• 제목/요약/키워드: Woomyeon Mountain

검색결과 3건 처리시간 0.014초

도시경관관리를 위한 조망점 및 선호특성 분석 - 우면산 조망관리대상지역을 중심으로 - (An Analysis on Viewpoint and Characteristics of Preference for Urban Landscape Management - Based on the Site of View Management in woomyeon Mountain -)

  • 송병화;양병이;이경진
    • KIEAE Journal
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    • 제7권5호
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    • pp.107-114
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    • 2007
  • This study purposed to review the alternative criteria for preserving urban scenic view and establishing its management methods by selecting preliminary viewpoints to preserve the views of woomyeon mountain. The contents of this research consists of the representative urban scenic view by analyzing its viewpoints and landscape preference. For this study, seventeen preliminary viewpoints were selected, the ratio of visual structure was calculated by types of landscapes and an analysis was conducted on landscape preference through a questionnaire survey to draw results. Conclusively, various side studies through statistical method for characteristic analysis with preference elements about viewpoint and visual structure for urban landscape management. This research will contribute to management on objective point of view in environmentally friendly urban landscape planning.

GIS를 이용한 우면산 토석류 지형인자 분석 (Analysis of Topographical Factors in Woomyun Mountain Debris Flow Using GIS)

  • 이한나;김기홍
    • 한국산업융합학회 논문집
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    • 제23권5호
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    • pp.809-815
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    • 2020
  • A number of investigations and studies have been conducted in various fields regarding the sediment disasters of Mt. Woomyeon that occurred in July 2011. We collected and compared the topographic information of the general points where debris flows did not occur and the collapse points where the debris flow occurred in order to find out the characteristics of the collapse points in Woomyeon mountain. The collected topographic information is altitude, curvature, slope, aspect and TPI(topographic position index). As a result of comparison, there were relatively many collapse points at an altitude of 210m to 250m, and at a slope of 30° to 40°. In addition, the risk of collapse was low in a cell where the curvature was close to 0, and the risk was higher in concave terrain than in convex terrain. In the case of TPI, there was no statistical difference between the general points and the collapse points when the analysis radius was larger than 200m, and there was a correlation with the curvature when the analysis radius was smaller than 50m. In the case of debris flows that are affected by artificial structures or facilities, there is a possibility of disturbing the topographic analysis results. Therefore, if a research on debris flow is conducted on a mountain area that is heavily exposed to human activities, such as Woomyeon mountain, diversified factors must be considered to account for this impact.

A Comparative Assessment of the Efficacy of Frequency Ratio, Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy in Landslide Susceptibility Mapping

  • Park, Soyoung;Kim, Jinsoo
    • 대한원격탐사학회지
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    • 제36권1호
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    • pp.67-81
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    • 2020
  • The rapid climatic changes being caused by global warming are resulting in abnormal weather conditions worldwide, which in some regions have increased the frequency of landslides. This study was aimed to analyze and compare the landslide susceptibility using the Frequency Ratio (FR), Statistical Index, Weight of Evidence, Certainty Factor, and Index of Entropy (IoE) at Woomyeon Mountain in South Korea. Through the construction of a landslide inventory map, 164 landslide locations in total were found, of which 50 (30%) were reserved to validate the model after 114 (70%) had been chosen at random for model training. The sixteen landslide conditioning factors related to topography, hydrology, pedology, and forestry factors were considered. The results were evaluated and compared using relative operating characteristic curve and the statistical indexes. From the analysis, it was shown that the FR and IoE models were better than the other models. The FR model, with a prediction rate of 0.805, performed slightly better than the IoE model with a prediction rate of 0.798. These models had the same sensitivity values of 0.940. The IoE model gave a specific value of 0.329 and an accuracy value of 0.710, which outperforms the FR model which gave 0.276 and 0.680, respectively, to predict the spatial landslide in the study area. The generated landslide susceptibility maps can be useful for disaster and land use planning.