Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 25, issue 9
Articles | Volume 25, issue 9
https://doi.org/10.5194/nhess-25-3525-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-25-3525-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 9
Research article
 | 
23 Sep 2025
Research article |  | 23 Sep 2025

Automated urban flood level detection based on flooded bus dataset using YOLOv8

Yanbin Qiu, Xudong Zhou, Jiaquan Wan, Tao Yang, Lvfei Zhang, Yuanzhuo Zhong, Leqi Shen, and Xinwu Ji

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Short summary
Floods pose a significant risk to cities, so fast and accurate information is essential for disaster management. This study used social media images to assess flood levels by analyzing submerged buses, a reliable reference object. An advanced AI model (YOLOv8) trained on different datasets achieved high flood detection accuracy. The results provide a scalable solution for real-time flood monitoring, enhancing urban transportation safety, and supporting emergency planning.
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