한국지구과학회지 (Journal of the Korean earth science society)

  • 제45권3호
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  • Pages.214-223
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  • 2024
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  • 1225-6692(pISSN)
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  • 2287-4518(eISSN)
한국지구과학회 (The Korean Earth Science Society)
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항공 초분광 원격탐사 실험 기반 선박 스펙트럼 분석 및 탐지

Spectrum Analysis and Detection of Ships Based on Aerial Hyperspectral Remote Sensing Experiments

  • 박재진 (선박해양플랜트연구소 해사안전.환경연구센터) ;
  • 박경애 (서울대학교 지구과학교육과) ;
  • 김태성 (선박해양플랜트연구소 해사안전.환경연구센터) ;
  • 이문진 (선박해양플랜트연구소 해사안전.환경연구센터)
  • Jae-Jin Park (Maritime Safety and Environmental Research Center, Korea Research Institute of Ships and Ocean Engineering) ;
  • Kyung-Ae Park (Department of Earth Science Education, Seoul National University) ;
  • Tae-Sung Kim (Maritime Safety and Environmental Research Center, Korea Research Institute of Ships and Ocean Engineering) ;
  • Moonjin Lee (Maritime Safety and Environmental Research Center, Korea Research Institute of Ships and Ocean Engineering)
  • 투고 : 2024.06.23
  • 심사 : 2024.06.28
  • 발행 : 2024.06.30
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초록

최근 해상 교통량 증가 및 연안 중심의 레저활동으로 인해 다양한 해양사고가 발생하고 있다. 그 중 선박사고는 인명 및 재산 피해를 유발할 뿐만 아니라 기름 및 위험·유해물질 유출을 동반한 해양 오염사고로 이어질 가능성이 크다. 따라서 해양사고 대비 및 대응을 위한 지속적인 선박 모니터링이 필요하다. 본 연구에서는 해상 선박 모니터링 체계 구축을 위한 초분광 원격탐사 기반의 항공 실험 수행 및 선박탐지 결과를 제시하였다. 한반도 서해 궁평항 인근 해역을 대상으로 초분광 항공관측을 수행하였으며, 사전에 다양한 선박 갑판에 대한 분광 라이브러리를 구축하였다. 탐지 방법으로는 spectral correlation similarity (SCS) 기법을 사용하였으며 초분광 영상과 선박 스펙트럼 사이의 공간 유사도 분포를 분석하였다. 그 결과 초분광 영상에 존재하는 총 15개의 선박을 탐지하였으며 최대 유사도에 기반한 선박 갑판의 색상도 분류하였다. 탐지 선박들은 고해상도 digital mapping camera (DMC) 영상과의 매칭을 통해 검증하였다. 본 연구는 해상 선박탐지를 위한 항공 초분광 센서 활용의 기초로서 향후 원격탐사 기반의 선박 모니터링 시스템에 주요 역할을 할 것으로 기대된다.

The recent increase in maritime traffic and coastal leisure activities has led to a rise in various marine accidents. These incidents not only result in damage to human life and property but also pose a significant risk of marine pollution involving oil and hazardous and noxious substances (HNS) spills. Therefore, effective ship monitoring is crucial for preparing and for responding to marine accidents. This study conducted an aerial experiment utilizing hyperspectral remote sensing to develop a maritime ship monitoring system. Hyperspectral aerial measurements were carried out around Gungpyeong Port in the western coastal region of the Korean Peninsula, and spectral libraries were constructed for various ship decks. The spectral correlation similarity (SCS) technique was employed for ship detection, analyzing the spatial similarity distribution between hyperspectral images and ship spectra. As a result, 15 ships were detected in the hyperspectral images. The color of each ship's deck was classified based on the highest spectral similarity. The detected ships were verified by matching them with high-resolution digital mapping camera (DMC) images. This foundational study on the application of aerial hyperspectral sensors for maritime ship detection demonstrates their potential role in future remote sensing-based ship monitoring systems.

키워드

과제정보

본 논문은 해양수산부 재원으로 선박해양플랜트연구소의 주요사업인 "초분광 원격탐사 기반 선박탐지 및 크기 추정 기술 개발"에 의해 수행되었습니다(PES5330). 또한 이 연구는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 일부 받아 수행되었습니다(No. RS-2023-00208935).

참고문헌

  1. Antao, P., Sun, S., Teixeira, A. P., and Soares, C. G., 2023, Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data. Reliability Engineering & System Safety, 234, 109166.
  2. Barnsley, M. J., Settle, J. J., Cutter, M. A., Lobb, D. R., and Teston, F., 2004, The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere. IEEE Transactions on Geoscience and Remote Sensing, 42(7), 1512-1520.
  3. Cheng, G., and Han, J., 2016, A survey on object detection in optical remote sensing images. ISPRS journal of photogrammetry and remote sensing, 117, 11-28.
  4. Folkman, M. A., Pearlman, J., Liao, L. B., and Jarecke, P. J., 2001, EO-1/Hyperion hyperspectral imager design, development, characterization, and calibration. Hyperspectral Remote Sensing of the Land and Atmosphere, 4151, 40-51.
  5. Galal, A., Hassan, H., and Imam, I. F., 2012. A novel approach for measuring hyperspectral similarity. Applied Soft Computing, 12(10), 3115-3123.
  6. Ghiyamat, A., Shafri, H. Z. M., Mahdiraji, G. A., Shariff, A. R. M., and Mansor, S., 2013, Hyperspectral discrimination of tree species with different classifications using single-and multiple-endmember. International Journal of Applied Earth Observation and Geoinformation, 23, 177-191.
  7. Kanjir, U., Greidanus, H., and Ostir, K., 2018. Vessel detection and classification from spaceborne optical images: A literature survey. Remote sensing of environment, 207, 1-26.
  8. Kim, T. S., Park, K. A., Li, X., Lee, M., Hong, S., Lyu, S. J., and Nam, S., 2015, Detection of the Hebei Spirit oil spill on SAR imagery and its temporal evolution in a coastal region of the Yellow Sea. Advances in Space Research, 56(6), 1079-1093.
  9. Kim, Y., Lee, S., Kim, J., and Park Y., 2017, Disaster management using high resolution optical satellite imagery and case analysis. Journal of the Korean Society of Hazard Mitigation, 17(3), 117-124.
  10. Kumar, A. S., Keerthi, V., Manjunath, A. S., Van der Werff, H., and Van der Meer, F., 2010, Hyperspectral image classification by a variable interval spectral average and spectral curve matching combined algorithm. International Journal of Applied Earth Observation and Geoinformation, 12(4), 261-269.
  11. Lee, M. S., Park, K. A., Lee, H. R., Park, J. J., Kang, C. K., and Lee, M., 2016, Detection and dispersion of thick and film-like oil spills in a coastal bay using satellite optical images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(11), 5139-5150.
  12. Lee, S., and Park, Y. K., 2013, The Legal Assessment of the Illegal Fishing Activities of Chinese Fishing Vessels: A Focus on Detention of Foreign Vessels. The Korean Journal of International and Comparative Law, 1(1), 31-48.
  13. Park, J. J., Kim, T. S., Park, K. A., Oh, S., Lee, M., and Foucher, P. Y., 2020, Application of spectral mixture analysis to vessel monitoring using airborne hyperspectral data. Remote Sensing, 12(18), 2968.
  14. Park, J. J., Oh, S., Park, K. A., Lee, M. S., Jang, J. C., and Lee, M., 2018, A methodology of ship detection using high-resolution satellite optical image. Journal of the Korean earth science society, 39(3), 241-249.
  15. Park, J. J., Park, K. A., Foucher, P. Y., Lee, M., and Oh, S., 2020, Estimation of ship size from satellite optical image using elliptic characteristics of ship periphery. International Journal of Remote Sensing, 41(15), 5905-5927.
  16. Qian, S. E., 2021, Hyperspectral satellites, evolution, and development history. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 7032-7056.
  17. Remer, L. A., Davis, A. B., Mattoo, S., Levy, R. C., Kalashnikova, O. V., Coddington, O., and Zhai, P. W., 2019, Retrieving aerosol characteristics from the PACE mission, Part 1: Ocean Color Instrument. Frontiers in Earth Science, 7, 152.
  18. Seo, D., Oh, S., and Lee, D., 2022, Classification and Identification of Spectral Pixels with Low Maritime Occupancy Using Unsupervised Machine Learning. Remote Sensing, 14(8), 1828.
  19. Shi, Z., Yu, X., Jiang, Z., and Li, B., 2013, Ship detection in high-resolution optical imagery based on anomaly detector and local shape feature. IEEE Transactions on Geoscience and Remote Sensing, 52(8), 4511-4523.
  20. Tang, J., Deng, C., Huang, G. B., and Zhao, B., 2014, Compressed-domain ship detection on spaceborne optical image using deep neural network and extreme learning machine. IEEE transactions on geoscience and remote sensing, 53(3), 1174-1185.
  21. Thenkabail, P., GangadharaRao, P., Biggs, T., Krishna, M., and Turral, H., 2007, Spectral matching techniques to determine historical land-use/land-cover (LULC) and irrigated areas using time-series 0.1-degree AVHRR pathfinder datasets. Photogrammetric Engineering and Remote Sensing, 73(10), 1029-1040.
  22. Van der Meer, F., 2006, The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery. International journal of applied earth observation and geoinformation, 8(1), 3-17.
  23. Vane, G., Green, R. O., Chrien, T. G., Enmark, H. T., Hansen, E. G., and Porter, W. M., 1993, The airborne visible/infrared imaging spectrometer (AVIRIS). Remote sensing of environment, 44(2-3), 127-143.
  24. Yang, F., Xu, Q., and Li, B., 2017, Ship detection from optical satellite images based on saliency segmentation and structure-LBP feature. IEEE geoscience and remote sensing letters, 14(5), 602-606.
  25. Yang, G., Li, B., Ji, S., Gao, F., and Xu, Q., 2013, Ship detection from optical satellite images based on sea surface analysis. IEEE Geoscience and Remote Sensing Letters, 11(3), 641-645.
  26. You J. S. and Chung, Y. J., 2015, Study on the Ship Fire Analysis According the Explosion Hazard. Korean Institute of Fire Science and Engineering, 29(1), 80-86.
  27. Zhu, C., Zhou, H., Wang, R., and Guo, J., 2010, A novel hierarchical method of ship detection from spaceborne optical image based on shape and texture features. IEEE Transactions on geoscience and remote sensing, 48(9), 3446-3456.
  28. Zou, Z. and Shi, Z., 2016, Ship detection in spaceborne optical image with SVD networks. IEEE transactions on geoscience and remote sensing, 54(10), 5832-5845.