Tomographic synthetic aperture radar (TomoSAR) can broaden the scope of change detection applications for urban studies, human activity and forest monitoring. In this work we design and evaluate a method utilizing SAR tomography for change detection purposes applied to human activity monitoring and urban studies. The method uses 2-D images to detect changes caused by targets with a small vertical extent, and 3-D images for changes caused by targets with a large vertical extent. It exploits both amplitude and height difference information combined in a conditional random field to detect changes of interest. A significant performance improvement was obtained when comparing to methods using 2-D or 3-D images only.