Economic and Environmental Geology (자원환경지질)

The Korean Society of Economic and Environmental Geology (대한자원환경지질학회)
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Monitoring of the Suspended Sediments Concentration in Gyeonggi-bay Using COMS/GOCI and Landsat ETM+ Images

COMS/GOCI 및 Landsat ETM+ 영상을 활용한 경기만 지역의 부유퇴적물 농 도 변화 모니터링

  • Eom, Jinah (Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology) ;
  • Lee, Yoon-Kyung (Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology) ;
  • Choi, Jong-Kuk (Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology) ;
  • Moon, Jeong-Eon (Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology) ;
  • Ryu, Joo-Hyung (Korea Ocean Satellite Center, Korea Institute of Ocean Science & Technology) ;
  • Won, Joong-Sun (Department of Earth System Science, Yonsei University)
  • 엄진아 (한국해양과학기술원 해양위성센터) ;
  • 이윤경 (한국해양과학기술원 해양위성센터) ;
  • 최종국 (한국해양과학기술원 해양위성센터) ;
  • 문정언 (한국해양과학기술원 해양위성센터) ;
  • 유주형 (한국해양과학기술원 해양위성센터) ;
  • 원중선 (연세대학교 지구시스템과학과)
  • Received : 2013.10.10
  • Accepted : 2013.12.30
  • Published : 2014.02.28
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Abstract

In coastal region, estuaries have complex environments where dissolved and particulate matters are mixed with marine water and substances. Suspended sediment (SS) dynamics in coastal water, in particular, plays a major role in erosion/deposition processes, biomass primary production and the transport of nutrients, micropollutants, heavy metals, etc. Temporal variation in suspended sediment concentration (SSC) can be used to explain erosion/sedimentation patterns within coastal zones. Remotely sensed data can be an efficient tool for mapping SS in coastal waters. In this study, we analyzed the variation in SSC in coastal water using the Geostationary Ocean Color Imager (GOCI) and Landsat Enhanced Thematic Mapper Plus (ETM+) in Gyeonggi-bay. Daily variations in GOCI-derived SSC showed low values during ebb time. Current velocity and water level at 9 and 10 am is 37.6, 28.65 $cm{\cdot}s^{-1}$ and -1.23, -0.61 m respectively. Water level has increased to 1.18 m at flood time. In other words, strong current velocity and increased water level affected high SSC value before flood time but SSC decreased after flood time. Also, we compared seasonal SSC with the river discharge from the Han River and the Imjin River. In summer season, river discharge showed high amount, when SSC had high value near the inland. At this time SSC in open sea had low value. In contrast, river discharge amount from inland showed low value in winter season and, consequently, SSC in the open sea had high value because of northwest monsoon.

연안환경은 해수의 유기물질 및 미립자들과 육상의 입자들이 섞여있는 매우 복잡한 환경을 가진다. 특히 연안에서의 부유퇴적물 (suspended sediment, SS) 이동은 침식 및 퇴적 과정, 기초 생물량, 영양분의 이동, 미세 오염 등에 중요한 역할을 한다. 따라서 이 연구에서는 천리안 해양관측 위성 (Geostationary Ocean Color Imager, GOCI) 및 Landsat Enhanced Thematic Mapper Plus (ETM+) 영상을 활용하여 경기만 지역에서의 부유퇴적물 농도 변화를 관측하였다. GOCI 영상을 활용하여 부유퇴적물 농도의 일변화를 관측한 결과 만조 이후에 부유퇴적물 농도가 낮게 나타났다. 부유퇴적물 농도와 유속 및 수위 자료와의 비교 결과, 만조 이전의 9시와 10시의 유속 세기는 각각 37.6, 28.65 $cm{\cdot}s^{-1}$이며, 수위는 각각 -1.23, -0.61 m이지만 만조 때 수위는 1.18 m로 점차 높아진다. 즉 수위 상승과 유속이 강하게 나타나면서 만조 이전에 높은 부유퇴적물 농도를 가지는 반면에 만조 이후에는 지속적으로 부유퇴적물 농도가 감소한다. 또한 Landsat ETM+ 영상으로부터 계절별 부유퇴적물 농도를 분석한 결과 겨울에 외해에서 높은 부유퇴적물 농도 값을 가지며 여름에는 한강 연안에서 높은 부유퇴적물 농도 값을 가진다. 이러한 이유는 겨울에는 북서계절풍의 영향으로 외해 부근에서 부유퇴적물 농도가 높게 나타났으며 여름에는 풍속보다는 유량의 영향이 크기 때문에 한강 연안에서 높은 부유퇴적물 농도 값을 가지는 것으로 판단된다.

Keywords

References

  1. Aronoff, S. (2005) Remote Sensing for GIS Managers. ESRI Press, Redlands, CA.
  2. Chavez, P.S. (1996) Image-based atmospheric corrections revisited and improved. American Society for Photogrammetry and Remote Sensing, v.62, p.1025-1036.
  3. Cho, S., Ahn, Y.H., Ryu, J.H, Kang, G.S. and Youn, H.S. (2010) Development of Geostationary Ocean Color Imager (GOCI), Korean J. Remote Sens., v.26(2), p.157-165. https://doi.org/10.7780/kjrs.2010.26.2.157
  4. Choi, J.K., Park, Y.J., Ahn, J.H., Lim, H.S., Eom, J. and Ryu, J.H. (2012) GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity, J. Geophys. Res., v.117, p.C09004.
  5. Choi, J.K., Park, Y.J., Lee, B.R., Eom, J., Moon J.E. and Ryu, J.H. (2014) Application of the Geostationary Ocean Color Imager (GOCI) to understanding the temporal dynamics of coastal water turbidity, Remote Sens. Environ. (in press).
  6. Choi, J.Y., Kwon,, Y.K. and Chung, G.S. (2012) Late Quaternary Stratigraphy and Depositional Environment of Tidal Sand Ridge Deposits in Gyeonggi Bay, West Coast of Korea, Jour. Korean Earth Science Society, v.33(1), p.1-10. https://doi.org/10.5467/JKESS.2012.33.1.1
  7. Doxaran, D., Castaing, P. and Lavender, S.J. (2006) Monitoring the maximum turbidity zone and detecting fine-scale turbidity features in the Gironde estuary using high spatial resolution satellite sensor (SPOT HRV, Landsat ETM+) data, Int. J. Remote Sens., v.27(11), p.2303-2321. https://doi.org/10.1080/01431160500396865
  8. Doxaran, D., Froidefond, J.M., Castaing, P. and Babin, M. (2009) Dynamics of the turbidity maximum zone in a macrotidal estuary (the Gironde, France): Observations from field and MODIS satellite data, Est. Coast. Shelf Sci., v.81, p.321-332. https://doi.org/10.1016/j.ecss.2008.11.013
  9. Doxaran, D., Froidefond, J.M., Lavender, S. and Castaing, P. (2002) Spectral signature of highly turbid waters Application with SPOT data to quantify suspended particulate matter concentrations, Remote Sens. Environ., v.81, p.149-161. https://doi.org/10.1016/S0034-4257(01)00341-8
  10. Jensen, J.R. (2005) Introductory digital image processing a remote sensing perspective (second edition), Prentice hall, New jersey, p.2-61.
  11. Korean Ocean Research & Development Institute (1998) Tidal Flat Studies for Conservation and Sustainable Use.
  12. Lee, B., Ahn, J.H., Park, Y.J. and Kim, S.W. (2013) Turbid water atmospheric correction for GOCI: Modification of MUMM algorithm, Korean J. Remote Sens., v.29(2), p.173-182. https://doi.org/10.7780/kjrs.2013.29.2.2
  13. Lee, M.S., Park, K.Y., Chung, J.Y., Ahn, Y.H. and Moon, J.E. (2011) Estimation of coastal suspended sediment concentration using satellite data and oceanic in-situ measurements, Korean J. Remote Sens., v.27(6), p.677-692. https://doi.org/10.7780/kjrs.2011.27.6.677
  14. Lorthiois, T., Doxaran, D. and Chami, M. (2012) Daily and seasonal dynamics of suspended particles in the Thone River plume based on remote sensing and field optical measurements, Geo-Mar. Lett., v.32(2), p.89-101.
  15. Mobley, C.D. (1999) Estimation of the remote-sensing reflectance from above-surface measurements, Appl. Opt., v.38(36), p.7442-7455. https://doi.org/10.1364/AO.38.007442
  16. Moon, J.E., Park, Y.J., Ryu, J.H., Choi, J.K., Ahn, J.H., Min, J.E., Son, Y.B., Lee, S.J., Han, H.J. and Ahn, Y.H. (2012) Initial validation of GOCI water products against in situ data collected around Korean Peninsula for 2010-2011, Ocean Sci., v.47(3), p.261-277. https://doi.org/10.1007/s12601-012-0027-1
  17. Paphitis, D. and Collins, M.B. (2005) Sediment resuspension envents within the (microtidal) coastal waters of Thermaikos Gulf, morthern Greece, Cont. Shelf Res., v.25, p.2350-2365. https://doi.org/10.1016/j.csr.2005.08.028
  18. Petus, C., Chust, G., Gohin, F., Doxaran, D., Froidefond, J.M. and Sagarminaga, Y. (2010) Estimating turbidity and total suspended matter in the Adour River plume (south bay of Biscay) using MODIS-250m imagery, Cont. Shelf Res., v.30, p.379-392. https://doi.org/10.1016/j.csr.2009.12.007
  19. Ruddick, K., Nechad, B., Neukermans, G., Park, Y. J., Doxara, D., Sirjacobs, D. and Beckers, J.M. (2008) Remote sensing of suspended particulate matter in turbid waters: state of the art and future perspectives, Proceedings of the Ocean Optics XIX conference, Barga, 6-10 October, 2008.
  20. Ruddick, K.G., De Cauwer, V., Park, Y.J. and Moore, G. (2006) Seaborne measurements of near infrared water-leaving reflectance: The similarity spectrum for turbid waters, Limnol Oceanogra, v.51(2), p.1167-1179. https://doi.org/10.4319/lo.2006.51.2.1167
  21. Ryu, J.H., Han, H.J., Cho. S., Park, Y.J. and Ahn, Y.H. (2012) Overview of Geostationary Ocean Color Imager (GOCI) and GOCI Data Processing System( GDPS), Ocean Sci., v.47(3), p.223-233. https://doi.org/10.1007/s12601-012-0024-4
  22. Suk, B.C. (1989) Sedimentology and history of sea level changes in the East China Sea and adjacent seas, Sedimentary facies in the active plate margin, p.215-231.
  23. Wang, M. and Shi, W. (2006) Cloud Masking for Ocean Color Data Processing in the Coastal Regions, IEEE Trans. Geosci. Remote Sens., v.44(11), p.3196-3205. https://doi.org/10.1109/TGRS.2006.876293
  24. Wilkie, D.S. and Finn, J.T. (1996) Remote Sensing Imagery for Natural Resources Monitoring: A Guide for First Time Users, Columbia University Press, New York.
  25. Zibordi, G., Holben, B., Slutsker, I., Giles D., D'Almonte, D., Melin, F., Berthon, J.-F., Vandemark, D., Feng, H., Schuster, G. Fabbri, B.E., Kaitala, S. and Seppala, J. (2009) AERONET-OC: A network for the validation of ocean color primary products, J. Atmos. Oceanic, v.26(8), p.1634-1651. https://doi.org/10.1175/2009JTECHO654.1