• DocumentCode
    3009646
  • Title

    Applying a New Integrated Classification Method to Monitor Shifting Mangrove Wetlands

  • Author

    Liu, Caixia ; Guo, Ziqi ; Fu, Nanxiang

  • Author_Institution
    State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Remotely sensed technique is a potential method for mangrove management. Free multi-temporal Landsat imagery data provided a feasible approach to monitor shifting mangrove wetlands in China. In order to know the historic and present situation of the west shore of Donghai Island mangrove, a new integrated classification method with Support Vector Machines (SVM) and Decision Tree (DT) was applied, which is more effective than SVM algorithm. The integrated method combined the information of spectrum, spectral transformation and geographical position for land cover extraction. Post-classification change detection was used for analyzing the mangrove loss conditions and its possible reasons in the past three decades. The results informed that the mangroves in the study area has been most affected since the early 1970s, nearly 62% of the mangrove area has lost. The annual loss rate exceeded 3.18%, higher than world total loss rate as 2.07%.
  • Keywords
    decision trees; geophysical image processing; pattern classification; remote sensing; support vector machines; Donghai Island mangrove; decision tree; integrated classification method; land cover extraction; mangrove management; multitemporal landsat imagery data; post classification change detection; remotely sensed technique; shifting mangrove wetlands monitoring; spectral transformation; spectrum information; support vector machines; Accuracy; Classification tree analysis; Earth; Monitoring; Remote sensing; Satellites; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Technology (ICMT), 2010 International Conference on
  • Conference_Location
    Ningbo
  • Print_ISBN
    978-1-4244-7871-2
  • Type

    conf

  • DOI
    10.1109/ICMULT.2010.5631392
  • Filename
    5631392