Comparative Analysis of Detailed Features in 3D Models for SAR Simulation

The lack of pre-disaster data often poses challenges for reliable building damage predictions in disaster response using remote sensing. To address this limitation, we propose a framework that leverages Synthetic Aperture Radar (SAR) simulators to generate high-resolution simulated SAR images. Assessing the realism of these simulated images is crucial for their reliability in representing authentic SAR data. However, obtaining pre-disaster SAR images for city-scale areas can be challenging.In this study, we utilized Google 3D Tiles and Blender-GIS model to recreate scenes for simulating pre-disaster SAR images. We conducted a comprehensive analysis, evaluating the similarity between simulated and authentic SAR images through similarity assessments. Preliminary results suggest that the SAR simulator successfully produces distinct signatures for different 3D models in simulated SAR imagery. This approach holds promise for use in disaster response scenarios.