The current synthetic aperture radar (SAR) theory makes a quite restrictive assumption – linearity – in the SAR imaging model, for the convenience of mathematical derivation. That is to say the imaged area is considered as an ensemble of individual point scatterers whose scattered fields and, hence, their responses in the SAR image superimpose linearly [1]. This is the so called the first Born approximation. However, the reality is, for sure, more complicated than such approximation. This work presents a step towards a better understanding of the scattering mechanism of different objects, and the occurrence of single scatterer, as well as multiple scatterers within a resolution cell. We back trace individual SAR scatterer to high resolution optical images where we can analyze the geometry, material, and other properties of the imaged object. The proposed approach consists of the following steps: 1. Retrieve the 3D positions of the scatterers’ positions from SAR images, i.e. a tomographic SAR inversion. 2. Co-register the 3D point cloud of the SAR scatterers with a reference 3D model, due to the relative position of the SAR point cloud to the reference point. 3. Co-register high resolution optical image with the reference 3D model, so that each scatterer can be traced in the optical image. 4. Classify the optical image pixels based on its semantic meaning, e.g. geometry, material, and so on. 5. Analyze the semantic meaning of the scatterers, especially those multiple scatterers within the same resolution cell. Currently, this work is finished till step three. The algorithm for step four and five are under development. We will present the findings in final full paper.