Various methods for automatic change detection in multi-temporal LANDSAT-TM images are described. In contrast to most previous work in change detection, which has operated at a pixel level, we operate at a parcel level (within a minimum size of 25 Ha). This makes it easier to employ structural measures (e.g. based on edges, corners, and texture) as well as correlation methods since these approaches cannot be calculated at each pixel independently. A neural network is trained to combine the different change measures in an appropriate manner.