게재연도 | 2022 |
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논문집명 | Scientific Reports |
논문명 | Dynamic landslide susceptibility analysis that combines rainfall period, rainfall, and geospatial information |
저자 | Jae-Joon Lee, Moon-Soo Song, Hong-Sic Yun, Sang-Guk Yum |
구분 | 국외저널 |
요약 | Worldwide, catastrophic landslides are occurring as a result of abnormal climatic conditions. Since
a landslide is caused by a combination of the triggers of rainfall and the vulnerability of spatial
information, a study that can suggest a method to analyze the complex relationship between the
two factors is required. In this study, the relationship between complex factors (rainfall period,
accumulated rainfall, and spatial information characteristics) was designed as a system dynamics
model as variables to check the possibility of occurrence of vulnerable areas according to the rainfall
characteristics that change in real-time. In contrast to the current way of predicting the collapse
time by analysing rainfall data, the developed model can set the precipitation period during rainfall.
By setting the induced rainfall period, the researcher can then assess the susceptibility of the
landslide-vulnerable area. Further, because the geospatial information features and rainfall data for
the 672 h before the landslide’s occurrence were combined, the results of the susceptibility analysis
could be determined for each topographical characteristic according to the rainfall period and
cumulative rainfall change. Third, by adjusting the General cumulative rainfall period (DG) and Interevent time defnition (IETD), the preceding rainfall period can be adjusted, and desired results can be
obtained. An analysis method that can solve complex relationships can contribute to the prediction of
landslide warning times and expected occurrence locations |
핵심어 |