International Journal of Atmospheric and Oceanic Sciences

| Peer-Reviewed |

Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+

Received: 24 September 2016    Accepted: 14 November 2016    Published: 21 December 2016
Views:       Downloads:

Share This Article

Abstract

Extraction of shoreline incoastal zone is important for coast protection and management. This paper presents extractingthe shoreline with fusion images, which are obtained using various image fusion methods such as IHStransform, Brovey Transform, Multiplicative, Principle Component, Wavelet Resolution Merge. Artificial constructions (e.g. coastalembankments), islands, lakes, tidal mudflats and estuaries have been selected as evaluation objects, shorelines of which are extracted and analyzed. The result indicates that shoreline extraction effect by the Principle Component method is bestamong other methods.

DOI 10.11648/j.ijaos.20170101.11
Published in International Journal of Atmospheric and Oceanic Sciences (Volume 1, Issue 1, December 2017)
Page(s) 1-6
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Previous article
Keywords

Image Fusion, Shoreline, Landsat ETM+

References
[1] Buchanan, M. D. (1979). Effective Utilization of Color in Multidimensional Data Presentation. Paper presented at the Society of Photo-Optical Engineers, 199, 9-19.
[2] Chavez, P. S., Jr., Sides, S. C., & Anderson, J. A. (1991). Comparison of Three Different Methods to Merge Multiresolution andMultispectral Data: Landsat TM and SPOT Panchromatic. Photogrammetric Engineering & Remote Sensing, 57(3), 295-303.
[3] Crippen, R. E. (1987). The Regression Intersection Method of Adjusting Image Data for Band Ratioing. International Journal ofRemote Sensing, 8(2), 137-155.
[4] Crippen, R. E. (1989). A Simple Spatial Filtering Routine for the Cosmetic Removal of Scan-Line Noise from Landsat TM P-Tape Imagery. Photogrammetric Engineering & Remote Sensing, 55(3), 327-331.
[5] Daily, M. (1983). Hue-Saturation-Intensity Split-Spectrum Processing of Seasat Radar Imagery. Photogrammetric Engineering & Remote Sensing, 49(3), 349-355.
[6] Frazier, P. S., &Page, K. J. (2000). Water Body Detection and Delineationwith Landsat TM Data. Photogrammetric Engineering and Remote Sensing, 66(12), 1461-1467.
[7] García-Rubio, C., Huntley, D., & Russell, P. (2014). Evaluating shoreline identification using optical satellite images. Marine Geology, 359(2015), 96-105.
[8] Ghoneim, E., Mashaly, J., Gamble, D., Halls, J., &AbuBakr, M. (2014). Nile Delta exhibited a spatial reversal in the rates of shoreline retreat on the Rosetta promontory comparing pre- and post-beach protection. Geomorphology, 228(2015), 1-14.
[9] Kloiber, S. M., Brezonik, P. L., & Bauer, M. E. (2002). Application of Landsat Imagery to Regional scale Assessment of Lake Clarity. Water Research, 36, 4330-4340.
[10] Kong, D. X., Miao, C. Y., Borthwick, A. G. L., Duan, Q. Y., Liu, H., Sun, Q. H., Ye, A. Z., Di, Z. H., & Gong, W. (2014). Evolution of the Yellow River Delta and its relationship with runoff and sediment load from 1983 to 2011. Journal of Hydrology. 520(2015), 157-167.
[11] Lemeshewsky, George P. (1999). Multispectral multisensor image fusion using wavelet transforms. in Visual Image Processing VIII, S. K. Park and R. Juday, Ed., Proc SPIE 3716, 214-222.
[12] Liu, J. G., &Mason, P. J. (2009). Essential Image Processingand GIS for Remote Sensing, Wiley-Blackwell, London, 37-134.
[13] McFeeters, S. K. (1996) The Use of Normalized Difference Water Index(NDWI) in the Delineation of Open Water Features. InternationalJournal of Remote Sensing, 17(7), 1425-1432.
[14] Schott, J. R. (2007). Remote Sensing the Image Chain Approach, 2nd Edition, OXFORDUNIVERSITY PRESS, 405-411.
[15] Vijay, P. S., Nicolas, H. Y.,&Roger L. K.(2008). An Efficient Pan-Sharpening Method via a CombinedAdaptive PCA Approach and Contourlets, IEEE Trans. Geosci. RemoteSens., 46(5), 1323-1335.
[16] Welch, R., &Ehlers, W. (1987). Merging Multiresolution SPOT HRV and Landsat TM Data. Photogrammetric Engineering& Remote Sensing, 53(3), 301-303.
[17] Yocky, D. A. (1995). Image merging and data fusion by means of the two-dimensional wavelet transform, J. Opt. Soc. Amer., 12(9), 1834-1845.
Cite This Article
  • APA Style

    Jo Jong-Song, Cha Jong-Hun. (2016). Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+. International Journal of Atmospheric and Oceanic Sciences, 1(1), 1-6. https://doi.org/10.11648/j.ijaos.20170101.11

    Copy | Download

    ACS Style

    Jo Jong-Song; Cha Jong-Hun. Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+. Int. J. Atmos. Oceanic Sci. 2016, 1(1), 1-6. doi: 10.11648/j.ijaos.20170101.11

    Copy | Download

    AMA Style

    Jo Jong-Song, Cha Jong-Hun. Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+. Int J Atmos Oceanic Sci. 2016;1(1):1-6. doi: 10.11648/j.ijaos.20170101.11

    Copy | Download

  • @article{10.11648/j.ijaos.20170101.11,
      author = {Jo Jong-Song and Cha Jong-Hun},
      title = {Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+},
      journal = {International Journal of Atmospheric and Oceanic Sciences},
      volume = {1},
      number = {1},
      pages = {1-6},
      doi = {10.11648/j.ijaos.20170101.11},
      url = {https://doi.org/10.11648/j.ijaos.20170101.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijaos.20170101.11},
      abstract = {Extraction of shoreline incoastal zone is important for coast protection and management. This paper presents extractingthe shoreline with fusion images, which are obtained using various image fusion methods such as IHStransform, Brovey Transform, Multiplicative, Principle Component, Wavelet Resolution Merge. Artificial constructions (e.g. coastalembankments), islands, lakes, tidal mudflats and estuaries have been selected as evaluation objects, shorelines of which are extracted and analyzed. The result indicates that shoreline extraction effect by the Principle Component method is bestamong other methods.},
     year = {2016}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+
    AU  - Jo Jong-Song
    AU  - Cha Jong-Hun
    Y1  - 2016/12/21
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ijaos.20170101.11
    DO  - 10.11648/j.ijaos.20170101.11
    T2  - International Journal of Atmospheric and Oceanic Sciences
    JF  - International Journal of Atmospheric and Oceanic Sciences
    JO  - International Journal of Atmospheric and Oceanic Sciences
    SP  - 1
    EP  - 6
    PB  - Science Publishing Group
    SN  - 2640-1150
    UR  - https://doi.org/10.11648/j.ijaos.20170101.11
    AB  - Extraction of shoreline incoastal zone is important for coast protection and management. This paper presents extractingthe shoreline with fusion images, which are obtained using various image fusion methods such as IHStransform, Brovey Transform, Multiplicative, Principle Component, Wavelet Resolution Merge. Artificial constructions (e.g. coastalembankments), islands, lakes, tidal mudflats and estuaries have been selected as evaluation objects, shorelines of which are extracted and analyzed. The result indicates that shoreline extraction effect by the Principle Component method is bestamong other methods.
    VL  - 1
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • Department of Earth and Environmental Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea

  • Department of Earth and Environmental Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea

  • Sections