Abstract
Geometrically corrected time series satellite images are often used for landcover change detections. The change detections are carried out under the assumption that pixel boundaries of geometrically corrected time series satellite images cover the same location. However that assumption can be wrong when shifts in the pointing direction of a satellite sensor occur. Currently, although the influence of misregistration on landcover change detection has been investigated, there have been few researchs on the influence of pointing direction shifts of a satellite sensor. In this study, a simple method for reducing the effects of pointing direction shifts of a satellite sensor is proposed : the classification of two ASTER images was carried out using the spectral mixture analysis, the two classification results are resampled into a geometrically fixed grid, and then the change detection of the two ASTER images was carried out by comparing the resampled classification results of the two images. The proposed method showed high performance in discriminating between changed areas and unchanged areas by removing the influence of the pointing direction shifts of a satellite sensor.
