Articles | Volume 19, issue 11
Brief communication
19 Nov 2019
Brief communication |  | 19 Nov 2019

Machine learning analysis of lifeguard flag decisions and recorded rescues

Chris Houser, Jacob Lehner, Nathan Cherry, and Phil Wernette


Total article views: 1,802 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,205 529 68 1,802 64 59
  • HTML: 1,205
  • PDF: 529
  • XML: 68
  • Total: 1,802
  • BibTeX: 64
  • EndNote: 59
Views and downloads (calculated since 18 Jun 2019)
Cumulative views and downloads (calculated since 18 Jun 2019)

Viewed (geographical distribution)

Total article views: 1,802 (including HTML, PDF, and XML) Thereof 1,581 with geography defined and 221 with unknown origin.
Country # Views %
  • 1


Latest update: 28 Nov 2023
Short summary
On many beaches, lifeguards set out flags to warn beach users of the surf and rip hazard based on the regional surf forecast and careful observation. There is a potential that the chosen flag does not accurately reflect the potential risk. Results of a machine learning analysis suggest that the greatest number of rescues occurred on days when the lifeguard flew a more cautious flag than the model predicted. It is argued that that beach users may be discounting lifeguard warnings.
Final-revised paper