Proceedings of IAHS
Proceedings of IAHS
PIAHS
Articles | Volume 386
Articles | Volume 386
https://doi.org/10.5194/piahs-386-203-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-386-203-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 386
Post-conference publication
 | 
19 Apr 2024
Post-conference publication |  | 19 Apr 2024

Satellite and UAV derived seasonal vegetative roughness estimation for flood analysis

Andre Araujo Fortes, Masakazu Hashimoto, Keiko Udo, and Ken Ichikawa

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Short summary
This research was motivated by the necessity to achieve better efficiency of hydraulic models. By using an automated calculation routine for the roughness in the vegetated areas, we could produce results with higher precision, reducing the error when comparing to the traditional method of roughness setting. The research shows that, using machine learning, and remote sensing data, the necessary vegetation parameters can be obtained in a broad area, enabling the application of the method.
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