In Image fusion the objective is generally to combine the spatial structure of a high resolution panchromatic image with the spectral information of a low resolution multispectral image to produce a high resolution multispectral image. The fused image should preserve the spectral characteristics of the multispectral image during the process and only the spatial structure of the panchromatic image should be inserted into the fused image. As a substitute for the panchromatic input we used image data of the German Radar satellite TerraSAR-X in this study. In the spotlight mode, the satellite is able to record data with one meter spatial resolution. The Radar image data was combined with SPOT multispectral data in a region in northern Spain. In this study we investigated if such an image fusion method could improve the results of a multispectral classification using unfiltered Radar image data as input for classification. Usually this would lead to worse classification results, because of its inherent speckle noise. This is especially true if the multispectral and the Radar image are from different dates. Therefore, only the highpass filtered information of the TerraSAR-X image is used during the fusion process. Use was made of the Ehlers Fusion, a fusion technique that was developed for preserving maximum spectral information. It has already proven its superiority over standard pansharpening techniques such as IHS, PC, Brovey, multiplicative fusion and Wavelet fusion methods. The Ehlers fusion is based on an IHS transformation combined with filtering in the Fourier domain and was developed for fusing panchromatic and multispectral electro-optical data. The Ehlers Fusion was then modified to integrate Radar data with optical data. Different classification algorithms were applied to show that the pansharpening method could improve the results, but this depends on the chosen classification algorithm.