• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.613-623
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• 2011

This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with $R^2$ 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with $R^2$ 0.66 and 0.73, respectively. Their performance showed the 'Approximate Prediction' with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.659-672
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• 2001

Generally, design flood for a hydraulic structure is estimated using statistical analysis of runoff data. However, due to the lack of runoff data, it is difficult that the statistical method is applied for estimation of design flood. In this case, the synthetic unit hydrograph method is used generally and the models such as NYMO method, Snyder method, SCS method, and HYMO method have been widely used in Korea. In this study, these methods and KICT method, which is developed in year 2000, are compared and analyzed in 10 study areas. Firstly, peak flow and peak time of representative unit hydrograph and synthetic unit hydrograph in study area are compared, and secondly, the shape of unit hydrograph is compared using a root mean square error(RMSE). In Nakayasu method developed in Japan, synthetic unit hydrograph is very different from peak flow, peak time, and the shape of representative unit hydrograph, and KICT method(2000) is superior to others. Also, KICT method(2000) is superior to others in the aspects of using hydrologic and topographical data. Therefore, Nakayasu method is not a proper in hydrological practice. Moreover, it is considered that KICT model is a better method for the estimation of design flood. However, if other model, i.e. SCS method, Nakayasu method, and HYMO method, is used, parameters or regression equations must be adjusted by analysis of real data in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.52-68
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• 2014

In this study, we investigated the seasonal variation of SST(Sea Surface Temperature) and thermal effluents estimated by using Landsat-7 ETM+ around the Kori Nuclear Power Plant for 10 years(2000~2010). Also, we analyzed the direction and range of thermal effluents dispersion by the tidal current and tide. The results are as follows, First, we figured out the algorithm to estimate SST through the linear regression analysis of Landsat DN(Digital Number) and NOAA SST. And then, the SST was verified by compared with the in situ measurement and NOAA SST. The determination coefficient is 0.97 and root mean square error is $1.05{\sim}1.24^{\circ}C$. Second, the SST distribution of Landsat-7 estimated by linear regression equation showed $12{\sim}13^{\circ}C$ in winter, $13{\sim}19^{\circ}C$ in spring, and $24{\sim}29^{\circ}C$ and $16{\sim}24^{\circ}C$ in summer and fall. The difference of between SST and thermal effluents temperature is $6{\sim}8^{\circ}C$ except for the summer season. The difference of SST is up to $2^{\circ}C$ in August. There is hardly any dispersion of thermal effluents in August. When it comes to the spread range of thermal effluents, the rise range of more than $1^{\circ}C$ in the sea surface temperature showed up to 7.56km from east to west and 8.43km from north to south. The maximum spread area was $11.65km^2$. It is expected that the findings of this study will be used as the foundational data for marine environment monitoring on the area around the nuclear power plant.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.90-108
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• 2015

The WRF-Chem model was applied to simulate the Asian dust event affecting the Korean Peninsula from 11 to 13 November 2010. GOCART dust emission schemes, RADM2 chemical mechanism, and MADE/SORGAM aerosol scheme were adopted within the WRF-Chem model to predict dust aerosol concentrations. The results in the model simulations were identified by comparing with the weather maps, satellite images, monitoring data of $PM_{10}$ concentration, and LIDAR images. The model results showed a good agreement with the long-range transport from the dust source area such as Northeastern China and Mongolia to the Korean Peninsula. Comparison of the time series of $PM_{10}$ concentration measured at Backnungdo showed that the correlation coefficient was 0.736, and the root mean square error was $192.73{\mu}g/m^3$. The spatial distribution of $PM_{10}$ concentration using the WRF-Chem model was similar to that of the $PM_{2.5}$ which were about a half of $PM_{10}$. Also, they were much alike in those of the UM-ADAM model simulated by the Korean Meteorological Administration. Meanwhile, the spatial distributions of $PM_{10}$ concentrations during the Asian dust events had relevance to those of both the wind speed of u component ($ms^{-1}$) and the PBL height (m). We performed a regressive analysis between $PM_{10}$ concentrations and two meteorological variables (u component and PBL) in the strong dust event in autumn (CASE 1, on 11 to 23 March 2010) and the weak dust event in spring (CASE 2, on 19 to 20 March 2011), respectively.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.123-130
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• 2008

Purpose : Motion effects in parallel magnetic resonance imaging (MRI) are investigated. Parallel MRI is known to be robust to motion due to its reduced acquisition time. However, if there are some involuntary motions such as heart or respiratory motions involved during the acquisition of the parallel MRI, motion artifacts would be even worse than those in conventional (non-parallel) MRI. In this paper, we defined several types of motions, and their effects in parallel MRI are investigated in comparisons with conventional MRI. Materials and Methods : In order to investigate motion effects in parallel MRI, 5 types of motions are considered. Type-1 and 2 are periodic motions with different amplitudes and periods. Type-3 and 4 are segment-based linear motions, where they are stationary during the segment. Type-5 is a uniform random motion. For the simulation, Cartesian and spiral grid based parallel and non-parallel (conventional) MRI are used. Results : Based on the motions defined, moving artifacts in the parallel and non-parallel MRI are investigated. From the simulation, non-parallel MRI shows smaller root mean square error (RMSE) values than the parallel MRI for the periodic (type-1 and 2) motions. Parallel MRI shows less motion artifacts for linear(type-3 and 4) motions where motions are reduced with shorter acquisition time. Similar motion artifacts are observed for the random motion (type-5). Conclusion : In this paper, we simulate the motion effects in parallel MRI. Parallel MRI is effective in the reduction of motion artifacts when motion is reduced by the shorter acquisition time. However, conventional MRI shows better image quality than the parallel MRI when fast periodic motions are involved.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.884-892
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• 2014

The purpose of this study was to investigate the drying characteristics and drying models of Ainsliaea acerifolia Sch. Bip. using far-infrared thin layer drying. Far-infrared thin layer drying test on Ainsliaea acerifolia Sch. Bip. was conducted at two air velocities of 0.6 and 0.8 m/sec, as well as three drying temperatures of 40, 45, and $50^{\circ}C$ respectively. The drying models were estimated using coefficient of determination and root mean square error. Drying characteristics were analyzed based on factors such as drying rate, leaf color changes, antioxidant activity, and contents of polyphenolics and flavonoids. The results revealed that increases in drying temperature and air velocity caused a reduction in drying time. The Thompson model was considered suitable for thin layer drying using far-infrared radiation for Ainsliaea accerifolia Sch. Bip. Greenness and yellowness values decreased and lightness values increased after far-infrared thin layer drying, and the color difference (${\Delta}E$) values at $40^{\circ}C$ were higher than those at $45^{\circ}C$ and $50^{\circ}C$. The antioxidant properties of Ainsliaea acerifolia Sch. Bip. decreased under all far-infrared thin layer drying conditions, and the highest polyphenolic content (37.9 mg/g), flavonoid content (22.7 mg/g), DPPH radical scavenging activity (32.5), and ABTS radical scavenging activity (31.1) were observed at a drying temperature of $40^{\circ}C$ with an air velocity of 0.8 m/sec.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.9
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• pp.1358-1365
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• 2016

The purpose of this study was to verify the drying characteristics of seasoned red pepper sauce and establish optimal drying conditions for far infrared drying of seasoned red pepper sauce. Seasoned red pepper sauce, which was dried by heated air, was used. One kg of seasoned red pepper was spread at thicknesses of 10 and 20 mm and dried by a far infrared dryer until a final moisture content of $15{\pm}0.5%$. The far infrared dryer conditions were air velocity of 0.6, 0.8 m/s and drying temperatures of 60, 70, and $80^{\circ}C$. The drying models were estimated using a determination coefficient and root mean square error. Drying characteristics were analyzed based on factors such as drying rate, color changes, content of capsaicinoids, and energy consumption. The results can be summarized as follows. The drying rate (that is, drying time) tended to be reduced as temperature and air velocity for drying increased. The Page and Henderson models were suitable for drying of seasoned red pepper sauce by a far infrared dryer. Redness decreased after far infrared drying under all experimental conditions. The color difference was 18.18 under the following conditions: thickness 20 mm, temperature $70^{\circ}C$, and air velocity 0.8 m/s. This value was slightly higher than those under other far infrared drying conditions. The capsaicinoid properties of seasoned red pepper sauce decreased under all far infrared drying conditions. The highest capsaicin (19.91 mg/100 g) and dihydrocapsaicin (12.87 mg/100 g) contents were observed at a thickness of 10 mm, temperature of $80^{\circ}C$, and air velocity of 0.8 m/s. Energy consumption decreased with higher temperature, slower air velocity, and thinner seasoned red pepper sauce.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.4
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• pp.275-283
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• 2010

This experiment was conducted to construct process models to estimate grain weight (GW) and grain nitrogen content (GN) in rice. A model was developed to describe the dynamic pattern of GW and GN during grain-filling period considering their relationships with temperature, solar radiation and growth traits such as LAI, shoot dry-weight, shoot nitrogen content, grain number during grain filling. Firstly, maximum grain weight (GWmax) and maximum grain nitrogen content (GNmax) equation was formulated in relation to Accumulated effective temperature (AET) ${\times}$ Accumulated radiation (AR) using boundary line analysis. Secondly, GW and GN equation were created by relating the difference between GW and GWmax and the difference between GN and GNmax, respectively, with growth traits. Considering the statistics such as coefficient of determination and relative root mean square of error and number of predictor variables, appropriate models for GW and GN were selected. Model for GW includes GWmax determined by AET ${\times}$ AR, shoot dry weight and grain number per unit land area as predictor variables while model for GN includes GNmax determined by AET ${\times}$ AR, shoot N content and grain number per unit land area. These models could explain the variations of GW and GN caused not only by variations of temperature and solar radiation but also by variations of growth traits due to different sowing date, nitrogen fertilization amount and row spacing with relatively high accuracy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.