• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.4
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• pp.280-286
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• 2011

In this research, the oil detection method and the characteristic of sensor using the selective reaction of silicone rubber in response to hydrocarbon oil will be described. As a sensing principle, the swelling property of silicone rubber in response to hydrocarbon fuel is used, also a strain gauge is used to transduce the volume change to an electrical signal. The sensor core is manufactured with a strain gauge embedded in silicone rubber by the curing process and experiments for characteristics of sensor core with various oils were carried out. It is shown that the sensor core can be used as an oil spill detection sensor. Also, for the application to the sea area, a buoy type sensor platform is integrated with a sensor core and a strain amplifier and it is tested in the simulated oil spill condition. In this study, it is proven that the integrated sensor can be used for the detection of various oils.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.9-10
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• 2009

해상에서 선박사고에 의한 기름 유출 시, 기름의 위치, 변화과정, 이동 특성을 신속하게 파악하고 예측하는 것은 방제전략에 있어 필수적 요소이다. 따라서 사고 이후의 유출의 현황 정보의 수집은, '유출유 대응 매뉴얼'(IMO, 1988; ITOPF, 2008) 에서 가장 우선시 되고 있다. 일반적으로 유출유 탐지는 선박, 항공기 및 인공위성을 이용한 방법이 사용되고 있으며, 최근 인공위성기술의 발전에 따라, 국제유조선선주오염방지연맹(ITOPF)에서는 인공위성 원격탐사 기술 적용을 통한 유류 모니터링 적용을 권장하고 있다 (ITOPF, 2008). 허베이스피리트호 원유유출 사고는 2007년 12월 7일 아침 7시 6분경 서해안 만리포 북서쪽 10km 해상에서 크레인을 적재한 1만1800t급 바지선이 정박 중인 홍콩 선적 유조선 허베이 스피리트호(14만6000t급)와 부딪치면서 발생했다. 국내에서는 원격탐사를 이용한 기술지원체계가 갖춰져 있지 않기 때문에, 이번 사고의 경우에도 실질적인 지원이 이루어지지 못했다. 본 연구에서는 원격탐사에 의한 유류오염 사고 시 유출유 탐지 및 추출 그리고 정보의 가시화 좌표화를 통해서 실질적인 방제지원시스템을 개발하기 위한 연구 개발의 중간보고를 하기 위한 것이다.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.4
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• pp.323-329
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• 2012

In this study, a new optical method for oil detection using an analysis the light-absorption image of separate oil-water mixture with a LED illumination is described. To obtain an information about the presence of oil on water and the thickness of oil, the intensity of light-absorption images acquired through CCD is analyzed. To select the optimal wavelength of the light source, the experiment is conducted using several LEDs having four different wavelength. In the case of using a blue LED having 465 nm wavelength, an intensity decreasing tendency of light-absorption image is obvious and clear. To identify the applicability of sensing system at the real sea condition, experiments are conducted as varying the brightness and water surface angle. Through this research, new optical oil detection methodology is proposed using the absorption difference between water and oil with single-wavelength LED and CCD.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1623-1631
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• 2022

Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.416-419
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• 2014

스미싱(SMiShing) 공격은 문자메시지(SMS)를 이용하여 정보를 유출하거나 타인에게 피해를 주는 행위를 일컫는다. 본 논문에서는 공격자의 공격유형에 따라 스미싱을 "직접 정보 유출", "파밍/피싱 사이트 유도", "악성어플리케이션 다운로드 유도"로 분류하였고 스미싱 공격의 시나리오를 통해 스미싱 공격을 표현하였다. 그 후 스미싱 방지 기술 동향을 파악을 위한 기존의 대응 기법들을 조사를 하고 기존의 스미싱 탐지 기법인 URL 검사와 APK 파일 분석 기법을 접목시킨 스미싱 탐지 모델을 제안한다.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.311-323
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• 2023

Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.4
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• pp.304-309
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• 2015

To evaluate the degree of contamination caused by oil spill accident in the sea, the in-situ sensors which are based on the scientific method are needed in the real site. The sensors which are based on the fluorescence detection theory can provide the useful data, such as the concentration of oil. However these kinds of sensors commonly are composed of the ultraviolet (UV) light source such as UV mercury lamp, the multiple excitation/emission filters and the optical sensor which is mainly photomultiplier tube (PMT) type. Therefore, the size of the total sensing platform is large not suitable to be handled in the oil spill field and also the total price of it is extremely expensive. To overcome these drawbacks, we designed the fluorimeter for the oil spill detection which has compact size and cost effectiveness. Before the detail design process, we conducted the experiments to measure the excitation and emission spectrum of oils using five different kinds of crude oils and three different kinds of processed oils. And the fluorescence spectrometer were used to analyze the excitation and emission spectrum of oil samples. We have compared the spectrum results and drawn the each common spectrum regions of excitation and emission. In the experiments, we can see that the average gap between maximum excitation and emission peak wavelengths is near 50 nm for the every case. In the experiment which were fixed by the excitation wavelength of 365 nm and 405 nm, we can find out that the intensity of emission was weaker than that of 280 nm and 325 nm. So, if the light sources having the wavelength of 365 nm or 405 nm are used in the design process of fluorimeter, the optical sensor needs to have the sensitivity which can cover the weak light intensity. Through the results which were derived by the experiment, we can define the important factors which can be useful to select the effective wavelengths of light source, photo detector and filters.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.