• Korean Journal of Ecology and Environment
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• v.44 no.2
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• pp.172-177
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• 2011

The study sought to determine the efficient management of Korean aucha perch by estimating the potential yield (PY), which means the maximum sustainable yield (MSY) based on the optimal stock, in the mid-upper region of the Seomjin River watershed from August 2008 to April 2009. The stock assessment was conducted by the swept area method and PY was estimated by a modified fisheries management system based on the allowable biological catch. Also, the yield-per-recruit analysis (Beverton and Holt, 1957) was used to review the efficient management of resource, Coreoperca herzi. The age at first capture ($t_c$) was 1.464 age and converted body length was 7.8 cm. Concerning current fishing intensities, the instantaneous coefficient of fishing mortality (F) was estimated to be 0.061 $year^{-1}$; yield-per-recruit analysis estimated the current yield per recruit as 4.124 g with F and $t_c$. The fishing mortality of Allowable Biological Catch ($F_{ABC}$) based on the current $t_c$ and F was estimated to be 0.401 $year^{-1}$, therefore, the optimum fishing intensities could be achieved at the higher fishing intensity for Coreoperca herzi. The calculated annual stock of Coreoperca herzi was 3,048 kg, the potential yield was estimated to be 861 kg with $t_c$ and $F_{ABC}$ at the fixed current level. Using yield-per-recruit analysis, if F and $t_c$ were set at 0.643 $year^{-1}$ and 3 age, respectively, the yield per recruit would be predicted to increase 3.4-fold, from 4.12 g to 13.84 g.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.1
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• pp.151-161
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• 2014

As concerns have been raised about the increasing number of children with food allergies, the management of food allergies through the consideration of school meals is an emerging issue. This study investigated the perception and practices regarding food allergy of elementary and middle school nutrition teachers in the Jeonnam area. A total of 236 nutritionists/nutrition teachers participated in the survey and completed questionnaires. The foods most reported to cause allergic reactions were peach, eggs, peanuts, shrimps, mackerel, and milk. Participants reported that the major tasks to be completed for management of food allergies: the estimated number of students with food allergies, the offering of allergy-free or alternative foods and informing families of foods that may cause an allergic reaction. A majority of the participants (94%) recognized that the nutrition teacher has the primary role in managing students with food allergies in school. To manage these students, nutrition teachers mostly reported informing of allergic foods/ingredients in the school menu and the estimation of students with food allergy. The percentage of participants who experienced education programs on food allergies was 16.9%, whereas 97% of participants answered that a good professional education regarding allergies for nutrition teachers is required. The knowledge level evaluated with objective questions was significantly higher than the self-estimated knowledge level. In conclusion, nutrition teachers understood the tasks regarding food allergy thoroughly and that, the tasks are relatively under-practiced. To improve the management of food allergies in school meals, professional education programs regarding food allergies should be provided for nutrition teachers.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.75-82
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• 2010

This study formed an estimation of the visual characteristics of urban bridges in Yanghwaro in the Gyeongui Railroad Area using a landscape simulation. Existing theses have formerly only suggested directions for design based on visual preference, but there is as yet no research on the practical process of landscape design. As a result, it is difficult to directly apply this to bridge design. This study found a potential bridge site and presented a direction for bridge design in order to improve the image of the surrounding urban landscape by surveying the visual effects and landscape preferences of different bridge types. An urban landscape was produced using a landscape simulation model and was made the background for the survey. Five bridge types--Girder, Arch, Truss, Cable and Suspension--were selected and presented. The shapes of the bridges were selected based on the floor plan. The results of this study are as follows. In a preference analysis, every bridge except Girder was evaluated as a positive influence. When rating the image, 'artificial' was rated significantly higher than other traits when assessing the background image. When the Girder Bridge was introduced, 'stable' and 'orderly' were both rated highly while 'stable', 'beautiful', 'orderly' and 'interesting' were high with the introduction of the Arch Bridge. 'Beautiful', 'stable', and 'orderly' were given a high value in the introduction of the Truss Bridge and every image except 'natural', 'harmony' and 'orderly' were highly rated in the introduction of the Cable Bridge. Further, every image but 'natural' was highly rated with the introduction of the Suspension Bridge. Based on the analysis of the landscape, there is a difference in preference before and after modeling a bridge type, while the bridge itself is an influence when it is the main object of the simulated scene. This study researched only the shape of the bridge as a part of the landscape but other elements such as stability, economics, and construction are also factors in the design of a bridge. Stability, economics, construction and other factors must be considered when selecting a bridge type in the future.

• 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.

• Journal of Wetlands Research
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• v.17 no.2
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• pp.193-202
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• 2015

In this study, a long term monitering of nonpoint source pollution runoff is conducted at the area of transportation related and EMCs(Event Mean Concentrations) in terms of water quality items, such as BOD, $COD_{Mn}$, SS, T-N and T-P are determined for each not only runoff event and but also observation site. On the other hands, SWMM(Storm Water Management Model) model is constructed using the data collected in the transportation areas selected. Model calibration and verification of SWMM is carried out based on the data collected. And simulated EMCs was compared with observed EMCs by monitoring and prior studies. SWMM applicability estimation was Using the compared result. The results of simulation showed that BOD 5.787 ~ 14.475 mg/L, $COD_{Mn}$ 12.946 ~ 59.611 mg/L, SS 13.742 ~ 46.208 mg/L, T-N 2.037 ~ 5.213 mg/L, T-P 0.117 ~ 0.415 mg/L. And a differential between simulated EMCs and observed EMCs is too low so comparing result show high fit(BOD 4.27 %, $COD_{Mn}$ 4.87%, SS 2.31%, T-N 5.78%, T-P 14.45%). A results of compared with the prior studies, BOD and T-P are included range of prior studies, $COD_{Mn}$ and SS are lower than range of prior studies, T-N is higher than range of prior studies. Differential between simulated EMCs and prior studies EMCs was showing for survey seasonal and changing land-use, so from now on, EMCs of using the internal representatives value will be calculated by more monitoring toward various precipitation events.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.83-89
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• 2010

The objective of this study was to investigate the effect of the environmental and genetic factors on the carcass traits of Korean cattle. We have used the data of 22,954 Korean cattle slaughtered from 2005 to 2009 in Gyeongnam region and estimated the genetic parameters of 36,868 cattle including the pedigree individuals by means of EM-REML analytical method. In summary, the heritability of the carcass weight, eye muscle area, backfat thickness and marbling score was 0.39, 0.30, 0.33 and 0.62, respectively. The carcass weight and the eye muscle area showed high correlation between them with the genetic correlation of 0.86 and the phenotypic correlation of 0.72. The high heritability of marbling score is assumed to be the result of focusing the breed improvement on the quality of the meat. Through this study, it is considered that the Korean cattle in Gyeongnam region are improving, which will thus contribute to the increase of the farmer's income. Additional study on the economic trait must be carried out to obtain clearer results that will lead to further improvement of Korean cattle.

• 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.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.120-132
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• 2022

Recently, the rapid increase in vacant houses in urban areas has caused various problems such as worsening urban landscape, causing safety accidents, crime accidents, and hygiene problems. According to the Statistics Korea Future Population Estimation results, the growth rate of Korean population and households is expected to continue to decrease, which is likely to lead to an increase in the occurrence of vacant houses. If the problem caused by the occurrence of vacant houses is neglected, it causes not only a physical decline such as a deterioration of the residential environment but also a social and economic decline. In order to solve this problem, it is necessary to grasp the spatial distribution characteristics of vacant houses at the local level considering the existence of regional characteristics and spatial influence. Therefore, in this study, in order to measure global spatial autocorrelation, the analysis was conducted centering on the old downtown area of Busan, where there are many vacant houses through Moran's I and Geographically Weighted Regression(GWR). In addition, the distribution of vacant houses in different spatial units in Eup_Myeon_Dong and Census was analyzed to evaluate the possibility of Modifiable Areal Unit Problem(MAUP), which differ in the results of spatial analysis as the spatial analysis units change. As a result of the analysis, the occurrence of vacant houses by Eup_Myeon_Dong in the old downtown area of Busan had spatial heterogeneity, and the spatial analysis results of vacant houses were different as the spatial analysis units were different. Accordingly, in order to understand the exact distribution characteristics of vacant house occurrence, spatial dimensions using the GWR model should be considered, and it is suggested that consideration of the MAUP is necessary.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.