Change detection with 1 m resolution satellite and aerial images

We propose an optimization of a computer based change detection technique based on Iterative Principal Component Analysis (IPCA). We determine and evaluate the changes between an airborne and a spaceborne multispectral image data set, the latter recorded by the commercial satellite IKONOS-2. The change detection algorithm proved to be applicable to large remotely sensed data sets. A vegetation filter, a shadow filter and an oversaturation filter improved the accuracy of the results. When applying all filters more than 80 percent of the objects with changes due to construction activity are detected by the IPCA algorithm. The false alarm rate (change of an object indicated but not verified) is about 5 percent