• Journal of the Korean earth science society
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• v.41 no.6
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• pp.599-616
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• 2020

Sea-surface temperature (SST) is one of the most important oceanic variables for understanding air-sea interactions, heat flux variations, and oceanic circulation in the global ocean. Extremely low SSTs from 0℃ down to -2℃ should be more important than other normal temperatures because of their notable roles in inducing and regulating global climate and environmental changes. To understand the temporal and spatial variability of such extremely low SSTs in the global ocean, the long-term SST climatology was calculated using the daily SST database of satellites observed for the period from 1982 to 2018. In addition, the locations of regions with extremely low surface temperatures of less than 0℃ and monthly variations of isothermal lines of 0℃ were investigated using World Ocean Atlas (WOA) climatology based on in-situ oceanic measurements. As a result, extremely low temperatures occupied considerable areas in polar regions such as the Arctic Ocean and Antarctic Ocean, and marginal seas at high latitudes. Six earth science textbooks were analyzed to investigate how these extremely low temperatures were visualized. In most textbooks, illustrations of SSTs began not from extremely low temperatures below 0℃ but from a relatively high temperature of 0℃ or higher, which prevented students from understanding of concepts and roles of the low SSTs. As data visualization is one of the key elements of data literacy, illustrations of the textbooks should be improved to ensure that SST data are adequately visualized in the textbooks. This study emphasized that oceanic literacy and data literacy could be cultivated and strengthened simultaneously through visualizations of oceanic big data by using satellite SST data and oceanic in-situ measurements.

• Maritime Security
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• v.1 no.1
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• pp.93-117
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• 2020

Four cargo ships were ambushed by bombs in 2019 while navigating in the Strait of Hormuz. It was not clear who attacked those ships, however, many nations including the United States argued that it was Iran due to several reasons. The United States established the maritime collective defense system named International Maritime Security Construct (IMSC) in order to protect the maritime security in the Strait of Hormuz, without disclosure against whom it is aimed. Persian, who uses the Persian language unlike other countries in the Middle East, is the major ethnic group in Iran, and most of them believe Shi'ah Islam while most of the Arabs in the Gulf countries adhere to Sunni Islam. It seems that historic and religious motives caused the bipolar system in the Middle East, however, it is plausible to analyze the system of international affairs in the Middle East via defensive or structural realism. Iran has attempted to maintain its hegemony in the region by supporting Shi'ah muslims in the neighboring countries as well as in the world by using military and economic means. In this context, Iran's maritime strategy is to maintain its maritime hegemony on the Persian Gulf via countering threats and cooperating with friendly navies by using the Islamic Republic of Iran Navy(IRIN) and the Islamic Revolutionary Guard Corps Navy(IRGCN). IRIN acts like other navies in the world: protecting national interest at sea, expending its operational areas to the outer seas, and enhancing cooperation with other navies. Meanwhile, IRGCN plays a role as an asymmetric force at sea. It is composed of small and fast asymmetric assets, which can ambush ships fast and furious. Considering the poor study for Iran's maritime strategy in Korea, analyzing the strategy is meaningful for the Republic of Korea Navy, which has operated the Cheonghae Unit for more than ten years since it has extended its operational area over the Strait of Hormuz. In order not to be drawn into the conflict in the Strait, research on the maritime strategy of Iran and other countries in the Middle East should be started.

• Atmosphere
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• v.30 no.4
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• pp.439-454
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• 2020

This study investigates the change in the fine particulate matter (PM2.5) concentration and World Health Organization (WHO) air quality index (AQI) in East Asia (EA) under Shared Socioeconomic Pathways (SSPs). AQI is an indicator of increasing levels about health concern, divided into six categories based on PM2.5 annual concentrations. Here, we utilized the ensemble results of UKESM1, the climate model operated in Met Office, UK, for the analysis of long-term variation during the historical (1950~2014) and future (2015~2100) period. The results show that the spatial distributions of simulated PM2.5 concentrations in present-day (1995~2014) are comparable to observations. It is found that most regions in EA exceeded the WHO air quality guideline except for Japan, Mongolia regions, and the far seas during the historical period. In future scenarios containing strong air quality (SSP1-2.6, SSP5-8.5) and medium air quality (SSP2-4.5) controls, PM2.5 concentrations are substantially reduced, resulting in significant improvement in AQI until the mid-21st century. On the other hand, the mild air pollution controls in SSP3-7.0 tend to lead poor AQI in China and Korea. This study also examines impact of increased in PM2.5 concentrations on downward shortwave energy at the surface. As a result, strong air pollution controls can improve air quality through reduced PM2.5 concentrations, but lead to an additional warming in both the near and mid-term future climate over EA.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of Environmental Impact Assessment
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• v.31 no.2
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• pp.95-105
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• 2022

Busan, where the coastal ecosystem health is deteriorating due to high development pressure and intensity of use, needs ecosystem management that considers humans and the natural environment together for sustainable use and ecosystem preservation of the coastal areas. In this study, the InVEST model was applied to assess the habitat status of the coastal land and coastal sea to manage the ecosystem based on habitats. As a result of the assessment of the coastal land, the habitat quality of Gadeok-do, Igidae, and Sinseondae, Gijang-gun are high, and Seo-gu, Jung-gu, Dong-gu, and Suyeong-gu are low. In the case of the coastal sea, the habitat risk of the Nakdong river estuary is low, and some areas of Yeongdo-gu, Saha-gu, Gangseo-gu are high. Therefore, for the sustainable use and preservation of coastal ecosystems, it is necessary to prepare ecosystem-based management measures to improve damaged habitats and reduce threats. In addition, the impact on coastal seas should be fully considered when planning coastal land development. The results of the InVEST habitat quality model in coastal land show similar tendencies to the biotope and environmental conservation value assessment map. The results of the habitat risk assessment in the coastal sea are expected to be utilized to identify habitats in the coastal sea and management of threat factors.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.295-307
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• 2021

The Korean Peninsula is surrounded on three sides by the East Sea, West Sea and South Sea which are connected to many rivers and streams, thereby facilitating easy inflow of debris from land. Furthermore, excessive debris inflow to the sea because of active fishing and various recreational activities. Debris entering the sea are weighted over time and settle in the seabed, thus, making direct monitoring of debris impossible and its collection difficult. Uncollected submerged marine debris affects the seabed ecosystem and water quality and can cause ghost fishing and ship accidents, especially due to waste net ropes and waste fishing gears. Therefore, understanding the debris distribution characteristics is necessary to assist quick collection of these debris (waste net ropes and waste fishing gears). Thus, this study conducted a survey of debris deposited in the seas of 39 ports. Furthermore, distribution characteristics and compositions of submerged marine debris were identified by a map prepared through GIS-based spatial analysis of the East Sea. Consequently, 58% of waste tires in the East Sea were concentrated in breakwaters and ship berthing facilities. Moreover, 26 % of waste plastics were distributed outside the port. Identifying the distinct distribution characteristics of submerged marine debris was difficult; however, compared with others, the distribution of waste plastics was possible outside the port. The findings of this study can serve as baseline data to assist the collection of submerged marine debris using the distribution characteristics.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.1-8
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• 2022

With the spread of COVID-19 worldwide, non-face-to-face services have grown rapidly, but at the same time, the problem of plastic waste is getting worse. Accordingly, eco-friendly policies such as carbon neutrality and sustainable circular economy are being promoted worldwide. Due to the high demand for eco-friendly products, the packaging industry is trying to develop eco-friendly packaging materials using PLA and PBAT and create new business models. On the other hand, Ulva australis occurs in large quantities in the southern seas of Korea and off the coast of Jeju Island, causing marine environmental problems. In this study, lactic acid was produced through dilute acid pretreatment, enzymatic saccharification, and fermentation processes to utilize Ulva australis as a new alternative energy raw material. In general, seaweeds vary in carbohydrate content and sugar composition depending on the species, harvest location, and time. Seaweed is mainly composed of polysaccharides such as cellulose, alginate, mannan, and xylan, but does not contain lignin. It is difficult to expect high extraction yield of the complex polysaccharide constituting Ulva australis with only one process. However, the fusion process of dilute acid and enzymatic saccharification presented in this study can extract most of the sugars contained in Ulva australis. Therefore, the fusion process is considered to be able to expect high lactic acid production yield when a commercial-scale production process is established.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1004-1010
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• 2021

Ship-floating object accidents can lead not only to a delay in ship's operations, but also to large scale casualties. Hence, preventive measures are required to avoid them. This study analyzed the spatiotemporal aspects of such collisions based on the data on ship-floating object accidents in sea areas in the last five years, including the collisions in South Korea's territorial seas and exclusive economic zones. We also provide basic data for related research fields. To understand the distribution of the relative density of accidents involving floating objects, the sea area under analysis was visualized as a grid and a two-dimensional histogram was generated. A multinomial logistic regression model was used to analyze the effect of variables such as time of day and season on the collisions. The spatial analysis revealed that the collision density was highest for the areas extending from Geoje Island to Tongyeong, including Jinhae Bay, and that it was high near Jeongok Port in the West Sea and the northern part of Jeju Island. The temporal analysis revealed that the collisions occurred most frequently during the day (71.4%) and in autumn. Furthermore, the likelihood of collision with floating objects was much higher for professional fishing vessels, leisure vessels, and recreational fishing vessels than for cargo vessels during the day and in autumn. The results of this analysis can be used as primary data for the arrangement of Coast Guard vessels, rigid enforcement of regulations, removal of floating objects, and preparation of countermeasures involving preliminary removal of floating objects to prevent accidents by time and season.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.1-10
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• 2022

As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m². The study is expected to play a major role in marine HNS monitoring.