Abstract: A critical factor when undertaking proper coastline management is the availability of reliable data, allowing those responsible to make informed decisions about land use and its impact on natural resources. Marine resource data (bathymetry, time-series of waves, coastal use levels, etc.) have often been difficult for policy-makers to obtain and use, given the high costs involved and difficulties in their application and interpretation. In cases where a source of coastline data is available, it is important that it be sufficiently complete to compare habitat changes (in morphology and use) that are only observable over a period of years. Thus, it is necessary to look for alternative methods to obtain this long-term information. The availability of new data-gathering techniques for the study of coastlines and coastal processes, such as remote sensors and underwater photography and videography, has increased during the last decade. One of the principal research applications of these techniques is bathymetry. This paper presents state-of-the-art image-based models that allow the construction of topo-bathymetric shore data. The Physical and Statistical Detection Model (PSDM), which constitutes the core of this research, is discussed and validated. The PSDM is based on a combination of six different algorithms that describe the shoreline features, and it assigns physical and statistical criteria to the detection process. In conclusion, a numerical tool based on video systems is introduced which shows great potential for monitoring coastal issues and supplying data to aid technicians and shoreline managers.

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