• Title of article

    Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery

  • Author/Authors

    Zhang، نويسنده , , Caiyun and Selch، نويسنده , , Donna and Xie، نويسنده , , Zhixiao and Roberts، نويسنده , , Charles and Cooper، نويسنده , , Hannah and Chen، نويسنده , , Ge، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    10
  • From page
    88
  • To page
    97
  • Abstract
    Accurate mapping of benthic habitats in the Florida Keys is essential in developing effective management strategies for this unique coastal ecosystem. In this study, we evaluated the applicability of hyperspectral imagery collected from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) for benthic habitat mapping in the Florida Keys. An overall accuracy of 84.3% and 86.7% was achieved respectively for a group-level (3-class) and code-level (12-class) classification by integrating object-based image analysis (OBIA), hyperspectral image processing methods, and machine learning algorithms. Accurate and informative object-based benthic habitat maps were produced. Three commonly used image correction procedures (atmospheric, sun-glint, and water-column corrections) were proved unnecessary for small area mapping in the Florida Keys. Inclusion of bathymetry data in the mapping procedure did not increase the classification accuracy. This study indicates that hyperspectral systems are promising in accurate benthic habitat mapping at a fine detail level.
  • Keywords
    benthic habitat classification , OBIA , Machine Learning , Florida Keys , Hyperspectral remote sensing
  • Journal title
    Estuarine, Coastal and Shelf Science
  • Serial Year
    2013
  • Journal title
    Estuarine, Coastal and Shelf Science
  • Record number

    1945757