• Nuclear Engineering and Technology
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• v.27 no.2
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• pp.176-188
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• 1995

A particle tracking scheme was developed in order to model radionuclide transport through a tortuous flow Held in a rock fracture. The particle tacking method may be used effectively in a heterogeneous flow field such as rock fracture. The parallel plate representation of the single fracture fails to recognize the spatial heterogeneity in the fracture aperture and thus seems inadequate in describing fluid movement through a real fracture. The heterogeneous flow field une modeled by a variable aperture channel model after characterizing aperture distribution by a hydraulic test. To support the validation of radionuclide transport models, a radionuclide migration experiment was performed in a natural fracture of granite. $^3$$H_2O$ and $^{131}$ I are used as tracers. Simulated results were in agreement with experimental result and therefore support the validity of the transport model. Residence time distributions display multipeak curves caused by the fast arrival of solutes traveling along preferential fracture channels and by the much slower arrival of solutes following tortous routes through the fracture. Results from the modelling of the transport of nonsorbing tracer through the fracture show that diffusion into the interconnected pore space in the rock mass has a significant effect on retardation.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1181-1194
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• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.33-41
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• 2003

Every year, several typhoons hit the Korean peninsula and cause severe damage. For the prevention and accurate estimation of these damages, real time or almost real time flood information is essential. Because of weather conditions, images taken by optic sensors or LIDAR are sometimes not appropriate for an accurate estimation of water areas during typhoon. In this case SAR (Synthetic Aperture Radar) images which are independent of weather condition can be useful for the estimation of flood areas. To get detailed information about floods from satellite imagery, accurate classification of water areas is the most important step. A commonly- and widely-used classification methods is the ML(Maximum Likelihood) method which assumes that the distribution of brightness values of the images follows a Gaussian distribution. The distribution of brightness values of the SAR image, however, usually does not follow a Gaussian distribution. For this reason, in this study the ANN (Artificial Neural Networks) method independent of the statistical characteristics of images is applied to the SAR imagery. RADARS A TSAR images are primarily used for extraction of water areas, and DEM (Digital Elevation Model) is used as supplementary data to evaluate the ground undulation effect. Water areas are also extracted from KOMPSAT image achieved by optic sensors for comparison purpose. Both ANN and ML methods are applied to flat and mountainous areas to extract water areas. The estimated areas from satellite imagery are compared with those of manually extracted results. As a result, the ANN classifier performs better than the ML method when only the SAR image was used as input data, except for mountainous areas. When DEM was used as supplementary data for classification of SAR images, there was a 5.64% accuracy improvement for mountainous area, and a similar result of 0.24% accuracy improvement for flat areas using artificial neural networks.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1125-1135
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• 2022

Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.132-147
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• 2016

In this study the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) sensor onboard the Soil Moisture Ocean Salinity (SMOS) and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor onboard the Global Change Observation Mission-Water (GCOM-W1) based soil moisture retrievals were revised to obtain better accuracy of soil moisture and higher data acquisition rate over East Asia. These satellite-based soil moisture products are revised against a reference land model data set, called Global Land Data Assimilation System (GLDAS), using Cumulative Distribution Function (CDF) matching and regression approach. Since MIRAS sensor is perturbed by radio frequency interferences (RFI), the worst part of soil moisture retrieval, East Asia, constantly have been undergoing loss of data acquisition rate. To overcome this limitation, the threshold of RFI, DQX, and composite days were suggested to increase data acquisition rate while maintaining appropriate data quality through comparison of land surface model data set. The revised MIRAS and AMSR2 products were compared with in-situ soil moisture and land model data set. The results showed that the revising process increased correlation coefficient values of SMOS and AMSR2 averagely 27% 11% and decreased the root mean square deviation (RMSD) decreased 61% and 57% as compared to in-situ data set. In addition, when the revised products' correlation coefficient values are calculated with model data set, about 80% and 90% of pixels' correlation coefficients of SMOS and AMSR2 increased and all pixels' RMSD decreased. Through our CDF-based revising processes, we propose the way of mutual supplementation of MIRAS and AMSR2 soil moisture retrievals.

• Journal of the Korean Geographical Society
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• v.38 no.3
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• pp.375-388
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• 2003

This study mainly focuses on evaluating how the triangular training operator could improve classification accuracy in SAR(Synthetic Aperture Radar) and VIR FCC(Visible Infra-red, False Colour Composite). The techniques for the determination of the most informative SAR/VIR combinations in the triangular space diagram, as developed tv the author of the paper, are given and the results obtained are presented. The SAR alone, VIR alone and SAR/VIR FCC classification showed trends for gradual improvement of accuracy. Accuracy distribution pattern for individual classes could be explained closely related to SAR/VIR signature components in the process of the triangular synergistic training. Due to contribution of SAR signature in training samples, it was possible to isolate major terrain features such as cloud cover area and roughness target with acceptable spatial precision. It is anticipated that this research output could be used as a valuable reference for distribution trends of classification accuracy obtained by triangular channel space based training in synergistic application.

• Journal of the Korean Vacuum Society
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• v.12 no.1
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• pp.64-69
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• 2003

Using a high fewer electron beam gun (max. power 20 kW), Gadolinium (Gd, atomic number 64) metal was melted and the temperature distribution of melted surface was measured. With proper optical filters and the adjustment of aperture of lens, the radiation of melted surface was received by a ccd camera and its signal transferred to a computer. The real time monitoring of melted surface with a variation of electron beam Power was Possible and stable operation of electron beam was achieved. It was found that the max. temperature measured by a ccd camera with an assumption of blackbody radiation of melted Gd surface and adaption of Planet's law was above 100~$200^{\circ}C$ compared to that measured by a pyrometer in the same e-beam power.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.210-213
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• 1988

A new and accurate expression to derive a window area is presented with a sequence for daylighting design using Daylight Factor Method process not in its classical point--by-point method but in lumen method as in artificial lighting design process to consider daylight in the early stage of a building design process. Accepting CIE Overcast Sky as the worst state with the lowest sky luminance, a user of a room can have more available daylight in his or her room. In the design process uniformity is checked to ensure reasonably even daylighting by comparing the depth of the room with the computed limiting depth. After these steps the shape and position of window is altered, of which the Sky Component of Daylight Factor under an Overcast Sky, SCo, is investigated and computed in Composite Simpson Multiple Integral so that a building designer or an analyst can choose the best shape and location that satisfies his/her taste and purpose of the room.

• Journal of the Korean Wood Science and Technology
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• v.46 no.4
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• pp.309-314
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• 2018

Size reduction is an important pre-processing operation for utilizing biomass as a sustainable resource in industrial-scale energy production and as a raw material for other industries. This work investigates the size reduction characteristics of air-dried Miscanthus sacchariflorus Goedae-Uksae 1 (Amur silver grass) via image processing and identifies the morphological characteristics of comminuted and screened M. sacchariflorus. At chopping lengths of 18, 40, 80, and 160 mm, 81%, 77%, 78%, and 76% of the particles, respectively, passed through a 4-mm sieve. Even a knife mill with a very small screen aperture (>1 mm) admitted over 10% of the particles. The average circularity and aspect ratio of the particles were <0.30 and >10, respectively. These results confirm that in all preparation modes, most M. sacchariflorus particles were needle-like in shape, irrespective of the type of preparation.