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A Study on Building Extraction Within Flood and Landslide Prone Areas Utilizing Spatial Information of Buildings

건축물 공간정보를 이용한 침수·산사태 위험 건축물 도출 연구

  • Baek, Jeongyeop (Dept. of Civil & Environmental Engineering, Korea Advanced Institute of Science and Technology) ;
  • Noh, Jaechang (Dept. of Civil & Environmental Engineering, Korea Advanced Institute of Science and Technology) ;
  • Hyeon, Tae-Hwan (Architecture & Urban Research Institute) ;
  • Cho, Young-jin (Architecture & Urban Research Institute) ;
  • Lim, Lisa (Dept. of Civil & Environmental Engineering, Korea Advanced Institute of Science and Technology)
  • 백정엽 (한국과학기술원 건설및환경공학과) ;
  • 노재창 (한국과학기술원 건설및환경공학과) ;
  • 현태환 (건축공간연구원) ;
  • 조영진 (건축공간연구원) ;
  • 임리사 (한국과학기술원 건설및환경공학과)
  • Received : 2023.01.03
  • Accepted : 2023.05.25
  • Published : 2023.06.30

Abstract

The purpose of this study was to extract buildings located within flood and landslide hazard areas using spatial information of domestic buildings. By identifying the characteristics of buildings in disaster-prone regions, this research aims to contribute to the identification of buildings requiring urgent preparation. This study employed a combination of building ledger data and land characteristic information to generate building spatial data. Building properties were defined based on the number of basement floors and the years that elapsed since the use approval date of the buildings. The resulting building spatial data were then categorized into seven distinct clusters based on their properties. To analyze the differences, ANOVA and posthoc tests were conducted to examine the average variances in flood hours and landslide hazard rates among the seven clusters. Furthermore, this study identified the building properties located within flood and landslide hazard areas. By implementing the proposed method, central and local governments can more efficiently and effectively prevent accidents in buildings during disasters through proactive measures.

Keywords

References

  1. Jeon, S., & Jang, H. (2008). Estimation of vulnerable disaster areas to establish Busan U-city model. Journal of the Korean Society of Hazard Mitigation, 8(2), 65-73.
  2. Kim, B. (2014). A Study on improvement of the urban flooding disaster prevention system coped with climate change. Planning and Policy, 392(6), 150-151.
  3. Kim, K. (2017). Impact of sea level rise under climate change on river flood level in coastal area, Thesis, Inha University.
  4. Kim, K., & Yoon, S. (2016). Analysis distribution of natural disaster risk buildings in Busan, Journal of the Regional Association of Architectural Institute of Korea, 18(4), 131-138.
  5. Kim, M., & Kim, M. (2014). Strategies for establishing a flood disaster monitoring system through convergence of spatial information and flood information, Land Policy Brief, 1-6.
  6. Lee, J., & Lee, S. (2018). Development of urban flood risk maps for strengthening urban planning toward disaster prevention, Journal of Korea Society of Civil Engineers, 38(2), 203-213.
  7. Lee, J. (2017). Development of regional flood damage functions for public facilities based on disaster statistics and impact assessment of climate change, Ph.D. Dissertation, Inha University.
  8. Lee, S., & Jung, S. (2021). Establishing a potential disaster risk assessment system based on grid data, Crisisonomy, 17(1), 35-44.
  9. Park, J., Park, C., An, J., & Yoon, H. (2020). An assessment method for evaluating vulnerability to regional disasters and its application to disaster due to heavy rain, Journal of the Korean Society of Hazard Mitigation, 20(1), 151-161. https://doi.org/10.9798/KOSHAM.2020.20.1.151
  10. Park, M., Park, M., & Song, Y. (2011). Analysis of spatial distributed risk for regional disaster management: 1. Hanzrd and exposure, Journal of the Korean Society of Hazard Mitigation, 11(4), 189-199. https://doi.org/10.9798/KOSHAM.2011.11.4.189
  11. Yoo, H., Kim, S., Park, K., & Choi, W. (2005). Disaster risk assessment of urban areas by geospatial information system, Korea Spatial Information Society, 13(3), 41-52.
  12. You, H., Shin, J., & Lee, J. (2012). Comparison of spatial analysis techniques for estimating landslide risk, Korea Spatial Information Society, 149-150.