• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.567-580
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• 2016

In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.307-314
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• 2011

This study proposed detection method of Marine debris using unmanned aerial photography. For unmanned aerial photography, a RC(Radio Control) helicopter which has good movability and economics was used. To a camera mounting, a gimbal equipment was attached to the bottom of the RC helicopter. The gimbal equipment is very useful because it is not seriously affected by vibration and rolling. In addition, we invented that digital image processing algorithm using Matlab program for detection of marine debris from photographs. Particularly, background subtraction in invented algorithm was applied. As a result, marine debris of a variety of forms from different sand states of coast were reliably detected. In the future, monitoring using proposed method was expected to contribute that the solution to representative problem of monitoring area selecting and estimate the total litter mass over the beach. Moreover, It is considered a greater application possibility to marine environmental observations.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.55-66
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• 2007

There has been increasing concerns regarding marine mineral resources as the land energy resources has been depleting from worldwide energy crisis. Also, all the coastal countries around the world are getting into the high competition as EEZ implemented to widen each country's marine autonomy. Especially, the adoption of EEZ in UN's marine regulation agreement at the January of 1996 has aggravated conflicts among coastal countries and eventually resulted in critical agenda to determine the boundaries of EEZ among such countries. It is imperative for us to have negotiation with neighboring countries to determine the boundaries of EEZ. For the preparation of such negotiation, it is essential to have data such as mineral distribution, deep-sea geology, related agreement and marine laws, etc. Therefore, this study mainly concentrates on analyzing existing data of resources exploration and establishing standards for each type of data and manipulating data based on such standards, thereby building a database for more efficient management of EEZ data from marine resources survey. MRIS has also been developed to diversely analyze and visualize graphic and attribute data considering data usage and inter-relationship in the database. This system can provide various spatial analysis and spatial searching techniques to enable easier comparison of cost-benefit analysis and data provision of any area in EEZ thereby facilitating major policy making. In addition, the system can support sustainable management of marine resources of EEZ regions and data supply for systematic management of national marine resources. Furthermore, this will be very useful for negotiating with neighboring countries to determine EEZ boundaries to lead more favorable results.

• Journal of Environmental Impact Assessment
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• v.29 no.2
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• pp.122-131
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• 2020

Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.2
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• pp.123-129
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• 2011

A study on the occurrence and movement of marine debris is required for protecting the marine environment and ecosystem from marine pollution. The aim of this study is to show annual production and movement characteristics through analysis for the flow path, composition and the sources of marine debris. This study analyzed the distribution and characteristics of marine debris collected in the region of $100\;m{\times}20\;m$($=2,000\;m^2$) at the Daekwang Beach in the Yellow Sea. During the collection period from 2008 to 2010, the total weight of the marine debris was 1,445 kg in this site. The most marine debris was plastic amounting to 46.5% of the whole collection; the rest were styrofoam(20%) and wooden material(12.6%). The amount of marine debris mused from foreign country observed 155.5 kg, more than 90% of them was plastic came from China such as buoys. Additionally, this study analyzed seasonal change if marine environment to understand occurrence amount change if marine debris. 2009 and 2010 was high occurrence ratio in season that the north wind is very strong and the occurrence rate appeared highest by 40% in the summer(July) of 2008 that appeared westbound tidal current. Overall, marine Debris mused from foreign country was high occurrence ratio in January, May and then November has a lot of quantity secondly. While, occurrence ratio was the highest by 46% summer(July) in 2008, but in 2009 and 2010 showed the lowest rate to 4%.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.875-883
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• 2023

In this letter, we used PlanetScope imagery to conduct experiments on the color characteristics for oil type classification of marine oil spills through Red-Green-Blue (RGB) histogram analysis. The histograms of marine oil spills can be divided into three categories (dark black tones, light silver tones, and light rainbow tones) according to the distribution of pixel values in each band. Thick oil layers with dark black tones can be classified as heavy oil, while thin oil layers with light silver and rainbow tones can be classified as light oil. As more images are analyzed in the future, these oil spill detection and classification methods will become more generalized and reliable.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1E
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• pp.31-39
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• 2004

Backscattered underwater signals from multiple scatterers contain information regarding resolvable spatial distribution of scatterers. This experimental study describes the spectral characteristics of backscattered signal from multiple scatterers, which are regularly or randomly spaced, in terms of their amplitude and phase and a proper signal analysis that will eventually provide scatterer spacing estimation. Air-filled tubes suspended in water, steel balls and plastic tubes buried in the sediment are the multiple scatterers. The cepstrum and the spectral autocorrelation (SAC) methods were used to estimate the scatterer spacing from the backscattered signals. It was found that the SAC method could be improved by employing singular value decomposition (SVD) to extract the effective rank for the spectral components. Unlike the conventional method of estimating the density of scatterers within the insonified volume of water, this type of estimation method would provide better understanding of the spatial distribution of scatterers in the ocean.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Ocean and Polar Research
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• v.28 no.3
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• pp.225-236
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• 2006

Seagrass meadows are considered as critical habitats for a wide variety of marine organisms in coastal and estuarine ecosystems. In many cases, studies on the spatial/temporal distribution of seagrass have depended on direct observations using SCUBA diving. As an alternative method fur studying seagrass distribution, an application of hydroacoustic technique has been assessed for mapping seagrass distribution in Dongdae Bay, on the south coast of Korea, in September 2005. Data were collected using high frequency transducer (420 kHz split-beam), which was installed with towed body system. The system was linked to DGPS to make goo-referenced data. Additionally, in situ seagrass distribution has been observed using underwater cameras and SCUBA diving at four stations in order to compare with acoustic data. Acoustic survey was conducted along 23 transects with 3-4 blot ship speed. Seagrass beds were vertically limited to depths less than 3.5m and seagrass height ranged between 55 and 90cm at the study sites. Dense seagmss beds were mainly found at the entrance of the bay and at a flat area around the center of the bay. Although the study area was a relatively small, the vertical and spatial distributions of the seagrass were highly variable with bathymetry and region. Considering dominant species, Zostera marina L., preliminary estimation of seagrass biomass with acoustic and direct sampling data was approximately $56.55g/m^2$, and total biomass of 104 tones (coefficient variation: 25.77%) was estimated at the study area. Hydroacoustic method provided valuable information to understand distribution pattern and to estimate seagrass biomass.