Thematic mapping from multitemporal image data using the principal components transformation

Abstract The principal components transformation is used to highlight regions of localized change evident in satellite multispectral imagery associated with bushfire damage and with vegetation regrowth following fire burns. In line with previous studies by other investigators it is the higher order components that are seen to lead to change enhancement. These components are classified by unsupervised techniques to yield thematic maps on which change classes are recorded. In this manner, confusion of class signatures between dynamic and static cover types is avoided. In the present case this relates to confusion between fire burn regions and water edge mixed pixels.