Automatic Change Detection for Validation of Digital Map Databases

In almost all areas of our society there is an increasing need for up to date digital map databases. Traditionally, different manual, labour intensive and hence costly methods have been used for map updating, with the change detection for the updating being by far the most complex and expensive part. In this paper an automatic change detection method is presented and evaluated. The method only considers changes in the buildings theme, but it can be extended to other object classes. The aim is the development of an efficient change detection procedure for database maintenance in a production environment. The method is based on classification principles and combines an unsupervised and a supervised classification in order to determine the spectral response of the building class and thus locate potential buildings. The result is filtered by a height filter to refine the result. The method is evaluated on building registrations from the Danish TOP10DK map database. The test case presented in the paper is from a residential suburban area. The method detects almost all changes due to demolished buildings whereas only a smaller part of the new buildings are detected. This is primarily due to the use of a very special roofing material. The method leads to a number of false alarms, which to a large degree can be eliminated by refinements of the algorithm or by introduction of additional information e.g. infra-red images or texture measures.