• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.196-200
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• 2004

The purpose of this study is to examine the image­based atmospheric correction models using the data from Landsat Enhanced Thermal Mapper Plus (ETM+) that have quite similar spectral characteristics to the forthcoming Korea Multi-Purpose SATellite (KOMPSAT)-2 Multi-Spectral Camera (MSC), and the in-situ measured surface reflectance data during satellite overflight. The main advantage of this type of correction is that it does not require in-situ measurements during each satellite overflight. While substantial differences are present between Top-Of-the Atmosphere (TOA) reflectance and in-situ measurements, the results showed that Case 1 based on COST model gives most accurate results among three cases. The accuracy of Case 2 is very close to Case 1 and its values are smaller than in-situ data. No notable features appear between some bands in the Case 3 and in-situ data. It is expected from this study that if the current methods are applied to the IKONOS high resolution data, we will be able to develop the suitable atmospheric correction methods for MSC data.

• 대한원격탐사학회지
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• 제34권1호
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• pp.127-139
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• 2018

The GOCI atmospheric correction overland surfaces is essential for the time-series analysis of terrestrial environments with the very high temporal resolution. We develop an operational GOCI atmospheric correction method over land surfaces, which is rather different from the one developed for ocean surface. The GOCI atmospheric correction method basically reduces gases absorption and Rayleigh and aerosol scatterings and to derive surface reflectance from at-sensor radiance. We use the 6S radiative transfer model that requires several input parameters to calculate surface reflectance. In the sensitivity analysis, aerosol optical thickness was the most influential element among other input parameters including atmospheric model, terrain elevation, and aerosol type. To account for the highly variable nature of aerosol within the GOCI target area in northeast Asia, we generate the spatio-temporal aerosol maps using AERONET data for the aerosol correction. For a fast processing, the GOCI atmospheric correction method uses the pre-calculated look up table that directly converts at-sensor radiance to surface reflectance. The atmospheric correction method was validated by comparing with in-situ spectral measurements and MODIS reflectance products. The GOCI surface reflectance showed very similar magnitude and temporal patterns with the in-situ measurements and the MODIS reflectance. The GOCI surface reflectance was slightly higher than the in-situ measurement and MODIS reflectance by 0.01 to 0.06, which might be due to the different viewing angles. Anisotropic effect in the GOCI hourly reflectance needs to be further normalized during the following cloud-free compositing.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.418-421
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• 2005

In this study, we analyzed surface temperature of lakes in the Han River system, using Landsat-5 and -7 time-series images. Surface temperature was extracted using NASA equation and compared with in situ 10m-depth temperature in Lake Soyang and surface temperature on five other dam lakes downstream. The 24 images out of 29 showed standard deviation of temperature difference less than $2^{\circ}C$, to which a novel statistical atmospheric correction could be applied. The correlation coefficients were 0.950 at Lake Soyang and 0.979-0.997 at the other lakes after atmospheric correction.

• 한국지구과학회지
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• 제37권7호
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• pp.408-419
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• 2016

동해 남서해역 퇴적물의 현장 음파전달속도를 파악하기 위하여 신호투과법을 이용하여 퇴적물의 실험실 음파전달속도를 측정하였다. 측정된 실험실 음파전달속도는 해저면 온도, 해수 음파전달속도, Kim et al. (2004)과 Hamilton (1980) 모델을 적용하여 현장 음파전달속도로 보정하였다. Kim et al. (2004)과 Hamilton (1980)의 현장 음파전달속도는 연구지역 퇴적물 특성을 반영하며, 유사한 분포를 보인다. 현장 음파전달속도 보정에는 해저면 온도의 영향을 크게 받는 것을 확인할 수 있다. 따라서 퇴적물의 실험실 음파전달속도를 통해 현장 음파전달속도를 파악하기 위해서는 해저표층 온도 자료를 통한 온도 보정이 반드시 수행되어야 한다.

• 항공우주기술
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• 제4권1호
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• pp.211-220
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• 2005

본 연구의 목적은 향후 발사될 KOMPSAT-2 MSC와 유사한 분광특성을 가지는 Landsat ETM+ 영상자료와 동시기에 지상에서 관측한 surface reflectance 자료를 이용하여 영상기반의 대기보정 모델을 검토하는 것이다. 이러한 영상기반의 대기보정은 현장관측 자료가 필요하지 않다는 이점이 있다. TOA reflectance와 현장 관측치 간에 상당한 차이를 보이며, 연구결과는 COST 모델을 기반으로 하는 Case 1이 세 가지 경우 중에서 가장 정확함을 나타냈다. 한편 Case 2_1의 경우 Case 1처럼 정확하나 그 값은 현장 자료보다 낮게 나타났다. 또한 Case 3_1은 일부 밴드에서 관측치와 전혀 상관성이 없는 것으로 나타났다. 향후 IKONOS와 같은 고해상도 영상자료에 본 연구방법을 적용하면 MSC 데이터 특성에 맞는 대기보정 모델을 개발할 수 있을 것으로 판단된다.

• International Journal of Ocean System Engineering
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• 제1권2호
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• pp.60-67
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• 2011

This paper presents an in-situ correction method to compensate for the position error of an autonomous underwater vehicle (AUV) near the sea floor. AUVs generally have an inertial navigation system assisted with auxiliary navigational sensors. Since the inertial navigation system shows drift in position without the bottom reflection of a Doppler velocity log, external acoustic positioning systems, such as an ultra short baseline (USBL), are needed to set the position without surfacing the AUV. The main concept of the correction method is as follows: when the AUV arrives near the sea floor, the vehicle moves around horizontally in a circular mode, while the USBL transceiver installed on a surface vessel measures the AUV's position. After acquiring one data set, a least-square curve fitting method is adopted to find the center of the AUV's circular motion, which is transferred to the AUV via an acoustic telemetry modem (ATM). The proposed method is robust for the outlier of USBL, and it is independent of the time delay for the data transfer of the USBL position with the ATM. The proposed method also reduces the intrinsic position error of the USBL, and is applicable to the in-situ calibration as well as the initialization of the AUVs' position. Monte Carlo simulation was conducted to verify the effectiveness of the method.

• 대한원격탐사학회지
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• 제20권5호
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• 대한원격탐사학회지
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• 제21권4호
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• pp.253-271
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• 2005

Landsat 시계열 영상과 실측수온자료를 이용하여 한강 수계 댐호들의 표면수온과 계절적 성층현상을 분석하였다. 1994년에서 2004년까지 29회에 걸쳐 얻어진 Landsat-5, 7 열적외선 영상으로부터 NASA 경험식을 이용하여 호수의 표면수온을 추출하였고, 이를 하천형 댐호인 파로호, 춘천호, 의암호, 청평호, 팔당호의 표층수온, 그리고 호소형 댐호인 소양호의 상층수온(수심 10m) 자료와 비교하였다. 십 수 년간 매월 1회 측정된 수온자료를 위성관측 날짜에 보간하여 사용하였음에도 불구하고, 하천형 댐호들에서는 수온오차(위성관측수온-실측보간수온)의 표준 편차가 $2^{\circ}C$ 이하인 영상이 94개로서, 새로운 통계적 대기보정을 적용할 수 있었다. 실측보간수온과 위성관측수온의 상관계수는 소양호가 0.915 (대기보정 후 0.950), 다른 호수는 0.951-0.980 (대기보정 후 0.979-0.997)로서, 높은 상관성을 보여주었다. 이는 수심이 얕고 인위적인 물의 유입과 유출이 연중 계속되는 하천형 댐호의 표층에는 혼합층이 상시 존재하고 수온의 일변화 및 월변화가 비교적 연속적이기 때문인 것으로 해석되었다. 그러나 소양호에서는 4-7월에 위성관측수온이 실측보간수온보다 $3-5^{\circ}C$ 더 높게 나타나는 이상 수온오차가 관찰되었다. 한강 수계의 최상류에 위치하며 수심이 깊고 자연적인 유입량만이 존재하는 소양호에서 이 시기는 상층수의 물리적 혼합현상이 없이 매우 안정적이고, 일조량 증가에 따라 호수 상층부에 수온약층이 발달하기 때문에, 수심 10m에서 측정된 실측수온보다 위성으로 관측된 표면수온이 연중 비교적 건조한 이 시기에 더 높게 나타나는 것으로 밝혀졌다.

• Ocean and Polar Research
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• 제38권4호
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• pp.259-270
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• 2016

Sea Surface Salinity (SSS) observations from the Aquarius satellite in the East Sea show large systematic biases mainly caused by the surrounding lands and Radio Frequency Interferences (RFI) along the descending orbits on which the satellite travels from the Asian continent to the East Sea. To develop a technique for correcting the systematic biases unique to the East Sea, the least square regression between in situ observations of salinity and the reanalyzed salinities by HYCOM is first performed. Then monthly mean reanalyzed salinities fitted to the in situ salinities are compared with monthly mean Aquarius salinities to calculate mean biases in $1^{\circ}{\times}1^{\circ}$ boxes. Mean biases in winter (December-March) are found to be considerably larger than those in other seasons possibly caused by the inadequate correction of surface roughness in the sea surrounded by the land, and thus the mean bias corrections are performed using two bias tables. Large negative biases are found in the area near the coast of Japan and in the areas with islands. In the northern East Sea, data sets using the ascending orbit only (SCIA) are chosen for correction because of large RFI errors on the descending orbit (SCID). Resulting mean biases between the reanalysis salinities fitted to in situ observations and the bias corrected Aquarius salinities are less than 0.2 psu in all areas. The corrected mean salinity distributions in March and September demonstrate marked improvements when compared with mean salinities from the World Ocean Atlas (WOA [2005-2012]). In September, salinity distributions based on the corrected Aquarius and on the WOA (2005-2012) show similar distributions of Changjiang Diluted Water (CDW) in the East Sea.

• 신재생에너지
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• 제4권4호
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• pp.23-29
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• 2008

Wind farm development project contains high business risks because that a wind farm, which is to be operating for 20 years, has to be designed and assessed only relying on a year or little more in-situ wind data. Accordingly, long-term correction of short-term measurement data is one of most important process in wind resource assessment for project feasibility investigation. This paper shows comparison of general Measure-Correlate-Prediction models and neural network, and presents new method using neural network for increasing prediction accuracy by accommodating multiple reference data. The proposed method would be interim step to complete long-term correction methodology for Korea, complicated Monsoon country where seasonal and diurnal variation of local meteorology is very wide.