• Proceedings of KOSOMES biannual meeting
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• 2008.05a
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• pp.125-127
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• 2008

허베이스피리트호 원유유출 사고는 2007년 12월7일 아침 7시6분경 서해안 만리포 북서쪽 10km 해상에서 크레인을 적재한 1만1800t급 바지선이 정박 중인 흥콩 선적 유조선 허베이 스피리트호(14만6000t급)와 부딪치면서 발생했다. 이와 같은 기름 유출 사고의 경우, 유출 범위를 정확하게 이해하는 것이 중요하다. 여기서는 위 사고 기간에 얻어진 인공위성 자료를 이용하여 기름 유출을 탐지하기 위한 연구결과를 소개한다. 광학과 마이로파영상에 대해 유출 범위의 계산 및 해석 알고리듬에 대한 현재까지의 결과를 소개한다. 광학영상으로는 아리랑 2호 (다목적 실용위성 2호, KOMPSAT II) MSC(Multi Spectral Camera)자료가 사용되었으며, 합성개구레이더로는 ENVISAT ASAR, TerraSAR-X 및 ALOS PALSAR의 자료가 사용되었다.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.339-349
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• 2018

The massive green tide occurred every summer in the Yellow Sea since 2008, and many studies are being actively conducted to estimate the coverage of green tide through analysis of satellite imagery. However, there is no satellite images selection criterion for accurate coverage calculation of green tide. Therefore, this study aimed to find a suitable satellite image from for the comparison of the green tide coverage according to the spatial resolution of satellite image. In this study, Landsat ETM+, MODIS and GOCI images were used to coverage estimation and its spatial resolution is 30, 250 and 500 m, respectively. Green tide pixels were classified based on the NDVI algorithm, the difference of the green tide coverage was compared with threshold value. In addition, we estimate the proportion of the green tide in one pixel through the Linear Spectral Unmixing (LSU) method, and the effect of the difference of green tide ratio on the coverage calculation were evaluated. The result of green tide coverage from the calculation of the NDVI value, coverage of green tide usually overestimate with decreasing spatial resolution, maximum difference shows 1.5 times. In addition, most of the pixels were included in the group with less than 0.1 (10%) LSU value, and above 0.5 (50%) LSU value accounted for about 2% in all of three images. Even though classified as green tide from the NDVI result, it is considered to be overestimated because it is regarded as the same coverage even if green tide is not 100% filled in one pixel. Mixed-pixel problem seems to be more severe with spatial resolution decreases.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.215-218
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• 2001

본 연구에서는 저해상도 다분광 영상으로부터 고해상도 다분광 영상을 효과적인 추출하기 위해 인공지능의 한 기법인 신경회로망을 이용하여 중합을 위한 구조를 제안하였고, IKONOS 위성 영상에 적용하여 실험 및 결과를 제시하였다. 실험 결과에서 얻어진 화상은 비교적 좋은 분광특성을 나타내었으며, 향후, 본 연구의 중합방법은 토지 이용분류, 환경감시, 자원조사 등의 많은 분야와 지형공간정보 시스템의 데이터 활용 등 여러분야 응용될 경우 우수한 성능을 제공할 것으로 사료된다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.319-320
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• 2022

해무는 해면에 인접한 층에서 수증기가 응결하여 대기 중에 부유하는 현상으로 기상학적으로 수평 가시거리가 1km이하 일때로 정의되며 해무로 인해 항공기 이착륙 지연, 교통사고, 운항 통제, 인명 피해 등 사회적, 경제적 피해를 유발하고 있다. 본 연구에서는 기존의 해무 발생, 탐지, 예측과 관련한 연구를 비교 분석하여 향후 연구개발의 방향을 제시하고자 한다. 해무 발생, 예측과 관련하여 연구개발이 진행되어 왔으나 해무의 특성상 규칙성이 약하고 고정적인 측정법이나 이를 다루기 위한 네트워크가 부족하여 예측하기가 어렵다. 특히, 국내에서는 국립해양조사원과 기상청에서 해무 탐지 및 예측에 관한 연구개발 및 서비스가 진행되고 있으나 현업화가 이루어지지 않거나 특정지점에 대한 정보만 제공되고 있는 한계가 있다. 따라서, CCTV영상, 인공위성 영상, 시정계, 기상자료, 수치모형을 통해 수집된 정보를 통합하여 예측할 수 있는 인공지능기반의 해무 탐지 및 예측 기술개발이 진행되어야 할 것이다.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.31-46
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• 1997

In recent years, as remotly-sensed image processing technologies have been improved and spread widely in the application areas, many new requirements for the image processing technologies have arisen. However, it is difficult and costly to access remotely-sensed image processing systems. Moreover, these systems have thier own processing facilities which are not easily accessible for general users. In this paper, those problems are challenged by adopting Internet as a universal information network for accessing remotly-sensed image DBMS and by allowing users to work remotely on the image processing. A remotly-sensed image processing system which can be accessed via Internet was designed and implemented. This system can be used to manipulate images over remote DBMS. The Illustra object-oriented relational DBMS with CGI(Common Gateway Interface) web interface was used in this project. The client consists of a WWW(World Wide Web) Netscap$e^{TM}$ browser, and the server consists of HTTPD(Web daemon), Illustra DBMS and Java modules in order to process the image being displayed. The developed system was tested on LAN environment and the service response time met the requirements.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.31-39
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• 2007

In this study, the hydrosphere change of the Daecheong dam basin was detected qualitatively and quantitatively using Landsat satellite images until recentness since the construction of Daecheong dam. The hydrosphere change of the basin was analyzed by applying supervised classification about Landsat satellite images which were classified according to the hydrosphere, vegetation, road and etc. for four distinct years which are 1981, 1987, 1993, and 2002 year. Landsat satellite images of each year were achieved overlay analysis with extracting only the hydrosphere, and though these results, the hydrosphere change of the Daecheong dam basin was monitored efficiently.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.35-43
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• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.221.2-221.2
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• 2012

우주물체 전자광학 감시체계(OWL: Optical Wide-field Patrol)는 관측소들의 자동운영을 통한 인공위성의 궤도정보추출이 목적이다. 이를 위해 각각의 관측소에서 매일 밤 운영되어야 하는 관측명령을 자동으로 생성하는 스케줄러를 개발하였다. 스케줄러는 OWL 본부가 설치될 한국천문연구원의 NOS(Network Operating System) 서버에 설치 운영된다. 스케줄러는 사용자가 정한 관측대상 인공위성의 관측우선순위와 OC(Orbit Calculation) 서브시스템이 제공한 위성궤도정보를 바탕으로, 시간에 따른 관측수행내용을 기록한 관측명령서(OCF: Observation Command File)를 작성한다. 작성된 OCF는 각 관측소가 관측을 시작하기 전까지 해당 관측소로 전달되며, 관측소는 OCF를 바탕으로 관측을 수행하게 된다. 스케줄러는 "제한조건반영" 및 "OCF작성" 등 2부분으로 구성된다. "제한조건반영"은 관측시스템의 특징을 스케줄러에 반영하는 단계로써 시야각 등 광학계의 특징, 필터 등 주변 장비의 특징, CCD 카메라의 노출대기시간 등 검출기의 특징 등이 이에 포함된다. 사용자는 장비의 교체 및 개선 등 관측시스템 변경이 발생하는 경우 "제한조건반영"에 이를 적용함으로써 스케줄러가 새로운 시스템에 쉽게 적용할 수 있다. "OCF작성"은 "제한조건반영"의 내용을 바탕으로 관측대상위성을 선정하는 , 위성 관측 구간 중 최대한 많은 노출 횟수를 산출하는 , 한 장의 영상에서 최대한 많은 궤도 정보를 획득하기 위한 등 3개의 알고리즘에 의해 OCF를 작성한다.