Abstract
Aim of study: The ambrosia beetle, Platypus quercivorus, is a vector of Japanese oak wilt, which causes massive mortality of oak trees in Japan. ALOS/AVNIR-2 true color images can be used to help detect areas of oak wilt, although such detection by inventory surveys is not realistic. Applying pan-sharpening techniques, a higher spatial resolution multispectral image can be generated from lower-resolution multispectral images and higher-resolution panchromatic images. In this study, some pan-sharpening algorithms were considered and evaluated for the detection of damage points.Area of study: The oak forests in Kanazawa prefecture, Japan.Materials and methods: The ALOS/AVNIR-2 and ALOS/PRISM sensors were used. The pan-sharpening algorithms adopted were: Brovey transformation, Modified IHS transformation, Wavelet transformation, Ehlers fusion and High Pass Filter Resolution Merge. Four types of quantitative spectral analyses and visual detection were conducted to evaluate these algorithms.Main results: The Brovey transformation was the most useful algorithm to detect damage points, although it had an issue with the preservation of spectral characteristics.Research highlights: The detection rate of damage points was improved in 50% by applying the Brovey algorithm to a 10 m panchromatic image and 62.5 m multispectral image.Key words: ambrosia beetle; oak wilt; pan-sharpening; satellite imagery; visual detection.
Highlights
Since the late 1980s, deciduous oak dieback has been prevalent in Japan, but recently, the infestation has lasted, and the area of dieback has spread to new localities where diebacks have never been recorded (Ito and Yamada, 1998)
Applying pan-sharpening techniques, a higher spatial resolution multispectral image can be generated from lower-resolution multispectral images and higher-resolution panchromatic images
Pan-sharpened imagery was generated with a pixel spacing of 10 m, and the original AVNIR-2 imagery was compared to evaluate the preservation of the spectral characteristics by the pansharpening algorithms
Summary
Since the late 1980s, deciduous oak dieback has been prevalent in Japan, but recently, the infestation has lasted, and the area of dieback has spread to new localities where diebacks have never been recorded (Ito and Yamada, 1998). Ambrosia beetles are wood-inhabiting, obligate mutualistic insects that construct galleries within which they cultivate fungi for food (Hulcr et al, 2007) and usually attack weakened or dead trees; e.g., the southern pine beetle (Rojas et al, 2010), the european elm bark beetle (Hubbes, 2004) and the spruce beetle (Makoto et al, 2013). Since ambrosia fungus cause the problems of oak wilt, decrease of wood resources and galleries, the determining the pattern of insect presence is a matter of great urgency. Applying pan-sharpening technics, higher spatial resolution multispectral image can be generated from a combination of lower resolution multispectral images and higher resolution panchromatic images
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