Semantic annotation of high resolution TerraSAR-X images using Information Mining

This paper addresses the problem of High Resolution Synthetic Aperture Radar (SAR) image semantic annotation using a Knowledge Based Information Mining (KIM) System. The authors propose the assessment of the capabilities of KIM to perform an automatic urban classification on TerraSAR-X data. Four test sites have been used in the experiment to prove that the system is generic and data independent. The performance is evaluated by matching the results with GeoEye optical representations of the selected areas. For the evaluation a number of three classes are presented and discussed (water bodies, green urban areas and tall buildings).