• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.133-133
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• 2010

인공위성 SAR센서는 기존 산란계 해상풍 자료의 낮은 해상도로 인한 여러 한계를 극복함으로써 다양한 해양연구에 있어 필요성과 활용영역이 넓어지고 있다. 이러한 추세에 따라 전세계적으로 다파장 SAR 센서들이 운용 또는 발사 예정에 있음에도 불구하고 현재까지 한반도 주변해에 대한 SAR 해상풍 산출 연구는 C밴드에만 한정되어왔다. 본 연구에서는 L밴드 해상풍 추출알고리즘을 적용하여 L밴드 SAR 영상으로부터 한반도 주변해의 해상풍을 추출하고 산란계 해상풍 자료와 비교 분석을 통해 정확도 특성을 제시하고자 하였다. 2007년 8월 우리나라 동해 지역을 관측한 L밴드 ALOS PALSAR 영상에 대해 L밴드 HH편광 GMF 알고리즘을 적용하여 해상풍을 산출하였다. 산출 해상풍은 동일시점의 산란계 QuikSCAT 자료와 공간적으로 유사한 패턴을 보였으며 두 자료 간의 풍속오차는 3.45m/s로 나타났다. 연구 해역과 같이 강한 바람 범위에서는 산출 해상풍 간의 차이가 크게 나타나며 풍향으로 인한 오차특성이 보인다. 특히 풍속의 경우, 산란계 해상풍이 중간바람 범위에 집중된 것에 비해 L밴드 SAR 산출 해상풍은 강한 바람 범위까지 포함하는 넓은 풍속값 범위를 나타냈다.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.201-204
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• 2006

태풍의 경우, 주요 자연재해 중의 하나로 태풍의 상황을 정확하게 파악하는 것은 기상예측의 정도를 높이고, 재해를 방지하는데 중요한 역할을 할 수 있다. 일반적으로 태풍의 동향을 감시하는데 있어, MTSAT 등의 기상위성이 주로 활용되고 있다. 근년 인공위성의 원격탐사를 이용하여 광범위의 해양에 대한 해상풍과 파랑의 관측이 가능하게 되었다. 본 연구에서는, 2000년 QuickSCAT위성에 의한 해상풍의 월변동 특성을 조사하고, 7월에 한반도에 영향을 준 태풍 카이탁내의 해상풍을 검토하였다. 추가로 2005 년 8월 30일의 태풍 탈림에 대해서 ENVISAT ASAR Scan SAR에 의한 해상풍 추출을 시도하였다. QuickSCAT 에 의한 풍향을 이용한 방법과 SAR 자체의 패턴을 이용한 방법이 비교되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.706-711
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• 2006

In order to retrieve ocean wind from SAR() image, and to estimate and validate between SAR-derived wind and in-situ wind, with RADAR SAR ocean images and real time marine meteorological data. It was used images with more than 10km to analyze the band of wind in SAR image by FFT(First Fourier Transformation) method and was used CMOD5 as wind retrieval model to retrieve ocean wind. In this study, generally it showed good results as RMS presented 0.8m/s for speed and 8 degree for direction, and especially when wind was hish speed, it presented very good results.

• 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.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.1
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• pp.32-39
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• 2013

Although space-borne satellites are useful in obtaining information all around the world, they cannot observe at a suitable time and place. In order to overcome these limitations, an airborne remote sensing system was developed in this study. It is composed of a SAR sensor and a thermal infrared sensor. Additionally GPS, IMU, and thermometer/hygrometer were attached to the plane for radiometric and geometric calibration. The brightness of SAR image varies depending on surface roughness, and capillary waves on the sea surface, which are easily generated by sea winds, induce the surface roughness. Thus, sea surface wind can be estimated using the relationship between quantified SAR backscattering coefficient and the sea surface wind. On the other hand, thermal infrared sensor is sensitive to measure object's temperature. Sea surface temperature is obtained from the thermal infrared sensor after correcting the atmospheric effects which are located between sea surface and the sensor. Using these two remote sensing sensors mounted on airplane, four test flights were carried out along the west coast of Korea. The obtained SAR and thermal infrared images have shown that these images were useful enough to monitor coastal environment and estimate marine meteorology data.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.198-203
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• 2007

최근 인공위성 SAR를 이용한 기술은 해풍，파랑，해류 등과 같은 해양에서 발생되는 다양한 현상을 관측하고 연구하는데 펼수적인 기술로 대두되고 있다. CMOD4, CMOD-IFR2 모델은 해상풍의 크기를 구할 수 있으며，wave-SAR 변환 기법과 inter-look cross-spectra 기법은 파랑의 크기，방향과 같은 물리적 값을 추출할 수 있다. 또한 Doppler shift 기법을 적용하여 해류속도를 구할 수 있다. 본 연구에서는 위의 기법들을 종합적으로 적용하여 SOP (SAR Ocean Processor) 프로세서를 개발하였다. 이 프로세서를 한반도 연안 지역에 적용하여 RADARSAT-1 영상자료로부터 해풍，파랑，해류의 물리적 정보를 추출하였으며，이를 현장 관련 자료와 비교하여 신뢰할만한 결과를 얻을 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.227-230
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• 2007

If we use the microwave of SAR, we can observe on the ocean in spite of bad weather, day and night time. Sea surface images on the ocean of SAR have a lot of information on the atmospheric phenomena related to surface wind vector. Information of wind speed which is extracted from SAR images is used variously. Wind direction data and sigma nought value are put in the CMOD which can extract wind information in order to estimate sea surface wind from SAR images. Wind spectrum which is extracted from SAR always presents opposed two points of $180^{\circ}$ because of applying to 2D-FFT. These ambiguities should be decided by position of land, wind direction or numerical model. Previously, we converted into sigma nought after extracting Digital Number from RadarSat-1 SAR using ENVI4.0, thus, it took a long time because every process was manual. Therefore, we converted sigma nought by matlab code after making matlab code. After that, we are extracting wind direction from sigma nought. Now, to decide wind direction needs further study because wind direction has $180^{\circ}$ ambiguity.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.187-194
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• 2006

Recently satellite SAR techniques have become essential observation tools for various ocean phenomena such as wind, wave, and current. The CMOD4 and CMOD-IFR2 models are used to calculate the magnitude of wind at SAR resolution with no directional information. Combination of the wave-SAR spectrum analysis and the inter-look cross-spectra techniques provides amplitude and direction of the ocean wave over a square-km sized imagette, The Doppler shift measurement of SAR image yields surface speed of the ocean current along the rador looking direction, again at imagette resolution. In this paper we report the development of a SAR Ocean processor (SOP) incorporating all of these techniques. We have applied the SOP to several RADARSAT-1 images of the coast of Korean peninsula and compared the results with oceanographic data, which showed reliability of spaceborne SAR-based oceanographic research.

• Journal of Navigation and Port Research
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• v.31 no.1 s.117
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• pp.35-42
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• 2007

Recently satellite SAR techniques have become essential observation tools for various ocean phenomena such as wind, wave, and current. The CMOD4 and CMOD-IFR2 models are used to calculate the magnitude of wind at SAR resolution with no directional information. Combination of the wave-SAR spectrum analysis and the inter-look cross-spectra techniques provides amplitude and direction of the ocean wave over a square-km sized imagette, The Doppler shift measurement of SAR image yields surface speed of the ocean current along the radar looking direction, again at imagette resolution. In this paper we report the development of a SAR Ocean processor(SOP) incorporating all of these techniques. We have applied the SOP to several RADARSAT-1 images of the coast of Korean peninsula and compared the results with oceanographic data, which showed reliability of spaceborne SAR-based oceanographic research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.149-157
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• 2008

If we use the microwave of SAR, we can observe ocean in spite of severe weather or night time. The sea surface image of SAR has numerous information about atmospheric phenomena related to surface wind field. The extracted wind information from SAR can be used diversely. In order to extract sea wind speed from SAR image, a generated wind direction from SAR and sigma nought should be input into wind model. Therefore, wind speed can be obtained by input wind direction into CMOD5 Model. Azimuth angle using CMOD5 Model is generated by added $90^{\circ}$ to Look angle which is extracted from SAR data file. A gained wind direction spectrum from SAR image has $180^{\circ}$ ambiguity because of 2D-FFT. This ambiguity should decide to use the location of land, wind direction in field or the result of numerical model. Consequently, wind direction using 2D-FFT is $3^{\circ}{\sim}7^{\circ}$ differences with actual surveying data. Wind speed by CMOD5 model is similar to actual surveying data as below 2m/s.