• Title/Summary/Keyword: Gokseong landslide

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A Long-Runout Landslide Triggered by Extreme Rainfall in Gokseong, South Korea on 7 August 2020

  • Nam, Kounghoon;Wang, Fawu;Dai, Zili;Kim, Jongtae;Choo, Chang Oh;Jeong, Gyo-Cheol
    • The Journal of Engineering Geology
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    • v.32 no.4
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    • pp.571-583
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    • 2022
  • On 7 August 2020, a large-scale catastrophic landslide was triggered by extreme rainfall at Osan village, Gokseong County, South Jeolla Province, South Korea. The initiation mechanism of the Gokseong landslide was different from those typical landslides that occurred in South Korea. Despite the relatively low elevation and slope degree, the landslide had a long runout distance of about 640 m over a total vertical distance of 90 m. A detailed field investigation and chemical analysis were conducted to understand the possible mechanisms for the high-speed and long-runout behavior of the landslide. The terrain controlled the motion behavior of the landslide and the seepage was observed at the whole landslide body. The clay-rich soils covered on granite bedrock of the landslide deposition area from the rice paddy field to the landslide crown. The results of this study may provide basic data for further research on the mechanisms for landslide initiation and propagation.

Detection of Landslide-damaged Areas Using Sentinel-2 Image and ISODATA (Sentinel-2 영상과 자기조직화 분류기법을 활용한 산사태 피해지 탐지 - 2020년 곡성 산사태를 사례로 -)

  • KIM, Dae-Sun;LEE, Yang-Won
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.253-265
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    • 2020
  • As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

Numerical Simulations of Landslide Disaster based on UAV Photogrammetry at Gokseong Areas (무인 항공사진측량 정보를 기반으로 한 곡성지역 산사태 수치해석)

  • Choi, Jae Hee;Kim, Nam Gyun;Jun, Byong Hee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.26-26
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    • 2021
  • 본 연구에서는 2020년 산사태가 발생한 곡성지역을 대상으로 무인항공기 사진측량을 통하여 산사태 지역의 범위와 변위를 조사하고 이를 기반으로 산사태에 의한 피해범위를 LS-RAPID에서 분석하였다. LS-RAPID는 지진과 강우의 영향을 반영하는 산사태 시뮬레이션 모델이며, 산사태 운동시작여부를 평가하며 만일 발생 시 토사의 이동, 퇴적 범위, 토사층의 깊이를 예측할 수 있다. 산사태 시뮬레이션에서 중요한 변수 중의 하나는 지중의 활동층의 깊이와 분포이다. 재해현장에서 이런 자료를 신속하고 정량적으로 측정하기 위한 방법으로서 무인항공기를 이용한 측량을 실시하였다. 또한 산사태 토사의 이동과 퇴적을 검증하기 위한 자료도 획득하였다. 매개변수의 추정 시선행연구에서 제시된 값을 참고하여, 재해현장의 피해범위와 규모를 비교하여 매개변수를 추정하여 다른 연구사례에서 이용한 값들과 비교, 분석하였다. 또한, 시뮬레이션의 지형입력자료로서 무인항공기 사진 측량자료에서 생성된 DSM(Digital Surface Model)과 수지지도에서 생성한 DEM(Digital Elevation Model)을 적용한 경우, 시뮬레이션 결과에 영향을 비교, 분석하였다. 결과적으로 DEM보다 DSM을 적용하는 것이 퇴적범위가 크게 확대되지 않으며, 현장을 잘 반영한 결과가 얻어지는 것으로 평가되었다.

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Evaluation of Steep Slopes Adjacent to Multi-use Facilities in National Parks using GIS (GIS를 활용한 국립공원 다중이용시설 인접 급경사지 평가)

  • Lee, Dong Hyeok;Jun, Kye Won;Jung, Min Jin;Park, Jun Hyo
    • Journal of Korean Society of Disaster and Security
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    • v.14 no.4
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    • pp.29-36
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    • 2021
  • Recently, due to climate change, the slope is increasing, and the risk of steep slope disasters such as the occurrence of slope collapse in the east coast and Busan region in 2019 and the Gokseong landslide in 2020 is increasing. Particularly, most national parks are made up of mountainous areas, and the risk of disasters on steep slopes is increasing. As the ground of the national park is aging and the weathering and jointing of the bedrock are accelerating due to climate change, the slope collapse and rockfall are increasing, and the annual number of visitors is increasing, it is necessary to manage steep slopes adjacent to multi-use facilities with many users. In this study, dangerous steep slopes that affect multi-use facilities in national parks were analyzed using GIS and verified through field surveys. As a process for extracting steep slopes adjacent to multi-use facilities in national parks, the slope was made in DEM and slopes of 34 degrees or higher were extracted. The difference between the maximum and minimum heights of the extracted slopes was used to confirm that the slopes met the standard for steep slopes, and the analysis of the slope direction was used to confirm whether it had an effect on the multi-use facilities. After that, precision aerial images and field photos were analyzed to finally identify risks at 4 sites, and field surveys were conducted. As a result of the field survey, all 4 sites were found to be steep slopes, 3 were graded D and 1 was graded C, so it was confirmed that management was required as a risk of collapse. All steep slopes extracted through GIS were found to be dangerous, so it is judged that the extraction of steep slopes through GIS would be appropriate.