Argus video monitoring system

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This article provides an introduces the video monitoring ARGUS. The article explains why ARGUS has been developed, where it is used and how it works. Also a literature list is provided with all relevant literature about ARGUS.


Figure 1 Argus video cameras in Noordwijk aan Zee, The Netherlands

Until only a few years ago, all information on nearshore morphodynamics had to be gathered from comprehensive field experience. This way of data collection has some fundamental limitations. One problem is the fact that such experiments are relatively expensive and that there is only a limited amount of instrument positions in traditional field experiments. A synoptical pattern is thus difficult to get with the use of a traditional field set up, but this can easily be measured with a shore-based video system. Another and even more important characteristic is the fact that the observation time scale is in practice limited to several weeks. Finally, surveying during severe weather and wave conditions is hardly possible. With the recent advent of new digital imaging technology, shore-based video systems now provide the additional capability of automated data collection, encompassing a much greater range of time and spatial scales than were previously possible.

History and use of ARGUS

The history behind video imaging in nearshore studies probably goes back to the 1930s, where the first attempts to study coastal processes were made with the help of aerial photography. In 1980, developments on video techniques for the monitoring of coastal changes have been initiated by the Coastal Imaging Lab of the Oregon State University, USA. Being continuously improved since 1992, the so-called Argus system nowadays features fully digital video technology which provides high image quality in combination with detailed pixel resolution. Continuous (typically every daylight hour) collection of image data with a resolution of centimetres to meters, extending along regions of hundreds of meters to several kilometres, is now routinely undertaken at sites in the USA, Europe, Australia and Asia.

Since the first automated Argus station was installed at Agate Beach on the Oregon Coast in 1992, the CIL-based program has expanded to 12 locations around the world. Sites were selected to span the parameter space considered relevant to nearshore processes research (ranges in wave period, wave height, tide range and beach slope).

In addition, approximately 30 Argus stations and 120 cameras are now operating daily in 8 countries (see also Figure 2). The greatest acceptance has been in Europe, where Argus technologies are at the heart of the three-year EU CoastView program, and in Australia, where 10 stations are now operating. These stations provide hourly measurements of a variety of topographic, geomorphic and fluid variables and are usually focused on practical Coastal Zone Management (CZM) issues.

Figure 2 Locations of Argus stations over the world

Monitoring process

An Argus monitoring system typically consists of four to five video cameras, spanning a 180º view, and allowing full coverage of about four to six kilometres of beach. The cameras are mounted on a high location along the coast and connected to an ordinary PC on site, which in turn communicates to the outside world using conventional techniques such as an analogue modems, ISDN, DSL, or a wireless LAN. Data sampling is usually hourly (although any schedule can be specified) and continues during rough weather conditions. As the process of data collection is fully automated, the marginal operating costs are virtually zero.

Each standard hourly collection usually consists of three types of images (Argus image types and conventions). A snapshot image serves as simple documentation of the ambient conditions but offers little quantitative information. Time exposure images average out natural modulations in wave breaking to reveal a smooth pattern of bright image intensities, which are an excellent proxy for the underlying, submerged sand bar topography. Time exposures also ‘remove’ moving objects from the camera field of view, such as ships, vehicles and people. Variance images help identify regions which are changing in time (like the sea surface), from those which may be bright, but are unchanging (like the dry beach).

Plan view, merged images (Argus standard image processing) can be composed by geo-referencing the images from all the cameras of an Argus station. This facilitates the measurement of length scales of morphological features like breaker bars and the detection of rip currents. Besides time-averaged video data, data sampling schemes can be designed to collect time series of pixel intensities, typically at 2 Hz, with which wave and flow characteristics can be investigated.

Argus tools

After collection of different Argus image types (see also Argus image types and conventions), the collected video data can be analysed using the standard Argus analysis software or through dedicated image analysis. At present, ten tools are part of the standard Argus analysis software suite. These are summarised in Table 1:

Table 1 Overview of standard Argus Analysis Tools

An eleventh application named argusDesignTool (ADT), that can be applied to design the camera configuration of new Argus stations, is meant for specialized use only.

See also

Internal links

External links

Further reading

  • Aarninkhof, S.G.J. (2003). Nearshore bathymetry derived from video imagery. PhD. Thesis, Delft University of Technology, 175 pp
  • Aarninkhof, S.G.J. and Holman, R.A. (1999). Monitoring the nearshore with video. Backscatter, 10(2), pp. 8-11.
  • Aarninkhof, S.G.J., Turner, I.L., Dronkers, T.D.T., Caljouw, M. and Nipius, L. (2003). A video-technique for mapping intertidal beach bathymetry. Coastal Engineering 49, pp. 275-289
  • Chickadel, C.C., R.A. Holman, and M. Freilich (2003). An optical technique for the measurement of longshore currents. Journal of Geophysical Research, 108 (C11), 3364, doi: 10.1029/2003JC001774, 2003.
  • Cohen, A.B., A.R. van Dongeren, J.A. Roelvink, N.G. Plant, S.G.J. Aarninkhof, M.C. Haller and P. Catalan (2007). Nowcasting of coastal processes through assimilation of model computations and remote observations. Proceedings of the 30st ICCE, ASCE, San Diego.
  • Cohen, A.B., Aarninkhof, S.G.J. and Chicadel, C.C. (2004). Video-derived observations of alongshore currents. Proceedings of the 29th ICCE, ASCE, Lisbon.
  • Davidson, M., Van Koningsveld, M., De Kruif, A., Rawson, J., Holman, R., Lamberti, A., Medina, R., Kroon, A., Aarninkhof, S. (2007). The CoastView project: Developing video-derived Coastal State Indicators in support of coastal zone management. Coastal Engineering 54, 463-475.
  • Enckevort, I.M.J. Van and Ruessink, B.G. (2001). Effect of hydrodynamics and bathymetry on video estimates of nearshore sandbar position. Journal of Geophysical Research, 106(C8): 16969-16980, 2001.
  • Holland, K.T. and Holman, R.A. (1993). The statistical distribution of swash maxima on natural beaches. Journal of Geophysical Research, 98, pp. 10271-10278.
  • Holland, K.T., Holman R.A., Lippmann T.C., Stanley J.and Plant N.G. (1997). Practical use of video imagery in nearshore oceanographic field studies. IEEE Journal of oceanic engineering, Vol. 22, No. 1.
  • Holman, R.A. (1981). Infragravity energy in the surf zone, Journal of Geophysical Research, 86(C7), 6442-6450, 1981.
  • Holman, R and Chickadel C., (2004). Optical remote sensing estimates of the incident wave angle field during NCEX. Proceedings of the 29th ICCE, ASCE, Lisbon.
  • Holman, R.A., Sallenger Jr, A.H., Lippmann, T.C. and Haines, J.W. (1993). The application of video image processing to the study of nearshore processes. Oceanography, Vol. 6, No 3.
  • Holman, R.A., Stanley, J. (2007). The history and technical capabilities of Argus. Coastal Engineering 54, 477-491.
  • Jiménez, J.A., Osorio, A., Marino-Tapia, I., Davidson, M., Medina, R., Kroon, A., Archetti, R., Ciavola, P., Aarninkhof, S.G.J. (2007). Beach recreation planning using video-derived coastal state indicators. Coastal Engineering 54, 507-521.
  • Kroon, A., Davidson, M.A., Aarninkhof, S.G.J., Archetti, R., Armaroli, C., Gonzalez, M., Medri, S., Osorio, A., Aagaard, T., Holman, R.A., Spanhoff (2007). Application of remote sensing video systems to coastline management problems. Coastal Engineering 54, 493-505.
  • Lippmann, T.C. and Holman R.A. (1989). Quantification of sand bar morphology: A video technique based on wave dissipation. Journal of Geophysical Research, 94 (C1), 995-1011, 1989.
  • Lippmann, T.C. and Holman R.A. (1990). The spatial and temporal variability of sand bar morphology, Journal of Geophysical Research, 95 (C7), 11,575-11,590, 1990.
  • Medina, R., Marino-Tapia, I., Osorio, A., Davidson, M., Martin, F.L. (2007). Management of dynamic navigational channels using video techniques. Coastal Engineering 54, 523-537.
  • Plant, N.G., Holland, K.T. and Puleo, J.A. (2002). Analysis of the scale of errors in nearshore bathymetric data. Marine Geology 191, pp. 71-86.
  • Smit, M.W.J., Aarninkhof, S.G.J., Wijnberg, K.M., González, M., Kingston, K.S., Southgate, H.N., Ruessink, B.G., Holman, R.A., Siegle, E., Davidson, M., Medina, R. (2007). The role of video imagery in predicting daily to monthly coastal evolution. Coastal Engineering 54, 539-553.
  • Stockdon, H. F. and Holman, R. A. (2000). Estimation of wave phase speed and nearshore bathymetry from video imagery. Journal of Geophysical Research, 105(C9): 22015-22034, 10. 1029/1999JC000124, 2000.
  • Turner, I.L., Anderson, D.J. (2007). Web-based and *real-time* beach management system. Coastal Engineering 54, 555-565.
  • Van Koningsveld, M., Davidson, M., Huntley, D., Medina, R., Aarninkhof, S., Jiménez, J.A., Ridgewell, J., De Kruif, A. (2007). A critical review of the CoastView project: Recent and future developments in coastal management video systems. Coastal Engineering 54, 567-576.
  • Wijnberg, K.M.., Aarninkhof, S.G.J., Van Koningsveld, M., Ruessink, B.G. and Stive, M.J.F. (2004). Video monitoring in support of coastal management. Proceedings of the 29th ICCE, ASCE, Lisbon.
The main author of this article is Cohen, Anna
Please note that others may also have edited the contents of this article.

Citation: Cohen, Anna (2007): Argus video monitoring system. Available from [accessed on 25-05-2020]