Finding unrevealed landslide hazard area induced by climate change and topography - Case study for Inje-gun, Gangwon-do, ROK -

Ho Gul Kim, Chan Park, Mingyun Cho

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Recently, as extreme weather phenomena increase due to climate change, various damages have occurred in cities. It is necessary to create a city that is resilient to respond to various threats in the future. In particular, in cities that include mountainous areas, human lives and infrastructure are damaged by landslides. However, studies that clearly analyze the hazard areas of landslides in areas adjacent to forests within cities are insufficient, and studies on predicting future hazard areas taking into account climate change are insufficient. Therefore, this study intends to more clearly predict future landslide hazard areas by combining a statistical model and a runout model. As a result of the study, it was possible to more clearly define landslide hazard areas in areas adjacent to the forest than when the statistical model was applied. In addition, it was possible to predict future landslide hazard areas, which are difficult to predict using only the runout model. The distribution of the future landslide hazard areas was different according to the scenario, but the overall hazard area was predicted to increase. In particular, the area of landslide hazard areas in urban areas adjacent to forests is predicted to increase significantly compared to the past. It was found that the landslide hazard area of ​​the city mainly has footslope topography connecting the inside and outside of the forest. This study is expected to support decision-making in establishing landslide adaptation measures in urban areas adjacent to forests.

Original languageEnglish
Article number103180
JournalSustainable Cities and Society
Volume75
DOIs
StatePublished - Dec 2021

Keywords

  • Complementary model
  • Landslide hazard
  • Landslide susceptibility
  • Runout model
  • Statistical model

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