19 June 2015 Αutomated 2D shoreline detection from coastal video imagery: an example from the island of Crete
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Proceedings Volume 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015); 95351J (2015) https://doi.org/10.1117/12.2192687
Event: Third International Conference on Remote Sensing and Geoinformation of the Environment, 2015, Paphos, Cyprus
Abstract
Beaches are both sensitive and critical coastal system components as they: (i) are vulnerable to coastal erosion (due to e.g. wave regime changes and the short- and long-term sea level rise) and (ii) form valuable ecosystems and economic resources. In order to identify/understand the current and future beach morphodynamics, effective monitoring of the beach spatial characteristics (e.g. the shoreline position) at adequate spatio-temporal resolutions is required. In this contribution we present the results of a new, fully-automated detection method of the (2-D) shoreline positions using high resolution video imaging from a Greek island beach (Ammoudara, Crete). A fully-automated feature detection method was developed/used to monitor the shoreline position in geo-rectified coastal imagery obtained through a video system set to collect 10 min videos every daylight hour with a sampling rate of 5 Hz, from which snapshot, time-averaged (TIMEX) and variance images (SIGMA) were generated. The developed coastal feature detector is based on a very fast algorithm using a localised kernel that progressively grows along the SIGMA or TIMEX digital image, following the maximum backscatter intensity along the feature of interest; the detector results were found to compare very well with those obtained from a semi-automated ‘manual’ shoreline detection procedure. The automated procedure was tested on video imagery obtained from the eastern part of Ammoudara beach in two 5-day periods, a low wave energy period (6-10 April 2014) and a high wave energy period (1 -5 November 2014). The results showed that, during the high wave energy event, there have been much higher levels of shoreline variance which, however, appeared to be similarly unevenly distributed along the shoreline as that related to the low wave energy event, Shoreline variance ‘hot spots’ were found to be related to the presence/architecture of an offshore submerged shallow beachrock reef, found at a distance of 50-80 m from the shoreline. Hydrodynamic observations during the high wave energy period showed (a) that there is very significant wave energy attenuation by the offshore reef and (b) the generation of significant longshore and rip flows. The study results suggest that the developed methodology can provide a fast, powerful and efficient beach monitoring tool, particularly if combined with pertinent hydrodynamic observations.
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A. F. Velegrakis, A. F. Velegrakis, V. Trygonis, V. Trygonis, M. I. Vousdoukas, M. I. Vousdoukas, G. Ghionis, G. Ghionis, A. Chatzipavlis, A. Chatzipavlis, O. Andreadis, O. Andreadis, F. Psarros, F. Psarros, Th. Hasiotis, Th. Hasiotis, } "Αutomated 2D shoreline detection from coastal video imagery: an example from the island of Crete", Proc. SPIE 9535, Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), 95351J (19 June 2015); doi: 10.1117/12.2192687; https://doi.org/10.1117/12.2192687
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