Research Article

Modified fuzzy c-means classification technique for mapping vague wetlands using Landsat ETM+ imagery

  1. Wen-Ya Chiu*,
  2. Isabelle Couloigner

Article first published online: 18 OCT 2006

DOI: 10.1002/hyp.6378

Issue

Hydrological Processes

Hydrological Processes

Special Issue: Canadian Geophysical Union — Hydrology Section

Volume 20, Issue 17, pages 3623–3634, 15 November 2006

Additional Information

How to Cite

Chiu, W.-Y. and Couloigner, I. (2006), Modified fuzzy c-means classification technique for mapping vague wetlands using Landsat ETM+ imagery. Hydrol. Process., 20: 3623–3634. doi: 10.1002/hyp.6378

Author Information

  1. Department of Geomatics Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada

*Department of Geomatics Engineering, University of Calgary, Calgary, Alberta T2N 1N4, Canada.

Publication History

  1. Issue published online: 18 OCT 2006
  2. Article first published online: 18 OCT 2006
  3. Manuscript Accepted: 1 FEB 2006
  4. Manuscript Received: 1 AUG 2005

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Keywords:

  • Fuzzy C-Means (FCM) clustering;
  • wetlands;
  • spatial vagueness;
  • multispectral image;
  • spatial information;
  • classification

Abstract

Wetland mapping derived from remotely sensed images is subject to error and uncertainty. Fuzzy classification techniques can deal with the spectral and spatial vagueness, and can be used to model the uncertainty in remote sensing classification. In this paper, we present a modified Fuzzy C-Means (FCM) classifier that allows the local texture information to regularize the classification result iteratively, and we propose a threshold defuzzification method to extract the potential wetland areas from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) imagery. By introducing the transition classes during the defuzzification process, the modified classifier reduces commission-errors and improves the mapping accuracy when compared to the standard FCM classifier. The accuracy assessment and a test of statistical significance indicate that the modified FCM classifier shows a significantly better mapping result than the standard FCM classifier because of the incorporation of this spatial information. Copyright © 2006 John Wiley & Sons, Ltd.

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