• DocumentCode
    3343310
  • Title

    Mangrove detection from high resolution optical data

  • Author

    Christophe, Emmanuel ; Wong, Choong Min ; Liew, Soo Chin

  • Author_Institution
    Centre for Remote Imaging, Sensing & Process., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2010
  • fDate
    25-30 July 2010
  • Firstpage
    437
  • Lastpage
    440
  • Abstract
    Mangroves are an important part of the ecosystem in tropical region. Unfortunately, they are also under intense ecological pressure from fishing, tourism or logging. As they are often in not easily accessible places and scattered over large areas, satellite observation is an ideal solution to monitor the mangrove evolution over the past few years. However, the mapping of mangrove from satellite images is a difficult task and mostly done manually. Here we propose a detection method based on support vector machine, exploring more than 100 features, providing a good accurary, enabling the mangrove expert to focus on the most difficult areas.
  • Keywords
    environmental monitoring (geophysics); geophysical signal processing; hydrological techniques; support vector machines; vegetation; vegetation mapping; detection method; ecosystem; high resolution optical data; mangrove detection; mangrove evolution monitoring; mangrove mapping; satellite observation; support vector machine; tropical region; Asia; Feature extraction; Image resolution; Indexes; Satellites; Support vector machines; Vegetation mapping; SVM; classification; detection; feature selection; mangroves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
  • Conference_Location
    Honolulu, HI
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4244-9565-8
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2010.5652027
  • Filename
    5652027