• Title/Summary/Keyword: 복사전달모델

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Analysis of the Impact of Surface Reflectance Error Retrieved from 6SV for KOMPSAT-3A according to MODIS AOD Expected Error (MODIS AOD 기대 오차에 따른 6SV 기반 KOMPSAT-3A 채널별 지표반사도 오차 영향 분석)

  • Daeseong Jung;Suyoung Sim;Jongho Woo;Nayeon Kim;Sungwoo Park;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1517-1522
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    • 2023
  • This study evaluates the impact of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) expected error (EE) on the accuracy of surface reflectance (SR) derived from the KOMPSAT-3A satellite, utilizing the Second Simulation of the Satellite Signal in the Solar Spectrum Vector radiative transfer model. By considering a range of ground-based AOD and the resultant MODIS AOD EE, the research identifies significant influences on SR accuracy, particularly under high solar zenith angles(SZA) and shorter wavelengths. The study's simulations reveal that SR errors increase with shorter wavelengths and higher SZAs, highlighting the necessity for further research to improve atmospheric correction algorithms by incorporating wavelength and SZA considerations. Additionally, the study provides foundational data for better understanding the use of AOD data from other satellites in atmospheric correction processes and contributes to advancing atmospheric correction technologies.

Generation of Simulated Image from Atmospheric Corrected Landsat TM Images (대기보정된 Landsat TM 영상으로부터 모의영상 제작)

  • Lee, Soo Bong;La, Phu Hien;Eo, Yang Dam;Pyeon, Mu Wook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.1
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    • pp.1-9
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    • 2015
  • A remote sensed image simulation following to weather and season conditions can be performed by a reverse atmospheric correction which is a function of image preprocessing. In this study, we have made an experiment to generate the simulated image to the raw image, which is prior to the atmospheric corrected images under the specific weather conditions. The applied methods in this study were the Forster algorithm (1984) and 6S RTM (Radiative Transfer Model). The simulated images has been compared with the original image to analyze compliances. In fact, the results from 6S RTM method show better compliances than Forster, with a mean of RMSE of DN difference 9.35 and a mean of $R^2$ 0.7. In conclusion, a simulated image has practical feasibility when similar to the period and season as the reference image.

Sensitivity Analysis of Numerical Weather Prediction Model with Topographic Effect in the Radiative Transfer Process (복사전달과정에서 지형효과에 따른 기상수치모델의 민감도 분석)

  • Jee, Joon-Bum;Min, Jae-Sik;Jang, Min;Kim, Bu-Yo;Zo, Il-Sung;Lee, Kyu-Tae
    • Atmosphere
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    • v.27 no.4
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    • pp.385-398
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    • 2017
  • Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

Numerical Simulation on the Spreading and Heat Transfer of Ex-Vessel Core Melt in a Channel (전산해석을 이용한 원자로 노심 용융물의 노외 거동 및 열전달 특성 분석)

  • Ye, In-Soo;Ryu, Chang-Kook;Ha, Kwang-Soon;Song, Jin-Ho
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.35 no.4
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    • pp.425-429
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    • 2011
  • In the unlikely of nuclear reactor meltdown, the leaked core melt or corium must be contained in a device called core-catcher so that the corium can be cooled and stabilized. The ex-vessel behavior of corium involves complex physical and chemical mechanisms of flow propagation, heat transfer, and reactions with sacrificial substrates. In this study, the detailed characteristics of corium flow and heat transfer were investigated by using a commercial CFD code for VULCANO VE-U7 test reported in the literature. The volume-of-fluid (VOF) model was used to predict the interfacial surface formation of corium and the surrounding air, and the discrete ordinate model was adopted to calculate radiation between corium and the surroundings. It was found that cooling via radiation through the top surface of corium had a dominant effect on the temperature and viscosity profiles at the front of the corium flow.

Investigation of NO Formation Characteristics in Multi Staged Air Combustor (공기 다단 연소기 화염의 NO 발생특성에 관한 연구)

  • Kim, Han-Seok;An, Guk-Yeong;Baek, Seung-Uk;Yu, Myeong-Jong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.25 no.11
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    • pp.1594-1605
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    • 2001
  • In this study, a numerical simulation was developed which was capable of predicting the characteristics of NO formation in pilot scale combustor adopting the air-staged burner flame. The numerical calculation was constructed by means of establishing the mathematical models fur turbulence, turbulent combustion, radiation and turbulent nitric oxide chemistry. Turbulence was solved with standard k-$\xi$ model and the turbulent combustion model was incorporated using a two step reaction scheme together with an eddy dissipation model. The radiative transfer equation was calculated by means of the discrete ordinates method with the weighted sum of gray gases model for CO$_2$and H$_2$O. In the NO chemistry model, the chemical reaction rates for thermal and prompt NO were statistically averaged using the $\beta$ probability density function. The results were validated by comparison with measurements. For the experiment, a 0.2 MW pilot multi-air staged burner has been designed and fabricated. Only when the radiation was taken into account, the predicted gas temperature was in good agreement with the experimental one, which meant that the inclusion of radiation was indispensable for modeling multi-air staged gas flame. This was also true of the prediction of the NO formation, since it heavily depended on temperature. Subsequently, it was found that the multi-air staged combustion technique might be used as a practical tool in reducing the NO formation by controlling the peak flame temperature.

Machine Learning-Based Atmospheric Correction Based on Radiative Transfer Modeling Using Sentinel-2 MSI Data and ItsValidation Focusing on Forest (농림위성을 위한 기계학습을 활용한 복사전달모델기반 대기보정 모사 알고리즘 개발 및 검증: 식생 지역을 위주로)

  • Yoojin Kang;Yejin Kim ;Jungho Im;Joongbin Lim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.891-907
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    • 2023
  • Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

Estimation of Leaf Area Index Based on Machine Learning/PROSAIL Using Optical Satellite Imagery (광학위성영상을 이용한 기계학습/PROSAIL 모델 기반 엽면적지수 추정)

  • Lee, Jaese;Kang, Yoojin;Son, Bokyung;Im, Jungho;Jang, Keunchang
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1719-1729
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    • 2021
  • Leaf area index (LAI) provides valuable information necessary for sustainable and effective management of forests. Although global high resolution LAI data are provided by European Space Agency using Sentinel-2 satellite images, they have not considered forest characteristics in model development and have not been evaluated for various forest ecosystems in South Korea. In this study, we proposed a LAI estimation model combining machine learning and the PROSAIL radiative transfer model using Sentinel-2 satellite data over a local forest area in South Korea. LAI-2200C was used to measure in situ LAI data. The proposed LAI estimation model was compared to the existing Sentinel-2 LAI product. The results showed that the proposed model outperformed the existing Sentinel-2 LAI product, yielding a difference of bias ~ 0.97 and a difference of root-mean-square-error ~ 0.81 on average, respectively, which improved the underestimation of the existing product. The proposed LAI estimation model provided promising results, implying its use for effective LAI estimation over forests in South Korea.

VALIDATION OF AURIC MODEL WITH EUV/FUV DAYGLOW OBSERVATION OF STP78-1 SATELLITE (STP78-1 위성의 극자외선/원자외선 낮대기광 관측자료를 이용한 AURIC 모델의 검증)

  • Kang, Mi-Ji;Kim, Jeong-Han;Kim, Yong-Ha
    • Journal of Astronomy and Space Sciences
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    • v.24 no.1
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    • pp.55-68
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    • 2007
  • We carried out a validation study on AURIC FUV/EUV dayglow calculation with $OII\;834{\AA},\;OI\;989{\AA},\;OI\;1027{\AA},\;NII\;1085{\AA},\;NI\;1134{\AA},\;NI\;1200{\AA},\;OI\;1304{\AA},\;OI\;1356{\AA}$ dayglows observed by STP78-1 satellite. Comparison between calculated and observed values indicates that they are in agreement within about 20% for dayglows of $OII\;834{\AA},\;OI\;1027{\AA},\;NI\;1200{\AA},\;OI\;1304{\AA}$. However, the calculated intensities of $OI\;989{\AA},\;NII\;1085{\AA},\;NI\;1134{\AA}$ are only 42, 74 and 45% of the observed values, respectively, showing serious differences from the observation. It was surmised that the differences in $OI\;989{\AA}\;and\;NI\;1134{\AA}$ are due to incomplete calculation of radiative transfer and uncertain photochemical processes in AURIC model, respectively. The difference in $NII\;1085{\AA}$ is conjectured to be due to variation of the input solar EUV flux rather than due to AURIC model itself. For up-looking dayglows from the satellite, the calculated values from AURIC are all less than those of STP78-1, which may imply that AURIC model does not include dayglow contribution from regions below the satellite altitude when it computes dayglows in up-looking direction. The differences are particularly serious for $OI\;989{\AA},\;NI\;1134{\AA},\;NI\;1200{\AA}$ dayglows. The calculated latitudinal variation of $OII\;834{\AA}$ dayglow is also significantly different from the observed one, especially at mid-latitude regions. This may be due to inability of MSISE-90 (in input of AURIC) to simulate oxygen atom densities at mid-latitudes during auroral storms at those days of STP78-1 observations. Our findings of the validation study should be resolved when AURIC model is revised in future.

Application and Analysis of Ocean Remote-Sensing Reflectance Quality Assurance Algorithm for GOCI-II (천리안해양위성 2호(GOCI-II) 원격반사도 품질 검증 시스템 적용 및 결과)

  • Sujung Bae;Eunkyung Lee;Jianwei Wei;Kyeong-sang Lee;Minsang Kim;Jong-kuk Choi;Jae Hyun Ahn
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1565-1576
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    • 2023
  • An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (Rrs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This Rrs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of Rrs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ Rrs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for Rrs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying Rrs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

Investigation of O4 Air Mass Factor Sensitivity to Aerosol Peak Height Using UV-VIS Hyperspectral Synthetic Radiance in Various Measurement Conditions (UV-VIS 초분광 위성센서 모의복사휘도를 활용한 다양한 관측환경에서의 에어로솔 유효고도에 대한 O4 대기질량인자 민감도 조사)

  • Choi, Wonei;Lee, Hanlim;Choi, Chuluong;Lee, Yangwon;Noh, Youngmin
    • Korean Journal of Remote Sensing
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    • v.36 no.2_1
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    • pp.155-165
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    • 2020
  • In this present study, the sensitivity of O4 Air Mass Factor (AMF) to Aerosol Peak Height (APH) has been investigated using radiative transfer model according to various parameters(wavelength (340 nm and 477 nm), aerosol type (smoke, dust, sulfate), aerosol optical depth (AOD), surface reflectance, solar zenith angle, and viewing zenith angle). In general, it was found that O4 AMF at 477 nm is more sensitive to APH than that at 340 nm and is stably retrieved with low spectral fitting error in Differential Optical Absorption Spectroscopy (DOAS) analysis. In high AOD condition, sensitivity of O4 AMF on APH tends to increase. O4 AMF at 340 nm decreased with increasing solar zenith angle. This dependency isthought to be induced by the decrease in length of the light path where O4 absorption occurs due to the shielding effect caused by Rayleigh and Mie scattering at high solar zenith angles above 40°. At 477 nm, as the solar zenith angle increased, multiple scattering caused by Rayleigh and Mie scattering partly leads to the increase of O4 AMF in nonlinear function. Based on synthetic radiance, APHs have been retrieved using O4 AMF. Additionally, the effect of AOD uncertainty on APH retrieval error has been investigated. Among three aerosol types, APH retrieval for sulfate type is found to have the largest APH retrieval error due to uncertainty of AOD. In the case of dust aerosol, it was found that the influence of AOD uncertainty is negligible. It indicates that aerosol types affect APH retrieval error since absorption scattering characteristics of each aerosol type are various.