A natural system such a coastal zone is subject to the vagaries of natural conditional variation. Within in a matter of weeks to months beach nourishment adopts an equilibrium profile through phases that may be both unexpected and pose temporary problems. Rip currents may even develop within days, forming a serious threat to swimmer safety. Effective decision making and engineering design in this complex field thus demands the availability of detailed coastal-state information at small scales of days to weeks and metres to kilometres.
With the advent of digital imaging technology, shore-based remote video techniques like the advanced Argus system developed at Oregon State University (USA) are increasingly being used to monitor coastal processes in support of coastal management and engineering. Unmanned, automated video stations (Figure 1) guarantee the collection of video data at spatio-temporal scales of decimetres to kilometres and hours to years. Under continual improvement since 1992, the system now features fully digital video technology that provides high-quality imagery.
An Argus monitoring system typically consists of four to five video cameras spanning a 180º view and allowing full coverage of about three to six kilometres of beach. The cameras are mounted at a high-lying location along the coast and connected to an ordinary PC onsite that in turn communicates with the outside world using broadband internet. 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, marginal operating costs are virtually none. For full flexibility, a self-contained system has been developed with a low-power computer embedded in the camera housing.

Data Collection
Each standard hourly collection usually consists of three types of images. A snapshot image (Figure 2a) serves as simple documentation of ambient conditions but offers little quantitative information. Time-exposure images (Figure 2b) 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 such as ships, vehicles and people from the camera field of view. Variance images (Figure 2c) help identify regions changing in time, like the sea surface, from those which may be bright but are unchanging, like the dry beach. Panoramic (Figure 2d) and plan-view (Figure 2e) merged images can be composed by geo-referencing the images from all Argus station cameras. Plan-view images enable 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 2Hz, with which wave and flow characteristics can be investigated.

Video Coastal State
Successful use of video-monitoring techniques in support of coastal management and engineering involves quantification of relevant coastal-state information from video data. Sophisticated operational video-analysis methods nowadays enable:

• quantification of shoreline evolution and beach width to evaluate potential for recreation or to assess morphological impact of a storm (cf. Application 1)
  
• quantification of erosion and accretion sediment volumes at an inter-tidal beach, for example to evaluate morphological impact of coastal structures, to investigate seasonal fluctuations in beach dynamics and beach nourishment or to study the behaviour of morphological features such as sand-spits and tidal-flats near a harbour entrance (cf Application 2)
  
• quantification of sub-tidal beach bathymetry to evaluate coastal safety, assess behaviour and performance of shore-face nourishment or even to facilitate military operations (cf. Application 3)
  
• quantification of wave run-up to evaluate stability of coastal structures such as seawalls, harbour moles and revetments (cf. Application 4).

• Aarninkhof, S.G.J., Ruessink, B.G. and Roelvink, J.A., 2005. Nearshore subtidal bathymetry from time-exposure video images. Journal of Geophysical Research, Vol. 110, C06011, doi:10.1029/2004JC002791, 2005.
  
• 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.
  
• Holman, R.A. and Stanley, J. (in press). The history, capabilities and future of Argus. Accepted for publication in Coastal Engineering.
  
• Turner, I.L., Aarninkhof, S.G.J. and Holman, R.A., 2006. Coastal imaging applications and research in Australia. Journal of Coastal Research, pp 37-48, doi:10.2112/05A-0004.1.