• Korean Journal of Agricultural Science
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• v.24 no.2
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• pp.145-155
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• 1997

The large scaled field test by prefabricated vertical drains was performed to evaluate the superiority of vertical discharge capacity for drain materials through compare and analyze the time-settlement behavior with drain spacing and the compression index and consolidation coefficient obtained by laboratory experiments and field monitoring system. 1. The relation of measurement settlement($S_m$) versus design settlement($S_t$) and measurement consolidation ratio($U_m$) versus design consolidation ratio($U_t$) were shown $S_m=(1.0{\sim}1.1)S_t$, $U_m=(1.13{\sim}1.17)U_t$ at 1.0m drain spacing and $S_m=(0.7{\sim}0.8)S_t$, $U_m=(0.92{\sim}0.99)U_t$ at l.5m drain spacing, respectively. 2. The relation of field compressing index($C_{cfield}$) and virgin compression index($V_{cclab.}$) was shown $C_{cfield}=(1.0{\sim}1.2)V_{cclab.}$, But it was nearly same value when considered the error with determination method of virgin compression index and prediction method of total settlement. 3. Field consolidation coefficient was larger than laboratory consolidation coefficient, and the consolidation coefficient ratio($C_h/C_v$) were $C_h=(2.4{\sim}3.0)C_v$. $C_h=(3.5{\sim}4.3)C_v$ at 1.0m and 1.5m drain spacing and increased with increasing of drain spacing. 4. The evaluation of vertical discharge capacity with drain spacing from the results of the consolidation coefficient ratio showed largely superior in case the Mebra drain and Amer drain than other drain materials at 1.0m and 1.5m drain spacing, while the values showed nearly same value in case same drain spacing.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.585-598
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• 1997

Background : Although there are growing concerns about the adverse health effect of air pollution, not much evidence on health effect of current air pollution level had been accumulated yet in Korea. This study was designed to evaluate the chronic health effect of ai. pollution using Korean Medical Insurance Corporation (KMIC) data and air quality data. Medical insurance data in Korea have some drawback in accuracy, but they do have some strength especially in their national coverage, in having unified ID system and individual information which enables various data linkage and chronic health effect study. Method : This study utilized the data of Korean Environmental Surveillance System Study (Surveillance Study), which consist of asthma, acute bronchitis, chronic obstructive pulmonary diseases (COPD), cardiovascular diseases (congestive heart failure and ischemic heart disease), all cancers, accidents and congenital anomaly, i. e., mainly potential environmental diseases. We reconstructed a nested case-control study wit5h Surveillance Study data and air pollution data in Korea. Among 1,037,210 insured who completed? questionnaire and physical examination in 1992, disease free (for chronic respiratory disease and cancer) persons, between the age of 35-64 with smoking status information were selected to reconstruct cohort of 564,991 persons. The cohort was followed-up to 1995 (1992-5) and the subjects who had the diseases in Surveillance Study were selected. Finally, the patients, with address information and available air pollution data, left to be 'final subjects' Cases were defined to all lung cancer cases (424) and COPD admission cases (89), while control groups are determined to all other patients than two case groups among 'final subjects'. That is, cases are putative chronic environmental diseases, while controls are mainly acute environmental diseases. for exposure, Air quality data in 73 monitoring sites between 1991 - 1993 were analyzed to surrogate air pollution exposure level of located areas (58 areas). Five major air pollutants data, TSP, $O_3,\;SO_2$, CO, NOx was available and the area means were applied to the residents of the local area. 3-year arithmetic mean value, the counts of days violating both long-term and shot-term standards during the period were used as indices of exposure. Multiple logistic regression model was applied. All analyses were performed adjusting for current and past smoking history, age, gender. Results : Plain arithmetic means of pollutants level did not succeed in revealing any relation to the risk of lung cancer or COPD, while the cumulative counts of non-at-tainment days did. All pollutants indices failed to show significant positive findings with COPD excess. Lung cancer risks were significantly and consistently associated with the increase of $O_3$ and CO exceedance counts (to corrected error level -0.017) and less strongly and consistently with $SO_2$ and TSP. $SO_2$ and TSP showed weaker and less consistent relationship. $O_3$ and CO were estimated to increase the risks of lung cancer by 2.04 and 1.46 respectively, the maximal probable risks, derived from comparing more polluted area (95%) with cleaner area (5%). Conclusions : Although not decisive due to potential misclassication of exposure, these results wert drawn by relatively conservative interpretation, and could be used as an evidence of chronic health effect especially for lung cancer. $O_3$ might be a candidate for promoter of lung cancer, while CO should be considered as surrogated measure of motor vehicle emissions. The control selection in this study could have been less appropriate for COPD, and further evaluation with another setting might be necessary.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.299-309
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• 2014

This paper evaluated the possibility for 1/5,000 digital topographic mapping by using PLEIADES images of 0.5m GSD(Ground Sampling Distance) resolution that has recently launched. Those results of check points by applying the initial RPC(Rational Polynomial Coefficient) of PLEIADES images came out as; RMSE of those were $X={\pm}1.806m$, $Y={\pm}2.132m$, $Z={\pm}1.973m$. Also, if we corrected geometric correction using 16 GCP(Ground Control Point)s, the results of RMSE became $X={\pm}0.104m$, $Y={\pm}0.171m$, $Z={\pm}0.036m$, and t he RMSE of check points were $X={\pm}0.357m$, $Y={\pm}0.239m$, $Z={\pm}0.188m$; which of those results indicated the accuracy of standard adjustment complied in error tolerances of the 1/5,000 scale. Additionally, we converted coordinates of points, obtained by TerraSAR. for comparing with measurements from GPS(Global Positioning System) surveying. The RMSE of comparing converted and GPS points were $X={\pm}0.818m$, $Y={\pm}0.200m$, $Z={\pm}0.265m$, which confirmed the possibility for 1/5,000 digital topographic mapping with PLEIADES images and GCPs. As method of obtaining GCPs in unaccessible area, however, the outcome evaluation of GCPs extracted from TerraSAR images was not acceptable for 1/5,000 digital topographic mapping. Therefore, we considered that further researches are needed on applicability of GCPs extracted from TerraSAR images for future alternative method.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.108-115
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• 2017

We report the assembly procedure and performance evaluation of a visible and near-infrared spectrometer in the wavelength region of 400-900 nm, which is later to be combined with fore-optics (a telescope) to form a f/2.5 imaging spectrometer with a field of view of ${\pm}7.68^{\circ}$. The detector at the final image plane is a $640{\times}480$ charge-coupled device with a $24{\mu}m$ pixel size. The spectrometer is in an Offner relay configuration consisting of two concentric, spherical mirrors, the secondary of which is replaced by a convex grating mirror. A double-pass test method with an interferometer is often applied in the assembly process of precision optics, but was excluded from our study due to a large residual wavefront error (WFE) in optical design of 210 nm ($0.35{\lambda}$ at 600 nm) root-mean-square (RMS). This results in a single-path test method with a Shack-Hartmann sensor. The final assembly was tested to have a RMS WFE increase of less than 90 nm over the entire field of view, a keystone of 0.08 pixels, a smile of 1.13 pixels and a spectral resolution of 4.32 nm. During the procedure, we confirmed the validity of using a Shack-Hartmann wavefront sensor to monitor alignment in the assembly of an Offner-like spectrometer.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.835-848
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• 2021

In Jeju Island which has peculiarity for its geological features and hydrology system, hydrological factor analysis for the effective water management is necessary. Because in-situ hydro-meteorological data is affected by surrounding environment, the in-situ dataset could not be the spatially representative for the study area. For this reason, remote sensing data may be used to overcome the limit of the in-situ data. In this study, applicability assessment of MOD16 evapotranspiration data, Globas Land Data Assimilation System (GLDAS) based evapotranspiration/soil moisture data, and Advanced SCATterometer (ASCAT) soil moisture product which were evaluated their applicability on other study areas was conducted. In the case of evapotranspiration, comparison with total precipitation and flux-tower based evapotranspiration were conducted. And for soil moisture, 6 in-situ data and ASCAT soil moisture product were compared on each site. As a result, 57% of annual precipitation was calculated as evapotranspiration, and the correlation coefficient between MOD16 evapotranspiration and GLDAS evapotranspiration was 0.759, which was a robust value. The correlation coefficient was 0.434, indicating a relatively low fit. In the case of soil moisture, in the case of the GLDAS data, the RMSE value was less than 0.05 at all sites compared to the in-situ data, and a statistically significant result was obtained as a result of the significance test of the correlation coefficient. However, for satellite data, RMSE over than 0.05 were found at Wolgak and there was no correlation at Sehwa and Handong points. It is judged that the above results are due to insufficient quality control and spatial representation of the evapotranspiration and soil moisture sensors installed in Jeju Island. It is estimated as the error that appears when adjacent to the coast. Through this study, the necessity of improving the existing ground observation data of hydrometeorological factors is emphasized.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.819-833
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• 2021

This study is to evaluate applicability of linkage modeling using PHABSIM (Physical Habitat Simulation System) and SWAT (Soil and Water Assessment Tool) and to estimate ecological flow for target fishes of Andong downstream (4,565.7 km²). The SWAT was established considering 2 multi purpose dam (ADD, IHD) and 1 streamflow gauging station (GD). The SWAT was calibrated and validated with 9 years (2012 ~ 2020) data of 1 stream (GD) and 2 multi-purpose dam (ADD, IHD). For streamflow and dam inflows (GD, ADD and IHD), R², NSE and RMSE were 0.52 ~ 0.74, 0.48 ~ 0.71, and 0.92 ~ 2.51 mm/day respectively. As a result of flow duration analysis for 9 years (2012 ~ 2020) using calibrated streamflow, the average Q185 and Q275 were 36.5 m³/sec (-1.4%) and 23.8 m³/sec (0%) respectively compared with the observed flow duration and were applied to flow boundary condition of PHABSIM. The target stream was selected as the 410 m section where GD is located, and stream cross-section and hydraulic factors were constructed based on Nakdong River Basic Plan Report and HEC-RAS. The dominant species of the target stream was Zacco platypus and the sub-dominant species was Puntungia herzi Herzenstein, and the HSI (Habitat Suitability Index) of target species was collected through references research. As the result of PHABSIM water level and velocity simulation, error of Q185 and Q275 were analyzed -0.12 m, +0.00 m and +0.06 m/s, +0.09 m/s respectively. The average WUA (Weighted Usable Area) and ecological flow of Zacco platypus and Puntungia herzi Herzenstein were evaluated 76,817.0 m²/1000m, 20.0 m³/sec and 46,628.6 m²/1000m, 9.0 m³/sec. This results indicated Zacco platypus is more adaptable to target stream than Puntungia herzi Herzenstein.