Earth Sciences

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

X. Yu, X. Hu, et al.

Discover how a groundbreaking multi-class damage detection model using AI is revolutionizing building damage analysis in the wake of the devastating 2023 Turkey-Syria earthquake. Developed by a team of researchers including Xiao Yu, Xie Hu, and others, this innovative approach leverages remote sensing data to enhance assessment accuracy and improve disaster response efforts.

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Abstract

The 2023 Turkey-Syria earthquake caused significant damage. This paper proposes a multi-class damage detection (MCDD) model using AI to analyze building damage from various remote sensing data (SAR, optical images, and PGA). The MCDD model integrates amplitude dispersion index (ADI), damage proxy (DP), normalized difference built-up index (NDBI), and peak ground acceleration (PGA) to classify damage levels. This approach improved damage assessment accuracy compared to traditional methods, aiding disaster response prioritization.

Publisher

npj Natural Hazards

Published On

Mar 15, 2024

Authors

Xiao Yu, Xie Hu, Yuqi Song, Susu Xu, Xuechun Li, Xiaodong Song, Xuanmei Fan, Fang Wang

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