• Land and Housing Review
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• v.4 no.1
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• pp.77-87
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• 2013

About 1,800 villages have released from Greenbelt since Greenbelt-reform-policy for readjustment of the area was promoted after 1997. Even though the government intended to attract planned development & improvement of these lifted villages through District Unit Plan and designating the lifted area as low-rise and low-density zoning considering the characteristics of the Greenbelt region, there are still many problems to be solved: a lack of funds, insufficient capability for self-improvement and unexecuted SOCs in long-term etc. It seems that these problems are caused by focusing on the lifting areas itself instead of researching deeply the condition and characteristics of the villages and searching proper direction/plans of improvement before lifting Greenbelt In addition, the existing plan of village improvement and management was not considering physical and spacial characteristics of the areas, social and economic situation of residents and relationship between the villages and surrounding cities, though these conditions are different among each villages, and the related regulations are applied uniformly across all the villages and those have been causing many civil appeals and environmental problems. In these respects, this study aims to consider the problems of the lifted villages using the existing researches on them and to make typology by characteristics-data of the villages and to establish improvement strategies of each types. In this study, the villages were classified into 5 types as a result of cluster analysis on 424 villages among all 1,800 through variables of locational potentiality : location, accessibility, size and form of village, condition of regulations etc. According to function of the villages, they were divided into 4 types: urban-type, rural-type, industrial-type and neighborhood-centered-type. This study also drew 4 improvement-strategy-types by combination of locational potentiality and village-function : type of improving life-environment, type of improving production-infra, type of inducing-planned-improvement and type of constructing center-of living-circle. Finally, this study suggested the directions of the each 4 types to desirable improvement and management which could be used to make and complement plans for village improvement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.1-10
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• 2022

Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.2
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• pp.95-110
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• 2022

This study was conducted to determine the extent to which climate change is expanding areas in which barley can be successfully cultivated. In 2019 and 2020, we collected data on areas that had requested certified seeds from the Korea Seed and Variety Service to determine potential cultivation areas. In addition, we surveyed the growth and yield of different types of barley in fields. Certified seeds of hulled and dehulled barley were requested by farmers across Korea from the Korea Seed and Variety Service in both years. Areas that were provided with certified seeds were considered potential barley cultivation areas. The varieties and use rates of certified seeds varied based on the barley type and region. For example, certified seeds of dehulled barley in 2019 and 2020 were not used in some areas, whereas in others, these seeds constituted 100% of the seeds sown for barley crops. In 2019 and 2020, the average sowing days in Korea were from October 17 to November 9 for dehulled barley, October 26 to November 13 for hulled barley, October 19 to November 5 for malting barley, and October 3 to November 1 for naked oats. Thus, the sowing days of the barley types varied depending on the area and year they were used. For example, in the case of hulled barley in Jeonnam, some farmers sowed until December 12. The yield per 10 a of barley cultivation was typically higher in the main production areas than in the cultivation limit areas. In extreme cases, harvest was impossible in some cultivation limited areas, such as Gangwon-do. Based on the current 20-year January minimum average temperature (JMAT) in Korea (2002-2021), climate change scenarios suggest that barley cultivation is feasible, provided that the minimum temperature in January is no lower than -10℃, -8℃, and -4℃ for hulled barley, dehulled barley, and for malting barley and naked oats, respectively. Additionally, cultivation of barley across South Korea seems feasible based on data on certified barley seeds by area. Although both JMAT and certified seed data suggest that barley cultivation across Korea is feasible, our survey results of barley growth and yield showed that harvest was impossible in certain cultivation areas, such as Gangwon-do. Therefore, climate change scenarios related to the cultivation limits of different barley types need to be re-estimated by factoring in survey data on the growth and yield of crops within those cultivation areas.

• Journal of Animal Science and Technology
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• v.49 no.1
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• pp.137-146
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• 2007

This study was conducted to determine fertilizer nutrient and pollutant production of Holstein dairy cattle by estimating manure characteristics. The moisture content of feces was 83.9% and 95.1% for urine. The pH of feces and urine were in the ranges of 7.0～7.4 and 7.5～7.8, respectively. The average BOD5, COD, SS, T-N, T-P concentrations of the dairy feces were 18,294, 52,765, 102,889, 2,575, and 457mg/ℓ, respectively. Dairy urine showed lower levels of BOD5(5,455mg/ℓ), COD(8,089mg/ℓ), SS(593mg/ℓ), T-N(3,401mg/l), and T-P(13mg/ℓ) than feces. The total daily produced pollutant amounts of a dairy cow were 924.1g(Milking cow), 538.8g(Dry cow), 284.4g(Heifer) of BOD5, 2,336.5g (Milking cow), 1,651.8g(Dry cow), 734.1g(Heifer) of COD and 4,210.1g(Milking cow), 2,417.1g(Dry cow), 1,629.1g(Heifer) of SS and 194.8g(Milking cow), 96.4g(Dry cow), 58.3g(Heifer) of T-N and 24.0g(Milking cow), 10.2g(Dry cow), 6.1g(Heifer) of T-P. The calculated amount of pollutants produced by a 450kg dairy cow for one year were 181.3kg of BOD5, 492.5kg of COD, 899.9kg of SS, 36.0kg of T-N and 4.1kg of T-P. The total yearly estimated pollutant production from all head(497,261) of dairy cattle in Korea is 90,149 tons of BOD5, 244,890 tons of COD, 447,491 tons of SS, 17,898 tons of T-N and 2,008 tons of T-P. The fertilizer nutrient concentrations of dairy feces was 0.26% N, 0.1% P2O5 and 0.14% K2O. Urine was found to contain 0.34% N, 0.003% of P2O5 and 0.31% K2O. The total daily fertilizer nutrients produced by dairy cattle were 197.4g (Milking cow), 97.4g(Dry cow), and 57.9g(Heifer) of Nitrogen, 54.2g(Milking cow), 22.2g(Dry cow), and 14.2g(Heifer) of P2O5 and 110.8g(Milking cow), 80.4g (Dry cow), and 39.5g(Heifer) of K2O. The total yearly estimated fertilizer nutrient produced by a 450kg dairy animal is 36.2kg of N, 8.8kg of P2O5, 24.6kg of K2O. The estimated yearly fertilizer nutrient production from all dairy cattle in Korea is 18,000 tons of N, 4,397 tons of P2O5, 12,206 tons of K2O. Dairy manure contains useful trace minerals for crops, such as CaO and MgO, which are contained in similar levels to commercial compost being sold in the domestic market. Concentrations of harmful trace minerals, such as As, Cd, Hg, Pb, Cr, Cu, Ni, Zn, met the Korea compost standard regulations, with some of these minerals being in undetected amounts.