Articles | Volume 386
https://doi.org/10.5194/piahs-386-203-2024
https://doi.org/10.5194/piahs-386-203-2024
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

Viewed

Total article views: 242 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
178 53 11 242 12 8
  • HTML: 178
  • PDF: 53
  • XML: 11
  • Total: 242
  • BibTeX: 12
  • EndNote: 8
Views and downloads (calculated since 19 Apr 2024)
Cumulative views and downloads (calculated since 19 Apr 2024)

Viewed (geographical distribution)

Total article views: 221 (including HTML, PDF, and XML) Thereof 221 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 02 Nov 2024
Download
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.