2012Unpublished venueRequires access

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

Kongwen Zhang, Baoxin Hu, Ian S. Hanou, Linhai Jin

Open publisher page 2 citations

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.

About this research paper

What this paper is about

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.

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Available 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.

Key concepts: Emerald ash borer, Agrilus, Fraxinus, Infestation, Hyperspectral imaging, Vegetation (pathology), PEST analysis, Environmental science

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