Journal of Forest and Environmental Science

  • 제39권4호
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  • Pages.213-224
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  • 2023
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  • 2288-9744(pISSN)
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  • 2288-9752(eISSN)
강원대학교 산림과학연구소 (Institute of Forest Science, kangwon National University)
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Investigating Regions Vulnerable to Recurring Landslide Damage Using Time Series-Based Susceptibility Analysis: Case Study for Jeolla Region, Republic of Korea

  • Ho Gul Kim (Department of Landscape Architecture and Urban Planning, Cheongju University)
  • 투고 : 2023.09.18
  • 심사 : 2023.11.17
  • 발행 : 2023.12.31
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초록

As abnormal weather events due to climate change continue to rise, landslide damage is also increasing. Given the substantial time and financial resources required for post-landslide recovery, it becomes imperative to formulate a proactive response plan. In this regard, landslide susceptibility analysis has emerged as a valuable tool for establishing preemptive measures against landslides. Accordingly, this study conducted an annual landslide susceptibility analysis using the history of landslides that occurred over many years in the Jeolla region, and analyzed areas with a high potential for landslides in the Jeolla region. The analysis employed an ensemble model that amalgamated 10 data-based models, aiming to mitigate uncertainties associated with a single-model approach. Furthermore, based on the cumulative data regarding landslide susceptible areas, this research identified regions vulnerable to recurring landslide damage in Jeolla region and proposed specific strategies for utilizing this information at various levels, including local government initiatives, adaptation plan development, and development approval processes. In particular, this study outlined approaches for local government utilization, the determination of adaptation plan types, and considerations for development permits. It is anticipated that this research will serve as a valuable opportunity to underscore the significance of information concerning regions vulnerable to recurring landslide damage.

키워드

과제정보

This work was supported by the research grant of "Research Institute of Industrial Sciences" at Cheongju University (2022. 3. 1.-2024. 2. 29.).

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