• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2001.02a
• /
• pp.12-1-12-7
• /
• 2001

• Journal of the korean society of oceanography
• /
• v.36 no.4
• /
• pp.101-108
• /
• 2001

Polybrominated diphenylether (PBDEs) congeners, 2,4,4'-TrBDE, 2,2',4,4'-TeBDE, 2,2',4,4',5-PeBDE, 2,2',4,4',5,5'-HXBDE, and 2,2',4,4',5,6-HxBDE, were measured in sediments from 52 stations in the southeastern coastal areas of Korea. Sediment samples were analyzed using gas chromatography coupled to mass spectrometer detector (GC/MSD) with positive electron impact (PEI) mode. New analytical methodology for PBDEs by the isotope dilution method was established using a multi-layer silica gel column chromatography. Total PBDEs levels in sediments for Pohang coast ranged from 1,1 to 33.8 ng/g dry weight (mean 5.3 ng/g dry), from 1.6 to 36.4 ng/g dry weight (mean 5.7 ng/g dry) for Ulsan coast, from 0.8 to 20.3 ng/g dry weight (mean 4.9 ng/g dry) for Busan coast, and from 0.8 to 10.3 ng/g dry weight (mean 4.4 ng/g dry) for Jinhae Bay. PBDEs contamination in surface sediments from Korean southeastern coasts was relatively moderate in comparison to that of other marine environment in the world. The predominant PBDE congeners were 2,2',4,4'-TeBDE and 2,2',4,4',5-PeBDE.

• Journal of Environmental Impact Assessment
• /
• v.29 no.2
• /
• pp.112-121
• /
• 2020

Organic pollution due to coastal development increases the distribution of organic pollution indicators (OPI) and disturbs benthic ecosystems by increasing the number of organic pollution indicators dominant in the target area. However, there is a little researches on the organic pollution levels of benthic ecosystems in subtidal target coast of all over Korea. Therefore, this study analyzed the distribution of macrobenthos in subtidal around the coast development sites of EIA, confirmed the distribution of OPI, and produced the benthic health index-map (organic pollution level) of all coasts of Korea. The benthic health index of the sites was calculated using the density of each OPI, and the image program was used for the benthic health index-map. Organic pollution levels varied by projects for EIA and OPI. Lumbrineris sp. was found to be dominant throughout the coast and correlated with the benthic health index in Korea. Through this study, we will be able to confirm the future organic pollution level in the subtidal ecosystems of the project for EIA through the results of research to macrobenthos in subtidal for EIA. In addition, the distribution of Lumbrineris sp. OPI can be used as an indicator to indirectly evaluate the organic pollution level of the development site.

• Proceedings of KOSOMES biannual meeting
• /
• 2017.11a
• /
• pp.75-75
• /
• 2017

• Journal of Environmental Science International
• /
• v.23 no.9
• /
• pp.1551-1562
• /
• 2014

To clarify the characteristics of TKE (Turbulence Kinetic Energy) variation for offshore wind power development, several numerical experiments using WRF were carried out in three different coastal area of the Korean Peninsula. Buoyancy, mechanical and shear production term of the TKE budget are fundamental elements in the production or dissipation of turbulence. Turbulent kinetic energy of the south coast region was higher than in other sea areas due to the higher sea surface temperature and strong wind speed. In south coast region, strong wind passing through the Korea Strait is caused by channelling effect of the terrain of the Geoje Island. Although wind speed is weak in east coast, because of large difference in wind speed between the upper and lower layer, the development of mechanical turbulence tend to be predominant. Since lower sea surface temperature and smaller wind shear were detected in west coastal region, the possibility of turbulence production not so great in comparison with other regions. The understanding of the characteristics of turbulence in three different coastal region can be reduced the uncertainty of offshore wind construction.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.19 no.4
• /
• pp.352-358
• /
• 2013

The objective of this paper is to introduce on a mobile APP called MAMIS(Marine pollution Accident response Mobile Information System) and it's functions. MAMIS was developed by Korea Coast Guard for marine pollution responder in 2012. Users can get information on marine pollution response easily without being restricted by time and place. MAMIS can be operated by smart phones with Android OS and iOS, both of which are the most popular mobile operating systems in Korea. And it has been developed in the form of hybrid APP which combined the functions of mobile APP and mobile WEB. MAMIS is composed of 9 menus, 5 mobile-based ones and 4 web-based ones. The mobile-based menus are on substance information, clean-up skills, response measures, QR code scanning, and volunteer's safety, and the web-based ones on weather information, response equipment, clean-up materials, and SNS.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.32 no.6
• /
• pp.803-808
• /
• 1999

Trend of sea level change has been analysed by using the tidal data gathered at the 12 tide stations along the coast of Korean peninsula. Analysis and prediction of the sea level change were performed by Principal Component Analysis (PCA). For the period of 20 years from 1976 to 1995, the trend generally shows a rising pattern such as 0.22 cm/yr, 0.29 cm/yr, and 0.59 cm/yr along the eastern, southern, and western coast of Korea, respectively. On the average the sea level around the Korean peninsula seems to be rising at a rate of 0.37 cm/yr. Adopting the average rate to the sea level prediction model proposed by EPA (Titus and Narrayanan, 1995), the sea level may be approximately 50$\~$60 cm higher than the present sea level by the end of the next century.

• Proceedings of KOSOMES biannual meeting
• /
• 2017.11a
• /
• pp.128-128
• /
• 2017

• Journal of Fisheries and Marine Sciences Education
• /
• v.16 no.2
• /
• pp.227-237
• /
• 2004

Recently development trends in information technology expand the activity boundaries for human living beyond coastal zones. These rapid changes of paradigm are stimulating scientists and strategists to be encouraged in making adequate model for marine geographic information system (MGIS) and their applications. Coastal zones are places which are affected by many factors, such as water quality, tide, wave, atmosphere, population, industry, etc. Therefore information related to the coast has to be integrated and analyzed for managing it efficiently. GIS-based Ocean Informatics is suited for those purposes and used in the study for establishing and managing coastal geographic and environmental information system. This paper reviews the properties of ocean and coastal spaces, then defines some MGIS related terminologies for clarifying the scope of MGIS boundaries. In this study, coastal geographic information is established by digital geographic information and digital terrain information. Digital coast chart having information on digital chart and map can merge and analyze various coastal information and can be a useful tool for the coastal integrated management.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.68 no.1
• /
• pp.153-158
• /
• 2019

In this paper, we analyze the infrared feature for the small coast targets according to the surrounding environment for autonomous flight device equipped with an infrared imaging sensor and we propose Cross Duality of Neural Network (CR-DuNN) method which can classify the target and clutter in coastal environment. In coastal environment, there are various property according to diverse change of air temperature, sea temperature, deferent seasons. And small coast target have various infrared feature according to diverse change of environment. In this various environment, it is very important thing that we analyze and classify targets from the clutters to improve target detection accuracy. Thus, we propose infrared feature learning algorithm through LSTM neural network and also propose CR-DuNN algorithm that integrate LSTM prediction network with Du-CNN classification network to classify targets from the clutters.