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A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatialresolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images.Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencingthe accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-basedpansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid withspectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectralsharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from theviewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened imagesgenerated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of theimages was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In thequantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band andland-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urbanand agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in theobserving spectral wavelengths of the sensors and local scene variances

COMPARISON OF THE SPECTRAL PROPERTIES OF PANSHARPENED IMAGES GENERATED FROM AVNIR-2 AND PRISM ONBOARD ALOS