4.5 Article

Spatial model integration for shallow landslide susceptibility and its runout using a GIS-based approach in Yongin, Korea

期刊

GEOCARTO INTERNATIONAL
卷 32, 期 4, 页码 420-441

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2016.1155658

关键词

Evidential belief function (EBF); integrated landslide susceptibility; runout propagation

资金

  1. Public Welfare and Safety Research Program through the National Research Foundation of Korea (NRF)
  2. Ministry of Science, ICT, and Future Planning [2012M3A2A1050977]
  3. Smart Civil Infrastructure Research Program - Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government [13SCIPS04]
  4. Korea Agency for Infrastructure Technology Advancement (KAIA)
  5. Brain Korea 21 Plus (BK 21 Plus)
  6. National Research Foundation of Korea [2012M3A2A1050977] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Rainfall-triggered shallow landslide is very common in Korean mountains and the socioeconomic impact is much higher than in the past due to population pressure in hazardous zones. Present study is an attempt toward the development of a methodology for the integration of shallow landslide susceptibility zones and runout zones that could be reached by mobilized mass. Landslide occurrence areas in Yongin were determined based on the interpretation of aerial photographs and extensive field surveys. Nineteen landslide-related factors maps were collected and analysed in geographic information system environment. Among 109 identified landslides, about 85% randomly selected training landslide data from inventory map was used to generate an evidential belief function model and remaining 15% landslides were used to validate the shallow landslide susceptibility map. The resulting susceptibility map had a success rate of 89.2% and a predictive accuracy of 92.1%. A runout propagation from high susceptible area was obtained from the modified multiple-flow direction algorithm. A matrix was used to integrate the shallow landslide susceptibility classes and the runout probable zone. Thus, each pixel had a susceptibility class in relation to its failure probability and runout susceptibility class. The study of landslide potential and its propagation can be used to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.

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