This paper focuses on finding changes in an urban environment (new or demolished buildings, activity monitoring) using Synthetic Aperture Radar (SAR) imagery. We propose a novel approach to characterize changes between two registered images. First, “what is a change” is learned interactively using user-provided examples in order to adapt the detection to the query context. Second, we propose the Change-Index Histogram of Oriented Gradients (CI-HOG), a new change descriptor that captures local statistics of change indices. We assess our system on TerraSAR-X data captured over challenging locations.