Assessment of GOCI radiometric products using MERIS, MODIS and field measurements

The first Geostationary Ocean Color Imager (GOCI) launched by South Korea in June 2010 constitutes a major breakthrough in marine optics remote-sensing for its capabilities to observe the diurnal cycles of the ocean. The light signal recorded at eight wavelengths by the sensor allows, after correction for Solar illumination and atmospheric effects, the retrieval of coloured biogeochemical products such as the chlorophyll, suspended sediment and coloured dissolved organic matter concentrations every hour between 9:00 am and 4:00 pm local time around the Korean peninsula. However operational exploitation of the mission needs beforehand a sound validation of first the radiometric calibration, i.e. inspection of the top-of-atmosphere reflectance, and second atmospheric corrections for retrieval of the water-leaving reflectance at sea surface. This study constitutes a contribution to the quality assessment of the GOCI radiometric products generated by the Korea Ocean Satellite Center (KOSC) through comparison with concurrent data from the MODerate-resolution Imaging Spectroradiometer (MODIS, NASA) and MEdium Resolution Imaging Spectrometer (MERIS, ESA) sensors as well as in situ measurements. These comparisons are made with spatially and temporally collocated data. We focus on Rayleigh-corrected reflectance (?? _RC ) and normalized remote-sensing marine reflectance (nRrs). Although GOCI compares reasonably well with MERIS and MODIS, what demonstrates the success of Ocean Colour in geostationary orbit, we show that the current GOCI atmospheric correction systematically masks out data over very turbid waters and needs further examination and correction for future release of the GOCI products.     

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?C2011, with a focus on remote-sensing reflectance (R _rs ). 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 R _rs data. This selection process yielded 32 optimal match-ups for the R _rs 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 R _rs match-ups showed the mean relative errors of 18?C33% for the visible bands with the lowest 18?C19% for the 490 nm and 555 nm bands and 33% for the 412 nm band. Correlation for the R _rs match-ups was high in the 490?C865 nm bands (R²=0.72?C0.84) 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 R _rs . 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 R _rs 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.     

Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)

This paper describes an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation. This algorithm was implemented in GOCI Data Processing System (GDPS) version 1.1. The algorithm is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of turbid case-2 water correction, optimized aerosol models, and solar angle correction per slot. For turbid water correction, we used a regional empirical relationship between water reflectance at the red (660 nm) and near infrared bands (745 nm and 865 nm). The relationship was derived from turbid pixels in satellite images after atmospheric correction, and processed using aerosol properties derived for neighboring non-turbid waters. For validation of the GOCI atmospheric correction, we compared our results with in situ measurements of normalized water leaving radiance (nL _w ) spectra that were obtained during several cruises in 2011 around Korean peninsula. The match up showed an acceptable result with mean ratio of the GOCI to in situ nL _w (??), 1.17, 1.24, 1.26, 1.15, 0.86 and 0.99 at 412 nm, 443 nm, 490 nm, 555 nm, 660 nm and 680 nm, respectively. It is speculated that part of the deviation arose from a lack of vicarious calibration and uncertainties in the above water nLw measurements.     

Continuous Observation of Groundwater and Crustal Deformation for Forecasting Tonankai and Nankai Earthquakes in Japan

In 2006, we started construction of an observation network of 12 stations in and around Shikoku and the Kii Peninsula to conduct research for forecasting Tonankai and Nankai earthquakes. The purpose of the network is to clarify the mechanism of past preseismic groundwater changes and crustal deformation related to Tonankai and Nankai earthquakes. Construction of the network of 12 stations was completed in January 2009. Work on two stations, Hongu-Mikoshi (HGM) and Ichiura (ICU), was finished earlier and they began observations in 2007. These two stations detected strain changes caused by the slow-slip events on the plate boundary in June 2008, although related changes in groundwater levels were not clearly recognized.     

Deep-learning based projection of change in irrigation water-use under RCP 8.5

Stream water-use is essential for both agricultural and hydrological management and yet not many studies have explored its non-stationarity and nonlinearity with meteorological variables. This study proposed a deep-learning based model to estimate agricultural water withdrawal using hydro-meteorological variables, which projected the changes of agricultural water withdrawal influenced by climate change of future. The relationships between meteorological variables and stream water-use rate (WUR) were quantified using a deep belief network (DBN). The influences of precipitation, potential evapotranspiration, and monthly averaged WUR on the performance of the developed DBN model were tested. As a result, this DBN with potential evapotranspiration (PET) provided better performances than precipitation to estimate the WUR. The PET of multi-model scenarios for Representative Concentration Pathways 8.5 would be increased as time goes by, and thus leads to increase WUR estimated by DBN in three basins, located in South Korea during the future period. On the contrary, water availability expected to decrease compared to the current. Therefore, managing water-uses and improving efficiencies can be prepared for the change in agricultural water-use by climate change in the future.     

A study of igneous rocks related to Zn–Pb mineralization in the Shinyemi and Gagok deposits of the Taebaeksan Basin,South Korea

The Shinyemi and Gagok deposits, located in the Taebaeksan Basin, South Korea, display Zn–Pb mineralization along a contact between Cretaceous granitoids and Cambrian–Ordovician carbonates of the Joseon Supergroup. The Shinyemi mine is one of the largest polymetallic skarn‐type magnetite deposits in South Korea and comprises Fe and Fe–Mo–Zn skarns, and Zn–Cu–Pb replacement deposits. Both deposits yield similar Cretaceous mineralization ages, and granitoids associated with the two deposits displaying similar mineral textures and compositions, are highly evolved, and were emplaced at a shallow depth. They are classified as calc‐alkaline, I‐type granites (magnetite series) and were formed in a volcanic arc. Compositional variation is less in the Shinyemi granites and aplites (e.g., SiO₂ = 74.4–76.6 wt% and 74.4–75.1 wt%, respectively) than in the Gagok granites and aplites (e.g., SiO₂ = 65.6–68.0 wt% and 74.9–76.5 wt%, respectively). Furthermore, SiO₂ vs K/Rb and SiO₂ vs Rb/Sr diagrams indicate that the Shinyemi granitoids are more evolved than the Gagok granitoids. Shinyemi granitoids had been already differentiated highly in deep depth and then intruded into shallow depth, so both granite and aplite show the highly evolved similar chemical compositions. Whereas, less differentiated Gagok granitoids were separated into two phases in the last stage at shallow depth, so granite and aplite show different compositions. The amounts of granites and aplite are similar in the Shinyemi deposit, whereas the aplite appears in an amount less than the granite in the Gagok deposit. For this reason, the Shinyemi granitoids caused not only Fe enrichment during formation of the dolomite‐hosted magnesian skarn but also was associated with Mo mineralization in the Shinyemi deposit. Zn mineralization of the Gagok deposit was mainly caused by granite rather than aplite. Our data suggest that the variation in mineralization displayed by the two deposits resulted from differences in the compositions of their associated igneous intrusions.     

Centrifuge modeling of disconnected piled raft using vertical pushover tests

Acta Geotechnica - A disconnected piled raft (DPR) foundation has been introduced as an effective pile design to reduce the vertical loading experienced by the pile. The characterization of DPRs...     

Protective effects of Ecklonia cava extract on the toxicity and oxidative stress induced by hair dye in in-vitro and in-vivo models

Oxidative hair dyes containing p-phenylenediamine(PPD) are reported to induce an allergic reaction by promoting oxidative stress when absorbed through the skin. Despite the associated risk, these hair dyes remain popular owing to their convenience and sharpness of color. This makes it important to minimize the cytotoxicity and oxidative stress induced by PPD-containing hair dyes. Ecklonia cava extract has been evaluated in different studies for its protective effects against external stress in fibroblasts and keratinocytes. Our study was aimed at using in-vitro and in-vivo models to investigate the extract's effects on cytotoxicity of and oxidative stress induced by PPD-containing hair dyes. Analysis of CIEL*a*b* Color space was first used to determine the range of E. cava extract that would not interfere with the coloring ability of the dye upon addition. Subsequently, the set ranges of E. cava extract(5% and 7%) were added to the hair dye and their toxicity assessed by evaluating the viability of fibroblasts and keratinocytes. The effects on developmental phenotypes and induction of oxidative stress by hair dye were evaluated and compared with those of hair dyes containing different contents of E. cava extract using an in-vivo zebrafish model. Our results showed that E. cava extract in hair dye could significantly decrease the cytotoxicity and levels of oxidative stress caused by hair dyes containing PPD in both in-vitro and in-vivo models.These results suggest that the addition of 7% E. cava extract to 250 μg/mL hair dye does not interfere with the coloring ability of the dye while showing significant protective effects against the hair dye. The study proposes that the use of E. cava extract as an adduct to hair dyes containing PPD reduces the cytotoxicity and oxidative stress induced by these hair dyes.     

Spatial variations of small phytoplankton contributions in the Northern Bering Sea and the Southern Chukchi Sea

Phytoplankton size classes (hereafter, PSCs) were derived from satellite ocean color data using a present phytoplankton abundance-based optical algorithm in the northern Bering and southern Chukchi Seas to characterize the spatial and seasonal variations of the different PSC and investigate the contributions of small phytoplankton to the total phytoplankton biomass. The comparison results showed that the phytoplankton abundance-based method approach could reasonably classify the three PSCs (pico-, nano-, and micro phytoplankton). The satellite maps of the dominant PSCs were derived using long-term satellite ocean color data. The general spatial distribution showed that the large (micro-) phytoplankton were dominant in the coastal waters and the west side of the Bering strait, while the small size (nano- or pico-) phytoplankton were dominant in the open ocean waters. Nano- and microphytoplankton were dominant in May and October in most of the study area, while pico-phytoplankton were dominant in the summer months in the open ocean waters. The annual variation in small phytoplankton dominance had a strong positive relationship with the annual mean sea surface temperature (SST), which is consistent with the increasing dominance of small phytoplankton biomass as water temperature increases. Microphytoplankton have an apparent increasing trend in the southeastern Chukchi Sea but slightly decreasing trends in Chirikov and St. Lawrence Island Polynya (SLIP). In contrast, there were increasing trends in picophytoplankton in Chirikov and SLIP, which seems to be related to increasing annual SST. It is crucial to monitor changes in dominant groups of phytoplankton community in the Bering and Chukchi Seas as important biological hotspots responding to the recent changes in environmental conditions.