Home   For the Media   Contact Us
Click here to learn more about ASBPA memberships.
Support ASBPA- Become a member!
ASBPAASBPAASBPAASBPA
  • About Us
    • Mission
    • Chapters
      • California Shore & Beach Preservation Association
      • Central Gulf Coast Chapter, ASBPA
      • Great Lakes Shore & Beach Preservation Association
      • Hawaii Shore and Beach Preservation Association
      • Mid-Atlantic Chapter, ASBPA
      • Northeast Shore and Beach Preservation Association
      • Students & New Professionals
      • Texas Chapter of ASBPA
    • Leadership
    • Awards Programs
    • Partners
    • Committees
    • Support Us
  • Conferences
    • Upcoming Conference
    • Future Meetings
    • Past Meetings
  • Resources
    • Shore & Beach Journal
    • Coastal Voice E-Newsletter
    • American Beach News Service
    • White Papers/Fact Sheets
    • Coastal Universities Guide
    • National Beach Nourishment Database
    • ASBPA/CSO/USACE Sediment Placement Regulations Project
    • Southeast Coastal Communities Water Level Observation System
  • Members
    • Join or Renew
    • Our Members
  • Get Involved
    • Science and Technology
    • Policy
    • Funding
    • Committees
    • Support Us
    • Blue Flag USA

Rip current and channel detection using surfcams and optical flow

Cover of Vol. 90 No. 1 Butterflies on beachSean P. McGill and Jean T. Ellis, 2022. “Rip current and channel detection using surfcams and optical flow”, Shore & Beach, 90(1), 50-58.

Access Shore & Beach Vol. 90, No. 1

ASBPA members have access to a full digital edition of Shore & Beach. Become a member now to get immediate access.

http://doi.org/10.34237/1009015

Rip current and channel detection using surfcams and optical flow
Sean P. McGill(1) and Jean T. Ellis(2)
1) Department of Geography, University of South Carolina, Columbia, SC 29208
sean.p.mcgill@usace.army.mil
Currently at: U.S. Army Engineer Research and Development Center,
Coastal and Hydraulics Laboratory, Vicksburg, MS 39183
2) Department of Geography, University of South Carolina, Columbia, SC 29208
jellis@seoe.sc.edu (corresponding author)

Rip currents are a common, naturally occurring surf-zone hazard that pose a risk to beach patrons. This study presents a remote-sensing-based algorithm to detect rip currents and rip channels. Optical flow-based computer vision methods are implemented to analyze large data sets and the automatic detection of these features. Surfcam video was collected from dissipative (La Jolla, CA), intermediate (Long Beach, NY), and reflective beaches (Pensacola Beach, FL) to demonstrate the efficacy of the methods. A clustering technique using the dominant wave period was implemented to transition from detected offshore movements to rip currents. The methods presented in this paper were used to detect 20,327 rip currents and 1,100 rip channels. The average accuracy for rip current and rip channel detection was 67.3% and 96.2%, respectively. The remote-sensing-based detection methods can be adapted for use on other video-based equipment and, with additional modifications, can be implemented in an operational capacity.

BECOME A MEMBER!

Please consider joining the ASBPA.

CLICK TO LEARN MORE

 

QUICK LINKS

News

Next Conference

Members

About Us

Back to Top

CONTACT US

General Inquiries

For the Media

Facebook
Twitter
Instagram
Copyright ASBPA 2022 | Privacy Policy | Terms & Conditions View our latest 990