Abstract
The emerald ash borer (EAB) poses a significant economic and environmental threat to ash trees in southern Ontario, Canada, and the northern states of the USA. It is critical that effective technologies are urgently developed to detect, monitor, and control the spread of EAB. This paper presents a methodology using multisourced data to predict potential infestations of EAB in the town of Oakville, Ontario, Canada. The information combined in this study includes remotely sensed data, such as high spatial resolution aerial imagery, commercial ground and airborne hyperspectral data, and Google Earth imagery, in addition to nonremotely sensed data, such as archived paper maps and documents. This wide range of data provides extensive information that can be used for early detection of EAB, yet their effective employment and use remain a significant challenge. A prediction function was developed to estimate the EAB infestation states of individual ash trees using three major attributes: leaf chlorophyll content, tree crown spatial pattern, and prior knowledge. Comparison between these predicted values and a ground-based survey demonstrated an overall accuracy of 62.5%, with 22.5% omission and 18.5% commission errors.
Highlights
The emerald ash borer (Agrilus planipennis, EAB) is one of the most destructive insects to affect ash species of the genus Fraxinus.[1,2] Ash is one of the most popular landscape trees in North America, replacing elm trees in new residential and commercial developments due to its high tolerance to environmental stresses and its resistance to pests.[3]
If this spectrum is input into the PROSAIL model, with three variables and the remaining parameters set to the values mentioned in the method section, the inversion result, giving leaf chlorophyll content, is 65
This study proposed an object-oriented approach to detecting early infestation of EAB from multisourced data, such as hyperspectral and high spatial resolution imagery
Summary
The emerald ash borer (Agrilus planipennis, EAB) is one of the most destructive insects to affect ash species of the genus Fraxinus.[1,2] Ash is one of the most popular landscape trees in North America, replacing elm trees in new residential and commercial developments due to its high tolerance to environmental stresses and its resistance to pests.[3]. In Pontius et al.,[9] a six-parameter function was proposed, and a 97% correlation was reported between selected vegetation indices and tree decline caused by EAB infestations This correlation can only be confirmed in the dieback stages, and the spectral-based variation is not sufficiently significant during the early infestation stage to allow unique identification. A significant drop compared to the surroundings, in addition to the tree crown degradation and distance from known infested trees may be considered key factors that can potentially lead to accurate estimation of the extent of infestation Despite recognition of these key factors, it remains a challenge to effectively assemble the diverse information derived from multisourced data in order to reach a meaningful, consistent, and accurate conclusion. Map out the health of individual ash trees within test areas using the proposed methodology
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