When to fuse what? random forest based fusion of low-, mid-, and high-level information for land cover classification from optical and SAR images

With increasing availability of different sensors for earth observation, data fusion gained more and more importance. While previous publications focussed on new sensor combinations, new fusion techniques, or new applications, this work investigates at which stage of the image analysis pipeline the fusion process is most beneficial. The fusion of an optical and a SAR image for the task of land cover classification serves as an example. The experimental results indicate, that although the fusion of complementary data is generally advantageous, it is most helpful at later stages of the classification process.