Most of change detection algorithms for multi-temporal images are performed in unit of pixels. Due to the limit of spatial resolution, a pixel is, in many cases, a mixed pixel that contains more than one ground cover types. In order to explore more information from images, we have reviewed several spectral unmixing algorithms and used them to accomplish subpixel change detection. In an application of landslide monitoring, we demonstrated the use of subpixel change detection for detection of landslide spreading. We used spectral unmixing algorithms to extract the abundance information from multispectral images. For the particular characteristic of landslides, we incorporated the slope feature into process. Our preliminary result shows that the subpixel change detection method can provide more detailed information about landslide spread than pixel-based change detection algorithms.