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1 May 2016 Evaluation of Opportunistic Shoreline Monitoring Capability Utilizing Existing “Surfcam” Infrastructure
Melissa A. Bracs, Ian L. Turner, Kristen D. Splinter, Andrew D. Short, Chris Lane, Mark A. Davidson, Ian D. Goodwin, Tim Pritchard, Daylan Cameron
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Abstract

Bracs, M.A.; Turner, I.L.; Splinter, K.D.; Short, A.D.; Lane, C.; Davidson, M.A.; Goodwin, I.D.; Pritchard, T., and Cameron, D., 2016. Evaluation of opportunistic shoreline monitoring capability utilizing existing “surfcam” infrastructure.

This paper investigates the opportunistic repurposing of existing low-elevation recreational surf cameras (“surfcams”) to provide quantitative shoreline position data. Shoreline data are of fundamental importance in coastal management; however, intensive effort is required to routinely sample this dynamic environmental parameter. Established (and generally research-oriented) coastal imaging systems provide shoreline data in higher temporal resolution across broader spatial scales than is achievable by traditional survey techniques. The key benefits of adopting surfcams for shoreline monitoring are the wide availability of existing stations and their relatively low cost. In addition to the known challenges of optical remote sensing, there are further constraints associated with the typically low elevations of surfcams (9 to 22 m in this study) and the common use of dynamic pan-tilt-zoom positioning. This study used surfcams at nine diverse sites along the SE Australian coastline. Surfcam-derived shorelines were evaluated against monthly real time kinematic global navigation satellite system (RTK-GNSS) surveys. Standard deviations (SDs) of error of 4 to 14 m (horizontal) were observed in data provided by the commercial surfcam operator. After consideration of image geometry, camera stability, shoreline visibility, and shoreline elevation, SDs of error within 1 to 4 m were achieved. At one site, daily surfcam-derived shorelines were evaluated against video-derived shorelines obtained by a state-of-the-art Argus coastal imaging system. Data provided by the surfcam operator had a SD of error of 6 m (horizontal) when compared to the Argus-derived shoreline dataset, and improved methodology reduced this to below 2 m. Generic methods for identifying and addressing issues resulting from surfcam movement and low viewing angle of the beach are presented, as well as data processing options and recommendations for the potential wider adoption of this largely untapped coastal monitoring resource.

Melissa A. Bracs, Ian L. Turner, Kristen D. Splinter, Andrew D. Short, Chris Lane, Mark A. Davidson, Ian D. Goodwin, Tim Pritchard, and Daylan Cameron "Evaluation of Opportunistic Shoreline Monitoring Capability Utilizing Existing “Surfcam” Infrastructure," Journal of Coastal Research 32(3), 542-554, (1 May 2016). https://doi.org/10.2112/JCOASTRES-D-14-00090.1
Received: 7 May 2014; Accepted: 29 December 2014; Published: 1 May 2016
KEYWORDS
beach monitoring
coastal imaging
coastal management
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