Initiated by Dr. Xin Wei, University of Michigan
Ongoing development by the community

Intelligent assessment of building damage of 2023 Turkey-Syria earthquake by multiple remote sensing approaches

Citation

Yu, X., Hu, X., Song, Y., Xu, S., Li, X., Song, X., Fan, X., Wang, F. (2024). Intelligent assessment of building damage of 2023 Turkey-Syria earthquake by multiple remote sensing approaches. npj Natural Hazards, 1(1): 3. Link to paper

Abstract

The devastating February 6, 2023 earthquake of magnitude 7.8 and its aftershocks in Turkey and Syria caused catastrophic destruction with more than 55,000 deaths and at least 230,000 buildings destroyed or damaged. Rapid assessment of building damage is critical for emergency response and recovery planning. This study presents a comprehensive framework for intelligent assessment of building damage using multiple remote sensing approaches. The methodology integrates various satellite imagery sources including optical and SAR data, combined with advanced machine learning and deep learning techniques to detect and classify building damage at multiple scales. The approach enables rapid, accurate, and scalable damage assessment across large affected areas, providing crucial information for disaster response teams and recovery planning. The framework demonstrates the power of integrating multiple remote sensing data sources and artificial intelligence techniques for post-disaster building damage assessment.