Journal of East China Normal University(Natural Sc ›› 2010, Vol. 2010 ›› Issue (4): 26-34.

• Article • Previous Articles     Next Articles

Artificial neural network classification of wetland integrating GIS data: A case study of Dongtan wetland in Chongming, Shanghai

LI Xiao-dong1, GUO Zhong-yang1, ZHU Yan-ling1, DAI Xiao-yan2   

  1. 1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200062, China; 2. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
  • Received:2009-06-01 Revised:2009-10-01 Online:2010-07-25 Published:2010-07-25
  • Contact: GUO Zhong-yang

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Abstract: This paper took Dongtan wetland in Chongming Island, Shanghai, as a case study; using the PCA outputs of TM surface feature spectrum, NDVI, MNDWI, DEM and the GIS data as inputting elements of an Artificial Neural Network (ANN), combined with improved BP algorithm, an ANN classification was applied to the Dongtan wetland. The results show that the ANN classification method improves the classification accuracy, and can effectively distinguish those objects with similar TM spetra.

Key words: remote sensing classification, ANN, wetland, remote sensing classification, ANN