It is difficult for remote sensing change detection based only on spectral information to obtain satisfactory results. In this paper, multiscale texture information combined with spectral information was adopted to evaluate the urban expansion detection by using the post-classification comparison technique. The results show that, if the scale for texture extraction and the data combination are appropriately selected, the addition of texture features in change detection can significantly improve the overall accuracy and Kappa coefficient in comparison with the method based only on spectral data. Moreover, the combination of multiscale texture and spectral data in change detection can produce the highest accuracy. However, it is shown that false alarm may appear on the edges of some land cover types when the texture information is incorporated in urban area change detection.