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Sentinel-1 영상을 이용한 북한 댐 위치도 구축

Establishment of North Korean Dam Location Map using Sentinel-1 Images

  • 김주훈 (한국건설기술연구원 수자원하천연구본부) ;
  • 김동필 (한국건설기술연구원 수자원하천연구본부) ;
  • 조용수 (충남도립대학교 건설안전방재학과)
  • Joo-Hun Kim (Dept. of Hydro Science and Engineering Research, Korea Institute of Civil engineering and building Technology (KICT)) ;
  • Dong-Phil Kim (Dept. of Hydro Science and Engineering Research, Korea Institute of Civil engineering and building Technology (KICT)) ;
  • Yong-Soo Cho (Dept. of Construction Safety & Disaster Prevention, Chungnam State University)
  • 투고 : 2025.04.18
  • 심사 : 2025.06.17
  • 발행 : 2025.06.30

초록

북한 댐에 대한 정보는 NASA, FAO, ICOLD 등에서 제공하고 있는 글로벌 정보에서 확인이 가능하다. 그러나 대부분의 댐 정보가 1980년대 이전의 댐 정보로서 정보의 시의성이 부족하다. 북한은 2010년대 이후 약 30여 곳에 댐을 건설한 것으로 확인되고 있다. 본 연구에서는 Sentinel-1 위성영상 분석을 통해 북한의 댐 위치도를 구축하는 것을 목적으로 하였다. Sentinel-1 영상분석을 통해 수체면적을 추출하였고 Google Earth와의 중첩을 통해 댐의 위치정보를 구축하였다. 북한 댐 523곳의 위치정보를 구축하였고, 이 중에서 댐 배후면 수체면적이 1.0km2 이상인 곳이 110곳으로 분석되었다. 본 연구에서 구축한 댐 정보는 위치정보만을 포함하고 있어 향후 댐명, 댐 제원 등에 대한 속성정보의 구축은 추가로 필요하다.

Information on North Korean dams can be found in global information provided by NASA, FAO, and ICOLD. However, most of the dam information is before the 1980s and the timeliness of the information is insufficient. It has been confirmed that North Korea has built dams in about 30 places since the 2010s. In this study, the purpose of constructing a map of the location of a dam in North Korea through Sentinel-1 satellite image analysis. The water surface area was extracted through Sentinel-1 image analysis and the location information of the dam was constructed through overlapping with Google Earth. Location information of 523 North Korea dams was established, of which 110 had a water surface area of 1.0 km2 or more behind the dam. Since the dam information constructed in this study includes only location information, it is necessary to establish additional attribute information on the dam name and dam specifications in the future.

키워드

과제정보

본 연구는 2025년도 한국건설기술연구원 주요사업인 "물관리 현안 및 이슈 대응을 위한 기반 구축 연구" 과제의 연구비 지원에 의해 수행되었습니다.

참고문헌

  1. Ahn, J.H. and Y.N. Yoon. 2010. Water resources situation and water supply outlook in North Korea(1). Water for Future 43(4):17-26 (안재현, 윤용남. 2010. 북한 수자원 현황과 용수수급 전망(1)-북한 하천유역의 수문학적 특성과 용수이용 현황. 물과 미래 43(4):17-26).
  2. ASCE. 2009. Guiding Principles for the Nation's Critical Infrastructure.
  3. Copernicus Climate Change Service (C3S). https://dataspace.copernicus.eu(Accessed : August. 20. 2024).
  4. Jing, M., L. Cheng, J. Chen, J. Mao, N. Li, Z.X. Duan, Z.M. Li and M.C. Li. 2021. Detecting unknown dams from high-resolution remote sensing images: A deep learning and spatial analysis approach. International Journal of Applied Earth Observation and Geoinformation Volume 104, 102576.
  5. Jing, Y., Y. Ren, Y. Liu, D. Wang and L. Yu. 2022. Dam Extraction from High-Resolution Satellite Images Combined with Location Based on Deep Transfer Learning and Post Segmentation with an Improved MBI. Remote Sens. 2022, 14(16), 4049; https://doi.org/10.3390/rs14164049.
  6. Jang, W.J., Y.G. Lee and S.J. Kim. 2020. A A feasibility modeling of potential dam site for hydroelectricity based on ASTGTM DEM data. J. Korea Water Resur. Assoc. J 53(7):545-555 (장원진, 이용관, 김성준. 2020. ASTGTM 전지구 DEM 기반의 수력발전댐 적지분석 사전모델링. 한국수자원학회논문집 53(7):545-555).
  7. King's College London https://www.policysupport.org/waterworld (Accessed : August. 1. 2023).
  8. Kim, J.H. and H.S. Noh. 2023. "Analysis of water surface change in reservoir using SAR Images." 2023 Korea Water Resource Association Conference. P3-53 (김주훈, 노희성. 2023. SAR영상을 이용한 저수지 수표면 변화 분석, 2023한국수자원학회 학술대회).
  9. Kim, J.H. and D.H. Kim. 2024. Analysis of water surface area chang in reservoir using satellite images KSCE 44(5):629- 636 (김주훈, 김동필. 2024. 위성영상을 이용한 저수지 수체면적 변화 분석. 대한토목학회 논문집 44(5):629-636).
  10. Kwon, J.H. 2022. 10 Years of Kim Jong-un's Administration, Major Target Construction Trends. Korea Institute for National Unification. 2022 North Korean Urban Forum (권주현. 2022. 김정은 집권 10년, 주요 대상건설 동향. 통일연구원 2022 북한도시포럼 발표집).
  11. Manavalan, R. 2017. SAR image analysis techniques for flood area mapping literature survey. Earth Science Informatics, 10(1): 1-14. https://doi.org/10.1007/s12145-016-0274-2
  12. Mason, D.C., I.J. Davenport, J. Neal, G. Schumann and P. Bates. 2012. Near real-time flood detection in urban and rural areas using high resolution synthetic aperture radar images. IEEE transactions on Geoscience and Remote Sensing 50(8), 3041-3052. https://doi.org/10.1109/TGRS.2011.2178030
  13. Ministry of Unification https://nkinfo.unikorea.go.kr/nkp/main/portalMain.do (Accessed : August. 20. 2024).
  14. Oh, S.H. and S.W. Nam. 2021. Improvement Plan on North Korea's Water Management System and Inter-Korean Water Resource Cooperation. National Assembly Research Service. LEGISLATION AND POLICY STUDIES 13(2):059-092 (오승환, 남성욱. 2021. 북한의 물관리 체계와 남북 수자원 협력 활성화 방안 연구. 국회입법조사처 입법과 정책 13(2):059-092) https:// doi.org/10.22809/nars.2021.13.2.003.
  15. Oosterhof, C., N. Gasnier, S. P. Luque and Y. Tanguy. 2023. Extractiom of small dam reservoirs using a combination of digital terrain model and water mask derived from satellite images. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium.
  16. SPN Seoul-Pyeongyang News. https://www.spnews.co.kr/ (Accessed : August. 20. 2024).
  17. Wang, K. and J. C. Trinder. 2014. Applied Watershed Segmentation Algorithm for Water Body Extraction in Airborne SAR Image. In EUSAR 2014; 10th European Conference on Synthetic Aperture Radar, 1-4.
  18. Wang, X., X. Xiao, Y. Qin, J. Dong, J. Wu and B. Li. 2022. Improved maps of surface water bodies, large dams, reservoirs, and lakes in China. ESSD 14(8):3757-3771 https://doi.org/10.5194/essd-14-3757-2022.