Evaluation of Opportunistic Shoreline Monitoring Capability Utilizing Existing “Surfcam” Infrastructure

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.

[1]  M. Crowell,et al.  Long-term Shoreline Position Prediction and Error Propagation , 2000 .

[2]  J. Peck,et al.  Long-Term Beach Profile Variations Along the South Shore of Rhode Island, U.S.A. , 1998 .

[3]  Andrew D. Short,et al.  Short-term changes in the morphodynamic states of beaches and surf zones: An empirical predictive model☆ , 1985 .

[4]  M. Fenster,et al.  Temporal analysis of shoreline recession and accretion , 1991 .

[5]  Massimo Brignone,et al.  A system for beach video-monitoring: Beachkeeper plus , 2012, Comput. Geosci..

[6]  Ian L. Turner,et al.  Coastal Imaging Applications and Research in Australia , 2006 .

[7]  Michael Blumenstein,et al.  The Detection of Persons in Cluttered Beach Scenes Using Digital Video Imagery and Neural Network-Based Classification , 2006, Int. J. Comput. Intell. Appl..

[8]  Hants Gu,et al.  Beach topography mapping - a comparison of techniques , 2000 .

[9]  Nathaniel G. Plant,et al.  Practical use of video imagery in nearshore oceanographic field studies , 1997 .

[10]  Mitchell D. Harley,et al.  Assessment and integration of conventional, RTK-GPS and image-derived beach survey methods for daily , 2011 .

[11]  Ian L Turner,et al.  The Performance of Shoreline Detection Models Applied to Video Imagery , 2007 .

[12]  Kristen D. Splinter,et al.  How much data is enough? The importance of morphological sampling interval and duration for calibration of empirical shoreline models , 2013 .

[13]  Amy S. Farris,et al.  Large-Scale Shoreline Response to Storms and Fair Weather , 1999 .

[14]  Nicholas C. Kraus,et al.  Temporal and spatial scales of beach profile change, Duck, North Carolina , 1994 .

[15]  Alexandre Bernardino,et al.  Auto-Calibration of Pan-Tilt Cameras Including Radial Distortion and Zoom , 2012, ISVC.

[16]  B. Zanuttigh,et al.  Integrated monitoring of the hydro-morphodynamics of a beach protected by low crested detached breakwaters , 2010 .

[17]  R. Guza,et al.  Overview of seasonal sand level changes on southern California beaches , 2009 .

[18]  R. Morton,et al.  Meso-scale transfer of sand during and after storms: implications for prediction of shoreline movement , 1995 .

[19]  Charles H. Fletcher,et al.  Modeling storms improves estimates of long-term shoreline change , 2009 .

[20]  BEACH EVOLUTION ON THE SOUTHERN NORTH SEA COAST , 1999 .

[21]  Luca Lucchese,et al.  Geometric calibration of digital cameras through multi-view rectification , 2005, Image Vis. Comput..

[22]  Robert A. Holman,et al.  Quantification of sand bar morphology: A video technique based on wave dissipation , 1989 .

[23]  Rodger Benson Tomlinson,et al.  Assessment of Coastal Hazards - CoastSAFE Alive Australia , 2009 .

[24]  Shoreline rotation and response to nourishment of a gravel embayed beach using a low-cost video monitoring technique: San Michele-Sassi Neri, Central Italy , 2014, Journal of Coastal Conservation.

[25]  Takayuki Suzuki,et al.  Linkages among interannual variations of shoreline, wave and climate at Hasaki, Japan , 2012 .

[26]  Chris Rizos,et al.  Resolution and Accuracy of an Airborne Scanning Laser System for Beach Surveys , 2013, Journal of Atmospheric and Oceanic Technology.

[27]  D. Mason,et al.  Beach topography mapping—a comparsion of techniques , 2000 .

[28]  Kristen D. Splinter,et al.  Capitalizing on the surfcam phenomenon: a pilot study in regional-scale shoreline and inshore wave monitoring utilizing existing camera infrastructure , 2013 .

[29]  M. Vousdoukas,et al.  Performance of intertidal topography video monitoring of a meso-tidal reflective beach in South Portugal , 2011 .

[30]  R. Holman,et al.  The history and technical capabilities of Argus , 2007 .

[31]  D. Basco,et al.  Managing coastal erosion , 1992 .

[32]  John Stanley,et al.  Applying Video Sensor Networks to Nearshore Environment Monitoring , 2003, IEEE Pervasive Comput..

[33]  G. Różyński.  Long-term shoreline response of a nontidal, barred coast , 2005 .

[34]  Salvador Balle,et al.  An open source, low cost video‐based coastal monitoring system , 2010 .

[35]  Raúl Medina,et al.  The CoastView project: Developing video-derived Coastal State Indicators in support of coastal zone management , 2007 .

[36]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[37]  Kathelijne Mariken Wijnberg,et al.  Extracting decadal morphological behaviour from high-resolution, long-term bathymetric surveys along the Holland coast using eigenfunction analysis , 1995 .

[38]  K. Bryan,et al.  Monitoring Beach Face Volume with a Combination of Intermittent Profiling and Video Imagery , 2007 .

[39]  Nathaniel S. Pearre,et al.  Quantifying Seasonal Shoreline Variability at Rehoboth Beach, Delaware, Using Automated Imaging Techniques , 2009 .

[40]  R. Holman,et al.  Application of remote sensing video systems to coastline management problems , 2007 .

[41]  Ian L Turner,et al.  A video-based technique for mapping intertidal beach bathymetry , 2003 .

[42]  R. Holman,et al.  Evaluation of Airborne Topographic Lidar* for Quantifying Beach Changes , 2003 .

[43]  Ian L Turner,et al.  Shoreline Definition and Detection: A Review , 2005 .

[44]  Kristen D. Splinter,et al.  Assessment of Post-Storm Recovery of Beaches Using Video Imaging Techniques: A Case Study at Gold Coast, Australia , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Patrick L. Barnard,et al.  Beach response dynamics of a littoral cell using a 17-year single-point time series of sand thickness , 2012 .

[46]  R. Holman,et al.  Estimation of Shoreline Position and Change using Airborne Topographic Lidar Data , 2002 .

[47]  Jin-Soo Kim,et al.  Accuracy evaluation of a smartphone-based technology for coastal monitoring , 2013 .

[48]  Ana Silva,et al.  COSMOS: A lightweight coastal video monitoring system , 2012, Comput. Geosci..

[49]  Michele Capobianco,et al.  Variability of shore and shoreline evolution , 2002 .

[50]  D. J. Clarke,et al.  Mean sea-level and beach-width variation at Scarborough, Western Australia , 1983 .