Panchromatic satellite image classification for flood hazard assessment

Ahmed Shaker, Wai Yeung Yan, Nagwa El-Ashmawy

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

The study aims to investigate the use of panchromatic (PAN) satellite image data for flood hazard assessment with an aid of various digital image processing techniques. Two SPOT PAN satellite images covering part of the Nile River in Egypt were used to delineate the flood extent during the years 1997 and 1998 (before and after a high flood). Three classification techniques, including the contextual classifier, maximum likelihood classifier and minimum distance classifier, were applied to the following: 1) the original PAN image data, 2) the original PAN image data and grey-level co-occurrence matrix texture created from the PAN data, and 3) the enhanced PAN image data using an edgesharpening filter. The classification results were assessed with reference to the results derived from manual digitization and random checkpoints. Generally, the results showed improvement of the calculation of flood area when an edge-sharpening filter was used. In addition, the maximum likelihood classifier yielded the best classification accuracy (up to 97%) compared to the other two classifiers. The research demonstrates the benefits of using PAN satellite imagery as a potential data source for flood hazard assessment.

Original languageEnglish
Pages (from-to)902-911
Number of pages10
JournalJournal of Applied Research and Technology
Volume10
Issue number6
DOIs
Publication statusPublished - Dec 2012
Externally publishedYes

Keywords

  • Flood hazard assessment
  • Image classification
  • Panchromatic imagery
  • Texture analysis

ASJC Scopus subject areas

  • Engineering(all)

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