• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.176-184
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• 2011

Cold air on sloping surfaces flows down to the valley bottom in mountainous terrain at calm and clear nights. Based on the assumption that the cold air flow may be the same as the water flow, current models estimate temperature drop by regarding the cold air accumulation at a given location as the water-like free drainage. At a closed catchment whose outlet is blocked by man-made obstacles such as banks and roads, however, the water-like free drainage assumption is no longer valid because the cold air accumulates from the bottom first. We developed an empirical model to estimate quantitatively the effect of cold pool on nocturnal temperature in a closed catchment. In our model, a closed catchment is treated like a "vessel", and a digital elevation model (DEM) was used to calculate the maximum capacity of the cold pool formed in a closed catchment. We introduce a topographical variable named "shape factor", which is the ratio of the cold air accumulation potential across the whole catchment area to the maximum capacity of the cold pool to describe the relative size of temperature drop at a wider range of catchment shapes. The shape factor is then used to simulate the density profile of cold pool formed in a given catchment based on a hypsometric equation. The cold lake module was incorporated with the existing model (i.e., Chung et al., 2006), generating a new model and predicting distribution of minimum temperature over closed catchments. We applied this model to Akyang valley (i.e., a typical closed catchment of 53 $km^2$ area) in the southern skirt of Mt. Jiri National Park where 12 automated weather stations (AWS) are operational. The performance of the model was evaluated based on the feasibility of delineating the temperature pattern accurately at cold pool forming at night. Overall, the model's ability of simulating the spatial pattern of lower temperature were improved especially at the valley bottom, showing a similar pattern of the estimated temperature with that of thermal images obtained across the valley at dawn (0520 to 0600 local standard time) of 17 May 2011. Error in temperature estimation, calculated with the root mean square error using the 10 low-lying AWSs, was substantially decreased from $1.30^{\circ}C$ with the existing model to $0.71^{\circ}C$ with the new model. These results suggest the feasibility of the new method in predicting the site-specific freeze and frost warning at a closed catchment.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.217-223
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• 2008

Amylose and protein contents are important traits determining the edible quality of rice, especially in East Asian countries. Near-Infrared Reflectance Spectroscopy (NIRS) has become a powerful tool for rapid and nondestructive quantification of natural compounds in agricultural products. To test the practically of using NIRS for estimation of brown rice amylose and protein contents, the spectral reflectances ($400{\sim}2500\;nm$) of total 9,483 accessions of rice germplasm in Rural development Administration (RDA) Genebank ere obtained and compared to chemically determined amylose and protein content. The protein content of tested 119 accessions ranged from 6.5 to 8.0% and 25 accessions exhibited protein contents between 8.5 to 9.5%. In case of amylose content, all tested accessions ranged from 18.1 to 21.7% and the grade from 18.1 to 19.9% includes most number of accessions as 152 and 4 accessions exhibited amylose content between 20.5 to 21.7%. The optimal performance calibration model could be obtained from original spectra of brown rice using MPLS (Modified Partial Least Squares) with the correlation coefficients ($r_2$) for amylose and protein content were 0.865 and 0.786, respectively. The standard errors of calibration (SEC) exhibited good statistic values: 2.078 and 0.442 for amylose and protein contents, respectively. All these results suggest that NIR spectroscopy may serve as reputable and rapid method for quantification of brown rice protein and amylose contents in large numbers of rice germplasm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.233-241
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• 2016

Experiments were carried out to quantify the topographic effects on attenuation of sunshine in complex terrain and the results are expected to help convert the coarse resolution sunshine duration information provided by the Korea Meteorological Administration (KMA) into a detailed map reflecting the terrain characteristics of mountainous watershed. Hourly shaded relief images for one year, each pixel consisting of 0 to 255 brightness value, were constructed by applying techniques of shadow modeling and skyline analysis to the 3m resolution digital elevation model for an experimental watershed on the southern slope of Mt. Jiri in Korea. By using a bimetal sunshine recorder, sunshine duration was measured at three points with different terrain conditions in the watershed from May 15, 2015 to May 14, 2016. The brightness values of the 3 corresponding pixel points on the shaded relief map were extracted and regressed to the measured sunshine duration, resulting in a brightness-sunshine duration response curve for a clear day. We devised a method to calibrate this curve equation according to sky condition categorized by cloud amount and used it to derive an empirical model for estimating sunshine duration over a complex terrain. When the performance of this model was compared with a conventional scheme for estimating sunshine duration over a horizontal plane, the estimation bias was improved remarkably and the root mean square error for daily sunshine hour was 1.7hr, which is a reduction by 37% from the conventional method. In order to apply this model to a given area, the clear-sky sunshine duration of each pixel should be produced on hourly intervals first, by driving the curve equation with the hourly shaded relief image of the area. Next, the cloud effect is corrected by 3-hourly 'sky condition' of the KMA digital forecast products. Finally, daily sunshine hour can be obtained by accumulating the hourly sunshine duration. A detailed sunshine duration distribution of 3m horizontal resolution was obtained by applying this procedure to the experimental watershed.

• The Korean Journal of Physiology
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• v.1 no.2
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• pp.169-175
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• 1967

An experiment was designed to see if the hippocampus exerts any influence upon the aggressive behavior of male rats. Fighting between rats was observed for the estimation of aggressiveness. Seventeen rats in which the hippocampus was almost totally removed through a small hole with a diameter around 3 mm made in the neocortex at the boundary between the parietal and occipital lobes (hippocampal group), 8 rats with similar neocortical damage alone (operated control group), and 17 normal control rats (normal group) were prepared and subjected to the experiment 3 months after the operation. Applying electric shock of short duration to the feet in a box with grid floor, a fight was provoked between an animal belonging to the hippocampal group and one belonging to the nor-mal group, between a rat of the hippocampal group and one of the operated control group, and also between a rat of the operated control group and one of the normal group. Three observers judged the performance of each animal independently and described it as winning, defeated, tied, or non-fighting. Fifteen shocked trials were administered to each pair of animals with around 2 minutes' interval between each trial. An animal received a 'judging score' of 3 when it won more frequently than was defeated, a judging score of 2 when it won as frequently as was defeated, when all fights were tied, or when no fighting occurred, while it received a judging score of 1 when it won less frequently than was defeated. Group differences in performances were analyzed in terms of judging score using Kolmogorov-Smirnov test for one sample. The results obtained were as follows: 1. In the fights between the hippocampal and the normal groups, the hippocampal animals made significantly better judging scores than the normal animals did (Table 1). 2. There was no significant difference between the hippocampal and the operated control group as to the judging scores they made in the course of fights between the two groups. However, the hippocampal animals tended to dominate over the operated control group as judged by comparing the total 'winning' of the former (30) to that of the latter (14) (Table 2). 3. The total judging score made by the operated control group in the course of the fights against the normal group was not significantly superior to that made by the normal group (Table 3). It was inferred from the above results that, though inconspicuous, the hippocampus tended to exert an inhibitory influence upon the aggressive behavior of male rats.

• Journal of Animal Science and Technology
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• v.46 no.2
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• pp.145-154
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• 2004

This study was conducted to estimate genetic parameter of Duroc, Landrace and Yorkshire breeds based on the on-farm performance tested records of 57,316 pigs under the supervision of Korean Animal Improvement Association from 1992 to 1999. Genetic parameters were estimated with a multiple trait animal model by using DF - REML. The result obtained in this study was summarized as follow ; The estimated heritabilities of Duroc, Landrace and Yorkshire were 0.46${\sim}$0.65 for the average backfat thickness, 0.28${\sim}$0.31 for loin depth, 0.50～0.60 for percent lean, 0.45${\sim}$0.55 for the average daily gain, 0.38${\sim}$0.50 for age at 90kg, respectively. Phenotypic correlation of average backfat thickness with loin depth, percent lean, average daily gain and age at 90㎏ for the three breeds were -0.12${\sim}$-0.01, -0.81${\sim}$-0.76, 0.34${\sim}$0.46, and -0.41${\sim}$-0.33, respectively. Phenotypic correlation of loin depth with percent lean, average daily gain and age at 90kg were 0.12${\sim}$0.23, 0.03${\sim}$0.21, and -0.17${\sim}$-0.03, respectively. Phenotypic correlation of percent lean with average daily gain and age at 90kg were -0.37${\sim}$-0.26 and 0.26～0.35, respectively. Phenotypic correlation of average daily gain with age at 90kg was -0.97${\sim}$-0.95. The estimated genetic correlation coefficients of average backfat thickness with loin depth, percent lean, average daily gain and age at 90kg estimated for the three breeds were -0.17${\sim}$0.03, -0.79${\sim}$-0.69, 0.24${\sim}$0.45 and -0.41${\sim}$-0.19, respectively. The estimated genetic correlation coefficients of loin depth with percent lean, average daily gain and age at 90kg were 0.11～0.19, 0.23 and -0.30～-0.20, respectively. The estimated correlation coefficients of percent lean with average daily gain and age at 90kg were -0.36${\sim}$-0.13 and 0.10～0.34, respectively. The estimated genetic correlation coefficients of average daily gain with age at 90㎏ was -0.96${\sim}$-0.95.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.200-211
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• 2009

A mathematical modeling program called Soil and Water Assessment Tool (SWAT) developed by USDA was applied to Kyongan stream watershed. It was run under BASINS (Better Assessment Science for Integrating point and Non-point Sources) program, and the model was calibrated and validated using KTMDL monitoring data of 2004${\sim}$2008. The model efficiency of flow ranged from very good to fair in comparison between simulated and observed data and it was good in the water quality parameters like flow range. The model reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The results of pollutant loads estimation as yearly (2004${\sim}$2008), pollutant loadings from 2006 were higher than rest of year caused by high precipitation and flow. Average non-point source (NPS) pollution rates were 30.4%, 45.3%, 28.1% for SS, TN and TP respectably. The NPS pollutant loading for SS, TN and TP during the monsoon rainy season (June to September) was about 61.8${\sim}$88.7% of total NPS pollutant loading, and flow volume was also in a similar range. SS concentration depended on precipitation and pollution loading patterns, but TN and TP concentration was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. SWAT based on BASINS was applied to the Kyongan stream watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and non-point sources in watershed scale.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Korean Journal of Poultry Science
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• v.47 no.4
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• pp.267-274
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• 2020

This study was conducted to estimate genetic parameters for growth and egg production traits in Black Korean native chicken (L strain) and Korean White Leghorn (F, K strains) using a multi-traits animal model BLUP. Traits used for this study were body weight at 150 days (BW150) and 270 days (BW270), age at first egg (DAY1st), egg weight at first egg (EW1st) and 270 days (EW270), and number of eggs laid by 270 days (EP270), and included 68,688 pedigree and 123,905 performance records collected from 2001 to 2013. In L, F, K strains, heritability estimates of BW150 were high (0.48, 0.52 and 0.50, respectively); of BW270 were high (0.56, 0.57 and 0.56); of DAY1st were medium to high (0.45, 0.39 and 0.31); of EW1st were low (0.15, 0.16 and 0.15); of EW270 were high (0.58, 0.55 and 0.59) and of EP270 were moderate (0.22, 0.21 and 0.20). The genetic and phenotypic correlation of DAY1st with EP270 were highly negative (-0.73 to -0.63 and -0.48 to -0.42). The genetic and phenotypic correlation of EP270 with BW150 and BW270, respectively were low negative (-0.16 to 0.01 and -0.14 to -0.03) and low to moderate positive (-0.08 to 0.07 and -0.13 to 0.04). The genetic and phenotypic correlation of EW270 with BW150 and BW270, respectively were moderate to high positive (0.39 to 0.49 and 0.36 to 0.46) and (0.29 to 0.33 and 0.34 to 0.37). The study showed that there is a potential for genetic improvement of Korean Indigenous chicken through selection program.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.