Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 17, issue 10
Articles | Volume 17, issue 10
https://doi.org/10.5194/essd-17-5259-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-17-5259-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 10
Data description paper
 | 
10 Oct 2025
Data description paper |  | 10 Oct 2025

The 2024 Noto Peninsula earthquake building damage dataset: multi-source visual assessment

Ruben Vescovo, Bruno Adriano, Sesa Wiguna, Chia Yee Ho, Jorge Morales, Xuanyan Dong, Shin Ishii, Kazuki Wako, Yudai Ezaki, Ayumu Mizutani, Erick Mas, Satoshi Tanaka, and Shunichi Koshimura

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Short summary
We compiled an inventory of building condition (destroyed vs. survived) following the 2024 Noto Peninsula earthquake for the entire affected area, totaling over 140 000 structures. We discuss how we fused freely available data of different types and from different sources to generate the final dataset. We show that our method produces highly accurate results relative to those obtained by on-site surveys. These data can be used to train AI to quickly detect damaged structures in future disasters.
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