Skip to main content
SpringerLink
Log in

Slope instability detection for muddy submarine channels using sub-bottom profile images based on bidimensional empirical mode decomposition

  • Original
  • Published:
Geo-Marine Letters Aims and scope Submit manuscript

Abstract

Slope stability is a key problem for safe submarine channel operation on muddy coasts. The early detection and identification of slope instabilities is important to allow safety measures to be taken in a timely manner. Owing to the difficulties in predicting or providing early forecasts of slope collapse in muddy submarine channels, this study introduces a bidimensional empirical mode decomposition (BEMD) with adaptive time–frequency resolution to identify slope instabilities using sound prints of sub-bottom profile images. The results show that three bidimensional intrinsic mode function (BIMF) images decomposed by BEMD with frequencies ranging from high to low can depict the spatial variation in the sound prints. The second and third BIMF images reveal the spatial relationship between the sound prints and the slope abnormalities at the early stage of slope collapse. This approach effectively identifies the early sound prints and the spatial information of the sub-bottom profile images during the process of slope collapse, which can improve abnormal feature recognition. This method will help in the prediction and early forecast of channel slope instability and collapse.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

References

  • Chen DC, Zhang GA, Yu ZY (2007) Report on shoreline evolution and stability in Lianyungang Harbor. Eastern China Normal University, Shanghai (in Chinese)

    Google Scholar 

  • Chen WK, Lee JC, Han WY, Shih CK, Chang KC (2013) Iris recognition based on bidimensional empirical mode decomposition and fractal dimension. Inf Sci 221:439–451

    Article  Google Scholar 

  • Chen T, Ju SH, Yuan XH, Elhoseny M, Ren FJ, Fan MY, Chen ZG (2018) Emotion recognition using empirical mode decomposition and approximation entropy. Comput Electr Eng 72:383–392

    Article  Google Scholar 

  • Chen YQ, Zhang LN, Zhao BB (2019) Identification of the anomaly component using BEMD combined with PCA from element concentrations in the Tengchong tin belt, SW China. Geosci Front 10:1561–1576

    Article  Google Scholar 

  • Frazer LN, Fu SS, Wilkens RH (1999) Seabed sediment attenuation profiles from a movable sub-bottom acoustic vertical array. J Acoust Soc Am 106:120–130

    Article  Google Scholar 

  • Hamilton EL (1970) Sound velocity and related properties of marine sediments, North Pacific. J Geophys Res 75:4423–4446

    Article  Google Scholar 

  • Hojat A, Arosio D, Ivanov VI, Longoni L, Papini M, Scaioni M, Tresoldi G, Zanzi L (2019) Geoelectrical characterization and monitoring of slopes on a rainfall-triggered landslide simulator. J Appl Geophys 170:103844

    Article  Google Scholar 

  • Hou WS, Yang ZJ, Zhou YZ, Zhang LP, Wu WL (2012) Extracting magnetic anomalies based on an improved BEMD method: a case study in the Pangxidong Area, South China. Comput Geosci 48:1–8

    Article  Google Scholar 

  • Hou ZY, Guo CS, Wang JQ, Chen WJ, Li TG, Zhang YX, Fu YT (2017) Analysis of the influences of physical parameters on sediment sound speed. Mar Georesour Geotechnol 35:466–471

    Article  Google Scholar 

  • Hu GH, Liu ZC, Sun YF, Zhang XL (2004) Advances in the research on sediment failure on submarine slope. Coast Eng 23:63–72 (in Chinese)

    Google Scholar 

  • Huang NE, Shen Z, Long SR, Wu MC, Shi HH, Zheng Q, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis. Proc R Soc Lond 454:903–995

    Article  Google Scholar 

  • Huang JN, Zhao BB, Chen YQ, Zhao PD (2010) Bidimensional empirical mode decomposition (BEMD) for extraction of gravity anomalies associated with gold mineralization in the Tongshi gold field, Western Shandong Uplifted Block, Eastern China. Comput Geosci 36:987–995

    Article  Google Scholar 

  • Karu K, Jain AK, Bolle RM (1996) Is there any texture in the image? Pattern Recogn 29:1437–1446

    Article  Google Scholar 

  • Lu B, Liang YB (1993) Acoustic velocity and physical parameters relationship in marine sediments. Marine Sciences. Mar Sci 11:54–57

    Google Scholar 

  • Lu YZ, Lu RF (2020) Enhancing chlorophyll fluorescence imaging under structured illumination with automatic vignetting correction for detection of chilling injury in cucumbers. Comput Electron Agric 168:1–9

    Article  Google Scholar 

  • Mosquera R, Groposo V, Pedocchi F (2014) Acoustic measurements of a liquefied cohesive sediment bed under waves. Adv Geosci 39:1–7

    Article  Google Scholar 

  • Nunes JC, Bouaoune Y, Delechelle E, Niang O, Bunel P (2003) Image analysis by bidimensional empirical mode decomposition. Image Vis Comput 21:1019–1026

    Article  Google Scholar 

  • Nunes JC, Guyot S, Delechelle E (2005) Texture analysis based on local analysis of the bidimensional empirical mode decomposition. Mach Vis Appl 16:177–188

    Article  Google Scholar 

  • Qi HF, Chen ZL, Li YC, Feng SJ, Chen HX (2020) Wave and current-induced dynamic response in a multilayered poroelastic seabed. Bull Eng Geol Environ 79:11–26

    Article  Google Scholar 

  • Qiao LH, Niu KF, Wang N, Peng LZ (2011) Perfect reconstruction image modulation based on BEMD and quaternionic analytic signals. SCIENCE CHINA Inf Sci 54:2602–2614

    Article  Google Scholar 

  • Shanmugam G (2015) The landslide problem. J Palaeogeogr 4:109–166

    Article  Google Scholar 

  • Sitkiewicz P, Rudowski S, Wróblewski R, Dworniczak J (2020) New insights into the nearshore bar internal structure using high-resolution sub-bottom profiling: the Vistula Spit case study. Mar Geol 419:1–10

    Article  Google Scholar 

  • Soh DCK, Ng EYK, Jahmunah V, Oh SL, San TR, Acharya UR (2020) A computational intelligence tool for the detection of hypertension using empirical mode decomposition. Comput Biol Med 118:1–6

    Article  Google Scholar 

  • Talling PJ, Wynn RB, Masson DG, Frenz M, Cronin BT, Schiebel R, Akhmetzhanov AM, Dallmeier-Tiessen S, Benetti S, Weaver PPE, Georgiopoulou A, Zühlsdorff C, Amy LA (2007) Onset of submarine debris flow deposition far from original giant landslide. Nature 450:541–544

    Article  Google Scholar 

  • Tang XS, Zhang YR, Tang HM (2013) Numerical analysis on the evolutionary features of deformation and failure modes of slopes. J Chongqing Univ 10:101–113 (in Chinese)

    Google Scholar 

  • Tran VT, Yang BS, Gu FS, Ball A (2013) Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis. Mech Syst Signal Process 38:601–614

    Article  Google Scholar 

  • Urlaub M, Villinger H (2018) Combining in situ monitoring using seabed instruments and numerical modelling to assess the transient stability of underwater slopes. Geological Society, London Special Publications. SP477.8

    Google Scholar 

  • Wang BC, Yu ZY, Liu CY, Jin QX (1980) The change of coasts and beaches and the movement of longshore sediments of Haizhou Bay. Acta Oceanol Sin 1:79–96 (in Chinese)

    Google Scholar 

  • Wu C, Zhou RZ (2013) nonlinear behavior analysis of structural dynamic response based on Hilbert spectrum. J Vibr Shock 32:69–77 (in Chinese)

    Google Scholar 

  • Xia SQ, Zhang JH, Ye SG, Xu B, Xiang JW, Tang HS (2019) A mechanical fault detection strategy based on the doubly iterative empirical mode decomposition. Appl Acoust 155:346–357

    Article  Google Scholar 

  • Xie MX, Zhang W, Guo WJ (2010) A validation concept for cohesive sediment transport model and application on Lianyungang Harbor, China. Coast Eng 57:585–596

    Article  Google Scholar 

  • Xu Q, Zhang YM, Huang RQ (1998) The analysis on nonlinear characteristics of slope developing process. J Geol Hazards Environ Preserv 9:1–4 (in Chinese)

    Google Scholar 

  • Ye JH, Zhang Y, Wang R, Zhu CQ (2014) Nonlinear interaction between wave, breakwater and its loose seabed foundation: a small-scale case. Ocean Eng 91:300–315

    Article  Google Scholar 

  • Yu ZY, Jin L, Hao XJ, Chen D (1981) The analysis of the problems concerning the building of Lianyungang deep-water outer navigation channel. J Eastern China Normal Univ 3:99–112 (in Chinese)

    Google Scholar 

  • Zhang CY (2019) Synthetic evaluation on the slope stability of muddy submarine channel based on the fuzzy comprehensive method. J Saf Environ 6:1892–1897 (in Chinese)

    Google Scholar 

Download references

Acknowledgements

The author would like to thank Wang X, Xu J, Wang Y, Feng J W, and Liu Z Y, who are Marine Technology undergraduate students, and Liu T P, Li T Y, and Chang T Y, who are Marine Resources Development Technology undergraduate students at Jiangsu Ocean University for their help with the fieldwork and laboratory experiments.

Funding

This work was supported by the Key Research and Development Program of Jiangsu Province (grant number BE2018676) and a project funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions.

Author information

Authors and Affiliations

  1. School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang, 222005, China

    Cunyong Zhang

Authors
  1. Cunyong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cunyong Zhang.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, C. Slope instability detection for muddy submarine channels using sub-bottom profile images based on bidimensional empirical mode decomposition. Geo-Mar Lett 41, 1 (2021). https://doi.org/10.1007/s00367-020-00681-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00367-020-00681-5

Search

Navigation