• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.435-444
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• 2009

In the case of oil spill accident at sea, information concerning the movement of spilled oil is important in making response strategies. Aircrafts and the satellites have been utilized for monitoring of spilled oil. In these days, numerical models are using to predict the movement of the spilled oil. In the future a coupling method of modeling and remote sensing data should be needed to predict more correctly the spilled oil. The purpose of this paper is to present an application of satellite image data to an oil spill prediction model as an initial condition. Environmental Fluid Dynamics Computer Code (EFDC) was used to predict the movement of the oil spilled from Hebei Spirit incident occurred in Taean coastal area on December 7,2007. In order to make the model initial condition and to compare the model results, two satellite images, KOMPSAT-2 MSC and ENVISAT ASAR obtained on December 8 and 11, were used during the period of the oil spill incident. The model results showed an improvement for the prediction of the spilled oil by using the initial condition deduced from satellite image data than the initial condition specified at the oil spill incident site in the respects of the distributed spilled area.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1994.04a
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• pp.227-227
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• 1994

퀴놀론계 항균제란 퀴놀린 이나 나프티리딘 핵을 갖고 있는 화합물로써 항균효과를 나타내는 물질을 의미한다. 이러한 퀴놀론계 항균제의 구조적 특성에 따라 항균활성의 영향은 ASAR에 의하여 이미 구조적 제한성을 가지고 있다고 보고 되어있다. 본 연구에서는 Drug-Enzyme inleraetion domain을 변화시킴으로서 보다 강력한 항균제를 찾아낼수 있을 것으로 판단하고, 기존 항균제가 C-7에 piperazine이 있으므로 piperazine의 chemical isoster 또는 bioisoster의 개념하에서 C-7에 도입한 아민류를 분자설계하고 합성하여 새로운 퀴놀론계 항균제를 만들어 내고자 하였으며 target molecule은 다음 그림과 같다.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.303-306
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• 2006

이 연구에서는 C 밴드 SAR 자료이면서 서로 다른 편광 상태의 자료를 제공할 수 있는 다중 시기 Radarsat-1 자료와 ENVISAT ASAR 자료를 이용한 토지 피복 분류를 수행하였다. 다중 시기/편광 자료로부터 평균 후방산란계수, 시간적 변이도, 긴밀도 등의 특징을 기본적으로 추출하였고, 이외에 상호 비교를 위해 주성분 분석을 이용한 특징 추출을 시도하였다. 특징들을 이용한 분류기법으로는 Random Forests를 적용하였다. 충남 예당평야 일대를 대상으로 사례연구를 수행한 결과, 주성분 분석을 통한 특징과 다편광 자료를 이용하였을 때 분류 정확도가 향상되는 것으로 나타났다.

• Proceedings of the KSRS Conference
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• v.2
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• pp.963-963
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• 2006

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.645-655
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• 2013

As one of segmentation techniques for Synthetic Aperture Radar (SAR) image with oil spill, we applied a bimodal histogram method to discriminate oil pixels from non-oil pixels. The threshold of each moving window was objectively determined using the two peaks in the histogram distribution of backscattering coefficients from ENVISAT ASAR image. To reduce the effect of wind speed on oil spill detection, we selected ASAR image which satisfied a limit of wind speeds for successful detection. Overall, a commonly used adaptive threshold method has been applied with a subjectively-determined single threshold. In contrast, the bimodal histogram method utilized herein produces a variety of thresholds objectively for each moving window by considering the characteristics of statistical distribution of backscattering coefficients. Comparison between the two methods revealed that the bimodal histogram method exhibited no significant difference in terms of performance when compared to the adaptive threshold method, except for around the edges of dark oil spots. Thus, we anticipate that the objective method based on the bimodality of oil slicks may also be applicable to the detection of oil spills from other SAR imagery.

• Ocean and Polar Research
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• v.31 no.1
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• pp.111-119
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• 2009

Biogenic surface films, which are often present in coastal areas, may enhance the signatures of hydrodynamic processes in microwave, optical, and infrared imagery. We analyzed ERS-1/2 Synthetic Aperture Radar (SAR) and Envisat Advanced Synthetic Aperture Radar (ASAR) images taken over the Japan/East Sea (JES). We focused on the appearance of the contrast SAR signatures, particularly the dark features of different scales caused by various oceanic and atmospheric phenomena. Spiral eddies of different scales were detected through surface film patterns both near the coast and in the open regions of the JES in warm and cold seasons. During field experiments carried out at the Pacific Oceanological Institute (POI) Marine Station 'Cape Shults' in Peter the Great Bay, the sea surface roughness characteristics were measured during the day and night using a developed polarization spectrophotometer and various digital cameras and systems of floats. The velocity of natural and artificial slicks was estimated using video and ADCP time series of tracers deployed on the sea surface. The slopes of gravity-capillary wave power spectra varied between .4 and .5. Surface currents in the natural and artificial slicks increased with the distance from the coast, varying between 4 and 40 cm/s. The contrast of biogenic and anthropogenic slicks detected on vertical and horizontal polarization images against the background varied over a wide range. SAR images and ancillary satellite and field data were processed and analyzed using specialized GIS for marine coastal areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.413-413
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• 2020

Godunov형 모형을 이용한 홍수모델링에서는 일반적으로 구조적 사각격자나 비구조적 삼각격자가 주로 적용된다. 2차원 수치모형을 이용한 홍수모델링에서 연구유역의 정보가 격자의 노드나 중심에 입력되므로 적용격자의 유형과 생성방법에 따라 모형의 입력자료 오차에 영항을 줄 수 있다. 따라서, 연구유역이 지형 변동성이 심한 지역이거나 흐름형상이나 흐름변동이 심한 구간이라면, 고해상도 격자를 통해 모형의 입력자료 오차를 최소화할 할 수 있다. 본 연구에서는 2가지 유형에 대한 연구를 수행하였다, 첫 번째는 홍수해석을 위한 2차원 모형의 격자형상과 해상도에 따른 홍수위 및 홍수범람범위를 비교·분석하는 연구를 수행하였다. 연구유역은 2000년 10월 29일부터 11월 19일까지 홍수가 발생한 영국의 Severn 강 유역이다. 연구유역의 홍수 모델링을 위한 지형자료는 3m 해상도의 LiDAR(Light Detection And Ranging)를 이용하여 구축하였으며, 격자유형 및 해상도에 따른 2차원 홍수위 및 홍수범람범위를 비교·분석하기 위해서 홍수 발생기간 동안 촬영된 4개(2000년 8월 11, 14, 15, 17일)의 ASAR(Advanced Synthetic Aperture Radar) 영상자료를 활용하였다. 즉, ASAR 영상으로 촬용된 최대범람시기 및 홍수류의 배수기를 활용하여 최대범람범위뿐만 아니라 홍수가 증가하는 시기와 하류단 배수로 인해 홍수가 감소하는 시기를 모두 포함하는 홍수범람범위에 대한 격자유형별 2차원 홍수범람모형의 계산 결과에 대해 비교하였다. 두 번째는 아마존 강 중류유역의 2,500K㎡ 면적에 해당하는 대규모 유역에 대해 SRTM(Shuttle Radar Topography Mission) 지형자료를 이용하여 홍수기와 갈수기에 대해 2차원 모델링을 수행하고 그 결과를 위성자료와 비교하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.125-125
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• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

• New & Renewable Energy
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• v.9 no.3
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• pp.14-19
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• 2013

Comparative evaluation of offshore wind retreival software, which use the satellite images taken by Synthetic Aperture Radar sensor; SARTools of CLS-SOPRONO, France and SpaceEye of London Research and Development Corporation, Canada is carried out. For a reference satellite image, ENVISAT ASAR imagery of Jeollanam-do Wan-do area when the winter-time northwestern wind prevails is processed by CMOD_IFR2, CMOD4, CMOD5 algorithms. Wind speed difference and its relative ratio are calculated to evaluate uncertainty of software selection.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2184-2189
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• 2009

China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.