Hyperspectral imaging data collected by airborne and satellite platforms have been used in a variety of fields, such as geology, agriculture and forestry. In order to make such quantitative and precise applications, accurate spectral calibrations of hyperspectral imaging data are necessary to be achieved. The center wavelength for each band obtained in a laboratory needs to be adjusted, since it changes easily by vibration and variation of observation condition. The shift of center wavelength triggers an artifact in atmospheric correction necessary for quantitative estimation of ground surface target. The quantitative estimation of the artifact appeared around absorption bands is important for accurate spectral calibration. This paper describes a new estimation method for the artifact, and shows that the artifact reduction is achieved by calibration of center wavelength with our proposed methods. Furthermore, we evaluate the artifact influence on practical remote sensing application, such as tree classification. Our estimation method accurately evaluates the artifact and makes wavelength corrected hyperspectral image without artifact. We clarify that the spectral change of artifact having a tendency in cross-track that is more influential in classification than spectral change of tree species. This method has been effectively applied to a variety of land use applications using data acquired with airborne hyperspectral imagers.
