• DocumentCode
    2241104
  • Title

    Early detecting ash Emerald Ash Borer (EAB) infestation using Hyperspectral imagery

  • Author

    Zhang, Kongwen ; Hu, Baoxin ; Hanou, Ian ; Jin, Linhai

  • Author_Institution
    Dept. of Earth & Space Sci. & Eng., York Univ., Toronto, ON, Canada
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    6360
  • Lastpage
    6363
  • Abstract
    The Emerald Ash Borer (Agrilus planipennis, EAB) is one of the most destructive insects damaging all Ash species of the genus Fraxinus in Ontario, Canada. It is crucial to detect the EAB invasion as early as possible to allow possible treatments and reduce economic loss. The challenge is that there are limited symptoms indicating EAB infestation due to this pest´s cryptic life stage. The current detection methods are all in-situ approaches, which are labour intensive and economically inefficient. In this study, the object oriented vegetation indices and texture information derived from Hyperspectral imagery were investigated to test the hypothesis that stressed Ash trees are more vulnerable to EAB and can be used to predict infestation levels.
  • Keywords
    geophysical image processing; image texture; object-oriented methods; vegetation mapping; Agrilus planipennis; Ash species; Ash trees; Canada; EAB infestation; EAB invasion; Ontario; ash emerald ash borer infestation; destructive insects; detection methods; economic loss; genus Fraxinus; hyperspectral imagery; infestation levels; object oriented vegetation indices; pest cryptic life stage; texture information; Ash; Educational Activities Board; Hyperspectral imaging; Indexes; Stress; Vegetation; EAB; Hyperspectral; data analysis; early detection; texture; vegetation index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6352714
  • Filename
    6352714