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Analysis of Flow Regime in the Turbidity Maximum Zone of Yangtze Estuary Based on Texture Features of Tiangong-2 Remote Sensing Images

  • Lizhi Teng
  • Heqin Cheng
  • Yuanying Qiao
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 541)

Abstract

Two regions in the South Passage of the turbidity maximum zone (TMZ) of the Yangtze Estuary were selected for an analysis of the flow regime by remote sensing images. The remote sensing images of these regions obtained by the wide-band imaging spectrometer in Tiangong-2 in the maximum flood during spring tide in the dry season and in flood season were processed by a Gabor filter to get the texture images on the ocean surface. The flow direction was extracted by visual interpretation, and the semi-quantitative flow regime information was obtained by calculation of the texture entropy in the images. The results show that the texture information in the remote sensing images processed by this method is abundant. The streamline is clear, which can clearly reflect the changes in the flow regime in different seasons. The texture features of these images reflect the variation in the flow regime around Nanhuizui after the construction of the reclamation project in 2014. Remote sensing images of Tiangong-2 are feasible in the semi-quantitative interpretation of the flow regime in the TMZ with high suspended sediment concentration (SSC) in the estuary.

Keywords

Tiangong-2 Texture features Flow regime Turbidity maximum zone Yangtze Estuary 

Notes

Acknowledgements

We thank China Manned Space Engineering for providing the wide-band imaging spectrometer data products of Tiangong-2, and the National Nature Science Foundation of China-The Netherlands Organization for Scientific Research-Engineering and Physical Sciences Research Council (NSFC-NWO-EPSRC) (51761135023), and the China Geological Survey (DD20160246) for support.

References

  1. 1.
    Fernández-Prieto, D., Sabia, R.: Remote Sensing Advances for Earth System Science. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    Ding, X.Y., XU, X.X.: A remote sensing analysis of characteristics of suspended sediments movement in Hangjiang estuary. Remote. Sens. Land Resour. 19(3), 71–73 (2007)Google Scholar
  3. 3.
    Yun, C.X.: Recent Developments of the Changjiang Estuary. China Ocean Press, Beijing (2004). ChineseGoogle Scholar
  4. 4.
    Li, Y., Meng, X.P.: Image texture feature detection based on Gabor filter. J. Chang. Univ. Technol. (Natural Science Edition), 29(1), 78–81(2008). ChineseGoogle Scholar
  5. 5.
    Qiao, Y.Y., Cheng, H.Q., Song, Z.K., et al.: Research on information semi-quantitation of estuarine flow pattern based on TM remote sensing image. Bull. Soil Water Conserv. 34(5), 118–123 (2014). ChineseGoogle Scholar
  6. 6.
    Ulaby, F.T., Kouyate, F., Brisco, B., et al.: Texture features for browsing and retrieval of image data. IEEE Trans. PAMI 18(8), 837–842 (1996). ChineseGoogle Scholar
  7. 7.
    Lei, Y.S., Wang, S.M., Qin, R.: Edge information extraction algorithm of CT cerebrovascular medical image based on imaginary part of Gabor filter. J. Tianjin Univ. 40(7), 833–838 (2007). ChineseGoogle Scholar
  8. 8.
    Clausi, D.A., Jernigan, M.E.: Designing Gabor filters for optimal texture separability. Pattern Recogn. 33(11), 1835–1849 (2000)CrossRefGoogle Scholar
  9. 9.
    Ma, H.: The optical characteristics of the three elements in high turbidity water of the Yangtze River Estuary and its influence on the inversion of TSM, East China Normal University, Shanghai (2015). ChineseGoogle Scholar
  10. 10.
    Xie, H.L., Dai, Z.J., Zuo, S.H.: Morph dynamic processes of the south passage of the Yangtze Estuary (1959–2013). Ocean. Eng. 33(5):51–59 (2015). ChineseGoogle Scholar
  11. 11.
    Yv, J., Guan, Z.Q.: Research on transformation method of target texture feature description under different imaging conditions. Bull. Surv. Mapp. (s1), 375–379 (2012). ChineseGoogle Scholar
  12. 12.
    Chen, X.G., Feng, J.F.: Fast Gabor filtering. Acta Autom. Sin. 33(5), 456–461 (2007). ChineseGoogle Scholar
  13. 13.
    Li, S., Ge, Y., Li, D.Y.: Visualizing presentation of the attribute uncertainty in classified remotely sensed imagery. Remote. Sens. Land Resour. 18(2):20–25 (2006). ChineseGoogle Scholar
  14. 14.
    Wang, H.M., Shi, P.: Methods to extract images texture features. J. Commun. Univ. China Sci. Technol. 13(1), 49–52 (2006). ChineseGoogle Scholar
  15. 15.
    Shen, H.T., Pan, D.A.: Turbidity Maximum in the Changjiang Estuary. China Ocean Press, Beijing (2001). ChineseGoogle Scholar
  16. 16.
    Chen, W., Li, J.F., Li, W.H.: Recent suspended sediment transport in bifurcation area of north and south passage of the Yangtze Estuary. Resour. Environ. Yangtze Basin 22(7), 865 (2013). ChineseGoogle Scholar
  17. 17.
    Fan, Z.Y.: The effect of deep waterway project on current and salinity in Changjiang Estuary. East China Normal University, Shanghai (2011). ChineseGoogle Scholar
  18. 18.
    Chen, W., Gu, J., Qin, X., et al.: Numerical analysis of the sediment deposition in the upper reach of the deepwater navigation channel in the Changjiang River Estuary. Chin. J. Hydrodyn. 27(2), 199 (2012). ChineseGoogle Scholar
  19. 19.
    Pan, L.Z.: Impacts of deep waterway project on morphological change within the north passage of Changjiang Estuary, East China Normal University, Shanghai, China (2012). ChineseGoogle Scholar
  20. 20.
    Cao, Y., Zhu, J.Z.: Discuss on hydrodynamic influence of the Nanhui reclamation in Yangzi Estuary. National Congress on Hydronamics, Shanghai (2003). ChineseGoogle Scholar
  21. 21.
    Huang, G., Chen, S., Zhang, G.A.: Characteristics of water and sediment movement in Nanhui side beach and its influence on reclamation project Yangtze River. 38(1), 60–63 (2007). ChineseGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Estuarine and Coastal ResearchEast China Normal UniversityShanghaiChina
  2. 2.Institute of Eco-Chongming (IEC)ShanghaiChina

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