• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.101-104
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• 2006

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that can explain ElNINO effect to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpola. Front (SPF) dividing into the north and south part of the East sea, the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF,SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong '-' value, where KF had strong '+' value. The time of '+' and '-' value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking '+' value which time was March and October That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.397-402
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• 2005

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that tan explain EININO effort to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpolar Front (SPF) dividing into the north and south part of the East sea , the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF, SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong'-'value, where KF had strong'+'value. The time of'+'and'-'value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking'+'value which time was March and October. That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.41-54
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• 2021

This study targets the urban park corresponding to the core areas (Hubs) of Green Infrastructure and estimates their value utilizing the Contingent Valuation Method (CVM) and determines the planning factors which affect them. The research aims to provide basic data for supporting the value improvement in the planning stage for urban parks representing green infrastructure. The primary purpose of this research is to derive variables that affect economic value and planning factors to improve the use-value of urban parks, one of the Hubs of the green infrastructure. In this study, Sejong Lake Park, located in Sejong City, is the target site. This study collected the responses of 105 people by conducting a survey on the intention to pay for the use-value and the planning factors that affect it, targeting visitors to Sejong Lake Park. The study conducts Contingent Valuation Method (CVM) on this survey responses. The results are as follows: first, as a result of analyzing the variables which affect willingness to pay for use-value, residence and age influence the willingness to pay significantly among socioeconomic characteristics. Next, the survey responses of Double-bounded dichotomous choices (DB-DC) CVM are converted into variables through statistic techniques. Furthermore, the variables are used for a Logit model to draw coefficients. The average willingness to pay per person for the use-value of Sejong Lake Park using the derived coefficients was approximately found to be 8,597 won. Therefore, as of 2019, Sejong Lake Park, with a total of 430,000 visitors, is estimated to have an annual economic value of 3.7 billion won. Third, the average Likert scale of the planning factor affecting the decision to pay for the economic value of Sejong Lake Park was the highest along the waterfront landscape, and the convenience facilities and waterfront landscape showed the highest willingness to pay, 10,000 won. In the range between 2,500 won and 5,000 won, the waterfront area ranks highest. Therefore, it can be said that visitors to Sejong Lake Park take account of the economic value of using the waterfront landscape the most. This study is meaningful as a thesis on use-value and the planning factors that affected value evaluation results of urban parks, and the analysis of the correlation between the planning factors of urban parks as hubs located in urban areas.