In order to enhance the spectral characteristics of features for clustering, in the experiment of wetland extraction in
Sanjiang Plain, we use a series of approaches in preprocessing of the MODIS remote sensing data by considering
eliminating interference caused by other features. First, by analysis of the spectral characteristics of data, we choose a set
of multi-temporal and multi-spectral MODIS data in Sanjiang Plain for clustering. By building and applying mask, the
water areas and woodland vegetation can be eliminated from the image data. Second, by Enhanced Lee filtering and
Minimum Noise Fraction (MNF) transformation, the data can be denoised and the characteristics of wetland can be
enhanced obviously. After the preprocessing of data, the fuzzy c-means clustering algorithm optimized by particle
swarm algorithm (PSO-FCM) is utilized on the image data for the wetland extraction. The result of experiment shows
that the accuracy of wetland extraction by means of PSO-FCM algorithm is reasonable and effective.
Conference Committee Involvement (1)
International Conference on Earth Observation Data Processing and Analysis
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