Waterline extraction from Landsat TM data in a tidal flat a case study in Gomso Bay, Korea

Joo Hyung Ryu, Joong Sun Won, Kyung Duck Min

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343 Citations (Scopus)


Waterline extraction is potentially one of the most effective satellite remote sensing tools for studying changes in tidal flat environment and coastlines. However, its application to the study of tidal flats has not been investigated in detail. The waterline in a tidal flat in Gomso Bay, Korea is characterized and evaluated using 27 sets of Landsat thematic mapper (TM) and Earth Observing System-Terra (EOS-Terra) Advanced Spaceborne Thermal Emission and Radiometer (ASTER) data. Ground truth data including grain size, soil moisture content, ground levelling, and waterline tracking have been obtained. The choice of spectral bands in terms of tidal conditions turned out to play a key role in locating the waterline. While the waterlines extracted from near-infrared (NIR), short-wavelength infrared (SWIR), and thermal infrared (TIR) data are commonly reliable on the flood fide, the discrepancies between different bands become large on the ebb tide. The bands TIR, NIR, and SWlR are, in that order, decreasingly effective in extracting the waterline while ebb tides are in progress. The effect of turbid water on NIR can be reduced by a ratioing of NIR and the visible band. The location of the waterline is also an important factor to consider; the discrepancy is largest on the middle tidal flat. Selection of the proper band for waterline extraction under various conditions is suggested. However, no single band can accommodate all aspects of the tidal flat environment. A schematic model associated with the spectral reflectance of the tidal flat is proposed in which the remnant water scattered on the surface after exposure is emphasized as an additional factor.

Original languageEnglish
Pages (from-to)442-456
Number of pages15
JournalRemote Sensing of Environment
Issue number3
Publication statusPublished - 2002 Dec 1

All Science Journal Classification (ASJC) codes

  • Soil Science
  • Geology
  • Computers in Earth Sciences


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