• 한국수자원학회논문집
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• 제48권5호
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• pp.409-423
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• 2015

본 연구에서는 기상레이더 자료를 이용하여 도시하천 유역을 대상으로 초단기 강우예측 및 홍수예측을 실시하였다. 초단기 강우예측 결과 선행시간이 증가함에 따라 관측 자료와의 상관계수가 감소하며, 평균제곱근오차는 증가하여 정확도가 감소하였으나, 선행시간 60분까지 상관계수가 0.5이상 유지되는 결과를 얻을 수 있었다. 또한 강우예측 자료 적용에 의한 도시유출 분석결과, 선행시간 증가에 따른 첨두유량과 유출체적의 감소가 발생하였으나, 첨두시간은 비교적 일치하는 것으로 분석되었다. 레이더 예측 강우 적용을 통한 도시유출 분석결과, 관측 자료와의 오차가 발생하나 이는 여러 가지 외부적인 요인으로 판단되며, 추후 강수 에코의 급격한 생성과 소멸현상 모의, 국지성 강우 예측 성능 향상 등 지속적인 알고리즘 개선과 강우-유출 모형 매개변수 검 보정이 필요할 것으로 사료된다. 본 연구의 결과는 도시하천 유역뿐만 아니라 관측이 어려운 미계측 지역의 수문자료 확보 및 실시간 홍수 예 경보시스템 구축에 확장이 가능하며, 다양한 관측자료 기반 Multi-Sensor 초단기 강우예측 기반기술로의 활용이 가능하다.

• 한국지구과학회지
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• 제22권3호
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• pp.186-194
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• 2001

제주 지방 기상청을 대상으로 하는 지역 규모 단시간 수치예보 시스템을 구축하였다. 기상청 본청에서 하루 2회 제공되는 30 km해상도의 수치예보 자료로는 지방 기상청의 예보관들이 우리 나라와 같이 복잡한 지형에서 발생하는 그 지역의 국지 악기상을 파악하기에는 무리가 있다. 지역 규모의 고해상도 수치예보를 위해 LAPS와 MM5를 자료분석과 예보 모델로 이용하였다. LAPS는 양질의 수치예보 초기자료를 생산해 내기 위해 종관 관측 자료뿐만 아니라 위성 및 레이더 등의 비 종관 관측자료도 자료동화에 이용한다. MM5 모델은 16노드의 펜티엄 PC로 구성된 클러스터에서 수행되었으며 이 시스템은 분산병렬 클러스터 컴퓨터로 가격대비 성능이 매우 우수한 미니 슈퍼컴퓨터이다. 자료동화 모델, 수치예보 모델 그리고 PC-클러스터를 종합한 지역 규모 단시간 수치예보 시스템을 한라 단시간 예측 시스템이라 명명하였으며 이 시스템은 현재 제주 지방 기상청에서 독자적으로 운영되고 있다. 기상청 본청에서 제공되는 수치예보 정보로는 탐지할 수 없었던 1999년 7월 9일 제주 지역의 집중호우 사례에 대하여 본 시스템을 검증한 결과 모델이 예측한 강수량이 실제 강수량을 잘 재현하였다. 한라 단시간 예측 시스템은 2000년 4월부터 하루 4회 제주 지방기상청에서 독자적으로 운영되고 있다.

• 한국측량학회지
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• 제35권4호
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• pp.319-326
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• 2017

SAR (Synthetic aperture radar) images are less affected by the weather compared to optical images and can be obtained at any time of the day. Therefore, SAR images are being actively utilized for military applications and natural disasters. However, because SAR data are in grayscale, it is difficult to perform visual analysis and to decipher details. In this study, we propose a color mapping method using RF (random forest) regression for enhancing the visual decipherability of SAR images. COSMO-SkyMed 2 and WorldView-3 images were obtained for the same area and RF regression was used to establish color configurations for performing color mapping. The results were compared with image fusion, a traditional color mapping method. The UIQI (universal image quality index), the SSIM (structural similarity) index, and CC (correlation coefficients) were used to evaluate the image quality. The color-mapped image based on the RF regression had a significantly higher quality than the images derived from the other methods. From the experimental result, the use of color mapping based on the RF regression for SAR images was confirmed.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.37-37
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• 2003

Rice is one of the most important crop in the world and is a major export of Thailand. Optical sensors are not useful for rice monitoring, because most cultivated areas are often obscured by cloud during the growing period, especially in South East Asia. Spaceborne Synthetic Aperture Radar (SAR) such as RADARSAT, can see through regardless of weather condition which make it possible to monitor rice growth and to retrieve rice acreage, using the unique temporal signature of rice fields. This paper presents the result of a study of examining the backscatter behavior of rice using multi-temporal RADARSAT dataset. Ground measurements of paddy parameters and water and soil condition were collected. The ground truth information was also used to identify mature rice crops, orchard, road, residence, and aquaculture ponds. Land use class distributions from the RADARSAT image were analyzed. Comparison of the mean DB of each land use class indicated significant differences. Schematic representation of temporal backscatter of rice crop were plotted. Based on the study carried out in Pathum Thani Province test site, the results showed variation of sigma naught from first tillering vegatative phase until ripenning phase. It is suggested that at least, three radar data acquisitions taken at 3 stages of rice growth circle namely; those are at the beginning of rice growth when the field is still covered with water, in the ear differentiation period, and at the beginning of the harvest season, are required for rice monitoring. This pilot project was an experimental one aiming at future operational rice monitoring and potential yield predicttion.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.405-409
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• 2004

We chose the Kushiro wetland in Hokkaido, Japan, as a test site to monitor wetland areas. Synthetic aperture radar (SAR) can carry out continuous observation in any weather conditions, and can therefore be used to observe high humidity areas such as wetlands. We applied multi-parameter SAR data (dual-frequency, multi-polarization, and multi-incidence angle) to monitoring the wetland forest. To find the optimum incidence angle and polarization for monitoring the wetland biomass, a simple backscattering model of wetland vegetation was developed and applied to estimate backscattering coefficients for different biomass and surface conditions.

• 한국군사과학기술학회지
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• 제13권1호
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• pp.105-113
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• 2010

SAR(Synthetic Aperture Radar) has characteristics well-suited for the measurement of geophysical parameters during day and night in all weather conditions. Recently, SAR data with high resolution acquired by satellites became available to the public. In such data, many features and phenomena of geometric structure of man-made objects and natural environments become observable. In this paper, we discuss main considerations including geometric distortion and coregistration for efficient utilization of high resolution SAR images. And, various advanced technologies in SAR application fields are introduced.

• 대한원격탐사학회지
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• 제38권1호
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.

• 한국환경과학회지
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• 제24권5호
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• pp.601-613
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• 2015

On the study of the characteristics and life cycle of mesoscale convective band in type of airmass that occurred in the Honam area from June to September for only 4 years in the period of 2009~2012, 10 examples based on the amount of rainfall with AWS 24 hours/60 minutes rainfalls, Mt. Osung radar 1.5 km CAPPI/X-SECT images and KLAPS data for convective band with heavy rainfall event were selected. There were analyzed and classified by using the convective band with heavy rainfall occurred along the convergence line of sea wind in the form of individual multi-cellular cell and moving direction of convective band appeared in a variety of patterns; toward southwestern (2 cases), northeastern (4 cases), congesting (2 cases), and changing its moving direction (2 cases). The case study dated of the 17th Aug. 2012 was chosen and implemented by sequentially different evolution of its shape along the convergence line of sea wind cell and moving direction of convective band as equivalent potential temperatures at the lower layer have increased to the upper layer 500 hPa, that the individual cells were developed vertically and horizontally through their merger, but owing to divergence caused by weakened rainfall and descending air current, the growth of new cell was inhibited resulting in dissipation of convective cells.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.977-980
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• 2006

Ships and industries damage the delicate coastal ecosystem in many parts of the world by releasing oil or pollutants into rivers, coastal and offshore waters. After a tanker accident the biggest problem is to get a clear idea of the extent of the oil slick and predict the way it will move. For natural and man-made oil spills it is necessary to operate a regular and operational monitoring. In the Mediterranean, North and Baltic seas aircrafts or ships normally carry it out. This is expensive and is constrained by the limited availability of these resources, borders between countries, daylight hours, good weather conditions, etc. Satellite imagery can help greatly identifying probable spills over large areas and then guiding aerial surveys for precise observation of specific locations. The Synthetic Aperture Radar (SAR) instrument, which can collect data almost independently of weather and light conditions, is an excellent tool to monitor and detect oil on water surfaces. SAR is currently on board the ENVISAT, ERS-2 and RADARSAT satellites. The application of this technology to the investigation of oil pollution in the Caspian, Black, Mediterranean, North and Baltic seas is shown.

• 해양환경안전학회지
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• 제29권7호
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• pp.887-892
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• 2023

해상교통관제센터에는 RADAR, AIS(Automatic Identification System), 기상센서, VHF(Very High Frequency) 등이 설치되어 운영되고 있으며, 해상교통관제사는 이를 활용하여 관제구역을 통항하는 선박의 동정을 관찰하고 정보를 제공하는 관제 업무를 수행한다. 이들 장비에서 생성되는 각종 관제 데이터는 해상교통 상황을 분석하기 위한 자료로 그 활용 가치가 매우 높지만, 시스템 제조사간 호환성 부족 또는 정책상의 문제로 인해 체계적으로 관리되지 않고 있는 실정이다. 이에 본 연구에서는 해상교통관제센터에서 수집되는 관제 데이터를 효율적으로 수집, 저장, 관리할 수 있는 관제 빅데이터 체계를 개발하였다. 개발된 관제 빅데이터 체계는 체계 개발의 중요한 이슈 중 하나였던 운영 안정성을 확보하기 위해 마이크로서비스 아키텍처를 적용하였으며, 효율적인 실시간 운항 정보의 탐색을 위해 저장소를 이원화하여 체계 성능을 향상시킬 수 있었다. 구현된 체계는 실해역 데이터를 적용한 시범 운영을 통해 성능을 확인하고 추가적인 개선 사항을 파악하였으며, 실제 관제 환경에서의 활용 가능성을 검토하였다.