J4 ›› 2011, Vol. 41 ›› Issue (4): 1246-1252.

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Wetland Classification Using Evidential Reasoning Approach with Multi-Temporal Landsat ETM+Imagery

LI Hua-peng1, 2, ZHANG Shu-qing1, SUN Yan1, 2, LIU Chun-yue1, 2   

  1. 1.Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun130012, China;
    2.Graduate University, Chinese Academy of Sciences, Beijing100049, China
  • Received:2010-10-07 Online:2011-07-26 Published:2011-07-26

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Abstract:

The Zhalong National Nature Reserve (NNR) that located in Heilongjiang Province was selected as a study area, five temporal ETM+imagery covering the study area were used as material for wetland mapping. An evidential reasoning (ER) approach that built on Dempster-Shafer theory was introduced to combine the five images. We used a new algorithm named minimum distance to generate evidence support from ETM+image. Results indicated that ER was an effective approach to integrate multi-temporal imagery for wetland mapping. Compared to classification results of single image based maximum likelihood classifier (MLC), the improvement of overall accuracy by ER approach was apparent (2%-12%).

Key words: image classification, wetland spatial classification, multi-temporal imagery, evidential reasoning (ER), remote sensing

CLC Number: 

  • TP79
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