Improved water classification using an application-oriented processing of landsat ETM+ and ALOS PALSAR

Xiaohong Xiao, Shimon Wdowinski, Yonggang Wu

Research output: Contribution to journalArticle


The aim of this study is to extract water body using the integrated features of Landsat ETM+ and ALOS PALSAR data. Water body extracted from Landsat ETM+ tends to lose smaller water bodies like small rivers and ponds. Besides, water area with plant (lotus) is difficult to recognize. ALOS PALSAR data have a much higher resolution, capable of extracting almost all the water bodies without confusion with other surface features, but leave some holes in water bodies due to its speckles. As a consequence, there is a significant interest in the development of fusion methods that are able to take advantage of the complementary nature of Landsat ETM+ and ALOS PALSAR data. A new combination method of integrating band 3, band 7 of Landsat ETM+ with a modified HH polarization of ALOS PALSAR is proposed, which well combine the complementary water information from each source compared to the standard image fusion methods. Experimental outcomes of the proposed combination B37ModHH shows great enhancement in water classification accuracy compared to Landsat ETM+ and ALOS PALSAR alone.

Original languageEnglish (US)
Pages (from-to)373-388
Number of pages16
JournalInternational Journal of Control and Automation
Issue number11
StatePublished - 2014



  • Image fusion
  • Landsat ETM
  • Remote sensing
  • Water extraction

ASJC Scopus subject areas

  • Control and Systems Engineering

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