The use of multidate multichannel radiance data in urban feature analysis

Abstract Previous work has suggested that seasonally varying reflectance properties are predictably related to radiance recorded by multichannel remote sensing devices. Two images were obtained from thematic mappers on Landsats 4 and 5 over the Washington, DC area during November 1982 and March 1984. These were registered, and selected training areas containing different types of urban land use were examined, one area consisting entirely of forest. Mean digital radiance values for each bandpass in each image were examined and variances, standard deviations, and covariances between bandpasses were calculated. We found that two bandpasses caused forested areas to stand out from other land use types, especially for the November 1982 image. In order to evaluate quantitatively the possible utility of principal components analysis in selected feature extraction, the eigenvectors were evaluated for principal axes rotations which rendered each selected land use type most separable from all other land use types. The evaluated eigenvectors were plotted as a function of land use type, whose order was decided by considering anticipated shadow component and by examination of the relative loadings indicative of vegetation for each of the principal components for the different features considered. The analysis was performed for each seven-band image separately and for the two combined images. We found that by combining the two images, we obtained more dramatic land use type separation. Conclusions have been drawn from this preliminary work suggesting directions for further study. Both British and U.S. image analysis systems were used.