Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+
International Journal of Atmospheric and Oceanic Sciences
Volume 1, Issue 1, December 2017, Pages: 1-6
Received: Sep. 24, 2016; Accepted: Nov. 14, 2016; Published: Dec. 21, 2016
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Jo Jong-Song, Department of Earth and Environmental Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea
Cha Jong-Hun, Department of Earth and Environmental Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea
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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.
Image Fusion, Shoreline, Landsat ETM+
To cite this article
Jo Jong-Song, Cha Jong-Hun, Application Effect Analysis of Image Fusion Methods for Extraction of Shoreline in Coastal Zone Using Landsat ETM+, International Journal of Atmospheric and Oceanic Sciences. Vol. 1, No. 1, 2017, pp. 1-6. doi: 10.11648/j.ijaos.20170101.11
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Buchanan, M. D. (1979). Effective Utilization of Color in Multidimensional Data Presentation. Paper presented at the Society of Photo-Optical Engineers, 199, 9-19.
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.
Crippen, R. E. (1987). The Regression Intersection Method of Adjusting Image Data for Band Ratioing. International Journal ofRemote Sensing, 8(2), 137-155.
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.
Daily, M. (1983). Hue-Saturation-Intensity Split-Spectrum Processing of Seasat Radar Imagery. Photogrammetric Engineering & Remote Sensing, 49(3), 349-355.
Frazier, P. S., &Page, K. J. (2000). Water Body Detection and Delineationwith Landsat TM Data. Photogrammetric Engineering and Remote Sensing, 66(12), 1461-1467.
García-Rubio, C., Huntley, D., & Russell, P. (2014). Evaluating shoreline identification using optical satellite images. Marine Geology, 359(2015), 96-105.
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.
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.
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.
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.
Liu, J. G., &Mason, P. J. (2009). Essential Image Processingand GIS for Remote Sensing, Wiley-Blackwell, London, 37-134.
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.
Schott, J. R. (2007). Remote Sensing the Image Chain Approach, 2nd Edition, OXFORDUNIVERSITY PRESS, 405-411.
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.
Welch, R., &Ehlers, W. (1987). Merging Multiresolution SPOT HRV and Landsat TM Data. Photogrammetric Engineering& Remote Sensing, 53(3), 301-303.
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.
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