An epidemic of Swiss needle cast, caused by the ascomycete Phaeocryptopus gaeumannii, is causing defoliation and growth reductions in Douglas-fir forest plantations along the Oregon Coast. The area of symptomatic plantations has been monitored annually since 1996 by aerial survey; in spring 1999, 119,500 ha were affected. Pathogen and symptom development have also been monitored on nine permanent plots in stands of differing disease severity. Infection levels and symptom severity are greatest in low elevation plantations close to the coast. In areas of severe disease, trees retain only current year needles. Defoliation is proportional to the number of stomata occluded by pseudothecia of the fungus, with needles being shed when about 50% of stomata are occupied, regardless of needle age. Fungus sporulation and premature needle abscission are greatest on the upper branches of trees. Annual application of fungicides increases needle retention significantly. Tree height and diameter growth and total tree volume are reduced by disease, and tree volume is significantly correlated with needle retention on our plot trees. The epidemic continues to be most severe in Douglas-fir plantations established on sites where Sitka spruce and western hemlock or red alder predominated in earlier times.

The main objective of this article is quality assessment of pansharpening fusion methods. Pansharpening is a fusion technique to combine a panchromatic image of high spatial resolution with multispectral image data of lower spatial resolution to obtain a high-resolution multispectral image. During this process, the significant spectral characteristics of the multispectral data should be preserved. For images acquired at the same time by the same sensor, most algorithms for pansharpening provide very good results, i.e. they retain the high spatial resolution of the panchromatic image and the spectral information from the multispectral image (single-sensor, single-date fusion). For multi-date, multi-sensor fusion, however, these techniques can still create spatially enhanced data sets, but usually at the expense of the spectral consistency. In this study, eight different methods are compared for image fusion to show their ability to fuse multitemporal and multi-sensor image data. A series of eight multitemporal multispectral remote sensing images is fused with a panchromatic Ikonos image and a TerraSAR-X radar image as a panchromatic substitute. The fused images are visually and quantitatively analysed for spectral characteristics preservation and spatial improvement. It can not only be proven that the Ehlers fusion is superior to all other tested algorithms, it is also the only method that guarantees excellent colour preservation for all dates and sensors used in this study.

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