• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.117-130
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• 2005

In both deteministic user Optimal Traffic Assignment Model (UOTAM) and stochastic UOTAM, travel time, which is a major ccriterion for traffic loading over transportation network, is defined by the sum of link travel time and turn delay at intersections. In this assignment method, drivers actual route perception processes and choice behaviors, which can become main explanatory factors, are not sufficiently considered: therefore may result in biased traffic loading. Even though there have been some efforts in Stochastic UOTAM for reflecting drivers' route perception cost by assuming cumulative distribution function of link travel time, it has not been fundamental fruitions, but some trials based on the unreasonable assumptions of Probit model of truncated travel time distribution function and Logit model of independency of inter-link congestion. The critical reason why deterministic UOTAM have not been able to reflect route perception cost is that the route perception cost has each different value according to each origin, destination, and path connection the origin and destination. Therefore in order to find the optimum route between OD pair, route enumeration problem that all routes connecting an OD pair must be compared is encountered, and it is the critical reason causing computational failure because uncountable number of path may be enumerated as the scale of transportation network become bigger. The purpose of this study is to propose a method to enable UOTAM to reflect route perception cost without route enumeration between an O-D pair. For this purpose, this study defines a link as a least definition of path. Thus since each link can be treated as a path, in two links searching process of the link label based optimum path algorithm, the route enumeration between OD pair can be reduced the scale of finding optimum path to all links. The computational burden of this method is no more than link label based optimum path algorithm. Each different perception cost is embedded as a quantitative value generated by comparing the sub-path from the origin to the searching link and the searched link.

• Korean journal of applied entomology
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• v.57 no.4
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• pp.339-345
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• 2018

The sugar beet cyst nematode (SBCN), Heterodera schachtii first detected in Taebaek, Gangwon-do in 2011, is one of the major plant parasitic nematodes that cause economic damage to the Chinese cabbage in highland regions. In addition, the distribution of clover cyst nematode (CCN), H. trifolii was confirmed in the highland Chinese cabbage cultivated regions in 2017. In order to investigate the spread of cyst nematodes, this study has been conducted since 2013 in the highland Chinese cabbage cultivation area. In addition, in 2017, the Real-Time PCR technique with the species-specific primer was used to investigate those two cyst nematodes and the soybean cyst nematode (SCN), H. glycines which is known for its distribution in Korea, focusing on the main production regions of highland Chinese cabbage cultivation. The number of infected fields in the Chinese cabbage plantation in highland increased every year to confirm distribution in Taebaek, Samcheok, Jeongseon and Gangneung in 2017, and the cumulative number of infection fields reached 245 by 2017. Of the 41 possible cyst nematode samples for PCR analysis, 61% were CCN, only 9.8% of the SBCN and 29.3% of the SCN were identified. Therefore, some of the previously known SBCN or CCN discoveries are likely to have been infected with SCN. It is believed that the CCN needs to be controlled in the future as CCN have been found to be dominant species in the highland Chinese cabbage plantation regions.