Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment

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Abstract

Synthetic aperture radar (SAR) imagery is indispensable for acquiring a comprehensive, large-scale topographical perspective of the Earth's surface, facilitating the evaluation of diverse scenarios spanning various events. However, integrating SAR imagery with ground truth data poses a formidable challenge, primarily due to the complex interactions of electromagnetic radar waves with the intricate features of the surface, characterized by multiple scatterings. This study seeks to bridge these disparities between authentic SAR and simulated by applying ray tracing SAR simulations within a meticulously controlled environment. Our investigation into SAR simulation focuses on evaluating the accuracy, precision, and reliability of theoretical models in representing surface features. Through ray tracing SAR simulations, we aim to understand better the complex interactions of electromagnetic radar waves with surface features, ultimately advancing our ability to interpret SAR imagery in diverse scenarios. The research findings indicate a robust correlation between the physical parameters of the surface and the backscattering levels observed in SAR simulations, underscoring the critical dependence of simulation accuracy on the granularity of the 3-D models employed. Moreover, this study delves into the consistency of modeling approaches in accurately replicating the assessment of building damage in postdisaster contexts, providing insights into the potential enhancements in disaster management and response strategies. The implications of these findings not only advance the understanding of SAR simulation fidelity but also pave the way for significant improvements in the application of SAR technology for disaster assessment and environmental monitoring.

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APA

Ho, C. Y., Mas, E., Adriano, B., & Koshimura, S. (2024). Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 1046–1059. https://doi.org/10.1109/JSTARS.2024.3418412

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