• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Journal of the Korean Wood Science and Technology
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• v.36 no.6
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• pp.147-158
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• 2008

In this study, fermentation characteristics of waste agricultural and forest biomass for production of heat energy were focused to be used in agricultural farm households. The purpose of this study was focused on seeking practical utilization of agricultural and forest biomass wastes in agricultural farm households in the form of thermal energy by means of simple fermentation process. Fermentation process was performed in terms of different raw-materials and their mixture with different ratios. Urea, lime, and bioaids were added as fermenting aids. Moisture contents of fermenting substrates were adjusted to 55~65%. In order to optimize the fermentation process various factors, such as raw-materials, moisture contents, amount of fermenting aids, and practical measurement of hot-water temperature during fermentation were carefully investigated. The optimum condition of fermenting process were obtained from hardwood only and hardwood: softwood (50 : 50) beds. In case of hardwood only the highest temperature was recorded between 60 to $90^{\circ}C$ the lowest temperature was determined to more or less $40^{\circ}C$ and the average temperature was ranged to $50{\sim}60^{\circ}C$ and this temperature ranges were maintained up to 20~30 days. The optimum amount of additives were estimated to ca. 15 kg of urea, 20 kg of bioaids, and 10 kg of lime for 1 ton of substrate. To reach the highest temperature the optimum moisture content of fermenting substrate was proved to 55% among three moisture content treatments of 45%, 55% and 65%. The temperature of hot-water tank installed in fermenting bed of hardwood : grass (50 : 50) showed very different patterns according to measuring positions. In general, temperatures in the mid- and upper-parts of substrate piling were relative higher than lower and surface parts during 45-day fermentation process. The maximum temperature of fermenting stage was determined to $65^{\circ}C$, minimum temperature, more or less $40^{\circ}C$, and average temperature was $60^{\circ}C$. The water temperature of tank exit was ranged to $33{\sim}48^{\circ}C$ during whole measuring periods. It could be concluded that fermentation process of waste agricultural and forest biomass produces a considerable amounts of heat, averaging about $50{\sim}60^{\circ}C$ for maximum 3 months by using the heat exchanger (HX-helical type).

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1605-1613
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• 2023

The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R² and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.721-732
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• 2016

The accuracy and error characteristics of microwave Sea Surface Temperature (SST) measurements in the Northwest Pacific were analyzed by utilizing 162,264 collocated matchup data between GCOM-W1/AMSR2 data and oceanic in-situ temperature measurements from July 2012 to August 2016. The AMSR2 SST measurements had a Root-Mean-Square (RMS) error of about $0.63^{\circ}C$ and a bias error of about $0.05^{\circ}C$. The SST differences between AMSR2 and in-situ measurements were caused by various factors, such as wind speed, SST, distance from the coast, and the thermal front. The AMSR2 SST data showed an error due to the diurnal effect, which was much higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. In addition, the RMS error tended to be large in the winter because the emissivity of the sea surface was increased by high wind speeds and it could induce positive deviation in the SST retrieval. Low sensitivity at colder temperature and land contamination also affected an increase in the error of AMSR2 SST. An analysis of the effect of the thermal front on satellite SST error indicated that SST error increased as the magnitude of the spatial gradient of the SST increased and the distance from the front decreased. The purpose of this study was to provide a basis for further research applying microwave SST in the Northwest Pacific. In addition, the results suggested that analyzing the errors related to the environmental factors in the study area must precede any further analysis in order to obtain more accurate satellite SST measurements.

• Korean Journal of Ecology and Environment
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• v.43 no.1
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• pp.129-135
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• 2010

The relationship between rainfall variable and zooplankton dynamics was studied in the Upo wetland, an ecosystem of international importance. Water sampling was conducted on biweekly basis from January 2002 to December 2007 in the study site. The annual average of total rainfall was 1,324 mm during the study period. Total rainfall amount in 2003 (1,766 mm) was unusually high, while total rainfall amount in 2005 (975 mm) was exceptionally lower than the average. Most of basic limnological parameters (water temperature, dissolved oxygen, pH, conductivity and turbidity) in the study site were greatly influenced by the flooding events and rainfall amounts in summer. There were statistically significance between seasonal and inter-annual differences in zooplankton abundance and the total rainfall amount (ANOVA, P<0.05). Zooplankton abundance was high in summer (mean${\pm}$s.d.: $1,594{\pm}1,598\;Ind.\;L^{-1}$) and low in winter ($246{\pm}234\;Ind.\;L^{-1}$. The 47% of annual total zooplankton abundance in the study site were observed in summer. The seasonal pattern of rotifers was similar to that of total zooplankton. This reflected the fact that rotifers strongly dominated and occupied ca. 65% the total zooplankton abundance (annual mean: $398{\pm}1,139\;Ind.\;L^{-1}$, n=149), followed by cladocerans ($65{\pm}140\;Ind.\;L^{-1}$) and copepods ($58{\pm}84\;L^{-1}$). Planktonic rotifers such as Keratella cochlearis, Polyarthra spp. and Brachionus calyciflorus were dominant from winter to spring and attached rotifers such as Lecane spp., Monostyla spp. and Trichocerca spp., observed commonly from spring to fall. Among the environmental variables considered, rainfall in summer seemed to play the most important role in determining characteristics of zooplankton community dynamics in the Upo wetland.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.4
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• pp.195-204
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• 2009

In order to estimate sea surface current fields in the East Sea, we examined characteristics of mean dynamic topography (MDT) fields (or mean surface current field, MSC) generated from three different methods. This preliminary investigation evaluates the accuracy of surface currents estimated from satellite-derived sea level anomaly (SLA) data and three MDT fields in the East Sea. AVISO (Archiving, Validation and Interpretation of Satellite Oceanographic data) provides a MDT field derived from satellite observation and numerical models with $0.25^{\circ}$ horizontal resolution. Steric height field relative to 500 dbar from temperature and salinity profiles in the East Sea supplies another MDT field. Trajectory data of surface drifters (ARGOS) in the East Sea for 14 years provide another MSC field. Absolute dynamic topography (ADT) field is calculated by adding SLA to each MDT. Application of geostrophic equation to three different ADT fields yields three surface geostrophic current fields. Comparisons were made between the estimated surface currents from the three different methods and in-situ current measurements from a ship-mounted ADCP (Acoustic Doppler Current Profiler) in the southwestern East Sea in 2005. For offshore areas more than 50 km away from the land, the correlation coefficients (R) between the estimated versus the measured currents range from 0.58 to 0.73, with 17.1 to $21.7\;cm\;s^{-1}$ root mean square deviation (RMSD). For coastal ocean within 50 km from the land, however, R ranges from 0.06 to 0.46 and RMSD ranges from 15.5 to $28.0\;cm\;s^{-1}$. Results from this study reveal that a new approach in producing MDT and SLA is required to improve the accuracy of surface current estimations for the shallow costal zones of the East Sea.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.469-477
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• 2020

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s^-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.

• Journal of Wetlands Research
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• v.6 no.1
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• pp.133-147
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• 2004

Environmental quality(water and sediment) was analyzed in the tidal flat of Saemangum of Jeonbuk Province, the west coast of Korea, using the 101 sediment samples and 69 water samples collected in September 4~13, 2001. Major water quality parameters with the means of 69 surface water samples are as follows; $25.51{\pm}0.68^{\circ}C$ for water temperature, $29.88{\pm}5.01$ for salinity, $1.40{\pm}0.78mg/L$ for COD, $0.352{\pm}0.417mg/L$ for DIN, and $0.027{\pm}0.023mg/L$ for phosphate, respectively. Higher values were found at the subestuary of Dongjin and Mangyung River, and lower values at the Saemangum embayment and Gomso Bay. There was a significant negative correlation between salinity and the other water quality parameters(p<0.0001) such as COD, nutrients, SS and N/P. This correlation suggested that the major pollution sources be from terrestrial inputs through tributaries in this area. Principal component analysis clearly revealed a spatial variation of water quality; stations with higher values of nutrients and COD located subestuary of tributaries. 14 sediment quality parameters including 8 trace metals were measured using the 101 surface sediment samples. Average values for the parameters are as follows; Al $2.28{\pm}0.92%$, Cd $0.61{\pm}0.27ppm$, Cu $8.95{\pm}4.06ppm$, Fe $1.19{\pm}0.37%$, Mn $182.31{\pm}77.45ppm$, Ni $10.83{\pm}4.97ppm$, Pb $15.20{\pm}4.35ppm$, Zn $41.34{\pm}34.62ppm$, COD $2.68{\pm}1.85mg/g\;dry$, AVS $0.04{\pm}0.08mg/g\;dry$, IL $1.29{\pm}1.08%$, water content $24.11{\pm}4.49%$, TN $0.02{\pm}0.02%$, TC $0.22{\pm}0.30%$. Spatial variations of sediment quality were not clear as water quality. Some higher values were found at the subestuary of Gum River and lower values at the other area. There was a significant positive correlation between the heavy metal concentrations and organic materials within the sediment(p<0.05). Enrichment factors showed the ranges of 1~2 for most of the metals in the sediment except zinc(1~6), indicating no serious exogenous input of heavy metals in the study area. Also, the heavy metal concentrations in the sediment were within the ranges found at the natural marine environments.

• Journal of Wetlands Research
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• v.5 no.2
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• pp.15-32
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• 2003

The ecological study on seven wetlands of Haman area in Kyungsangnamdo, Korea, was carried out. In especial, the biological data of the sites were unknown. In this study, water quality including water temperature, pH, DO, COD, T-N, T-P, SS were tested. On the survey of plants and animals, vegetation and flora were investigated and the fauna of insects, fish, and amphibians were studied on each wetland. Water of wetland Oksu was heavily polluted and wetlands Pyungy and Dodulyangy were relatively clean. The water pollution was most severe in winter at all of the wetlands. Plant communities were classified into 9 natural communities and 1 artificial community. On the vegetation, wetland Sugok showed the highest plant taxa, and 41 families, 78 species and 16 varieties were classified. There was remarkable difference in number of plant taxa. The difference may be caused by the variances of wetland sizes, the influence from terrestrial environment. Wetland Sugok showed most rich insect fauna, and 10 orders, 76 families 224 species and 1082 individuals were identified. The species diversity was 2.05 and the species richness was 73.49. Wetland Ddun showed poor insect fauna, and 6 orders, 23 families, 29 species and 81 individuals were identified. Total collected fish were 4 orders, 7 families and 11 species. The fish fauna was most rich in wetlands Oksu and Pyungy, but poor in wetland Unan. Total collected amphibians were 2 orders, 3 families and 4 species.