporal dynamics of the turbidity of coastal waters, i.e., sediment movements driven by currents along the west coast of the Korean Peninsula. Sediment movements can be applied to develop GOCI-based algorithms that calculate current velocities and generate maps of current vectors in this coastal area.

Prelaunch characterization of the Geostationary Ocean Color Imager

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.

PRELIMINARY VERIFICATION RESULTS OF THE GEOSTATIONARY OCEAN COLOR SATELLITE DATA PROCESSING SOFTWARE SYSTEM

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 equipments 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.

Development of the GOCI data processing system and establishment of Korea Ocean Satellite Center

The Worlds 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.

Application of Geostationary Ocean Color Imager Data to the extraction of ocean fronts

ABSTRACT We attempted for the first time to extract fronts from ocean colour data acquired at a geostationary orbit derived from the Geostationary Ocean Color Imager (GOCI), the world’s first geostationary ocean colour satellite sensor. We extracted fronts from hourly observed GOCI images and then attempted to investigate subtle changes in ocean condition. Suspended sediment (SS)-derived fronts were used to analyse tidal movements in a coastal region having semi-diurnal tides and highly turbid water. We were able to trace fast movements of tidal flows and discovered that the SS-derived ocean fronts are quite relevant to the submarine topography along shallow coasts. In relatively clear waters using chlorophyll concentration (chl)-derived fronts, we were able to discover dynamic variations on sea areas where two independent water masses mixed. We also found that GOCI-derived fronts can provide more detailed information than can SST-derived fronts. We expect that such results can be utilized to search for productive fisheries.

Preleminary analysis of data processing for geostationary ocean color remote sensing data from GOCI/COMS

The communication, ocean and meteorological satellite (COMS) was launched in 26 June 2010. The geostationary ocean color imager (GOCI), one of the three payloads of COMS, will be examined with its data processing system during in-orbit test (IOT). The GOCI data processing system (GDPS) has been verified in code level and function level and system level in each software development phase. GDPS will check the accuracy and performance of the processing by real-time data processing for the generation of reliable ocean color remote sensing data during IOT. By analysis the result, the deeply verification and modification of data processing algorithm and the configuration will be needed. GDPS will be released to public user as basic data processing software of GOCI/COMS.

Analysis anomaly during trial test and in-orbit test to set up stabilized operation of GOCI

The worlds 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.