Articles | Volume 27, issue 22
https://doi.org/10.5194/hess-27-4135-2023
https://doi.org/10.5194/hess-27-4135-2023
Research article
 | 
15 Nov 2023
Research article |  | 15 Nov 2023

Eye of Horus: a vision-based framework for real-time water level measurement

Seyed Mohammad Hassan Erfani, Corinne Smith, Zhenyao Wu, Elyas Asadi Shamsabadi, Farboud Khatami, Austin R. J. Downey, Jasim Imran, and Erfan Goharian

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Short summary
Predicting flood magnitude and location helps decision-makers to better prepare for flood events. To increase the speed and availability of data during flooding, this study presents a vision-based framework for measuring water levels and detecting floods. The deep learning models use time-lapse images captured by surveillance cameras to detect water extent using semantic segmentation and to transform them into water level values with the help of lidar data.