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New algorithms for shoreline monitoring from coastal video systems

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Abstract

Video systems have become widely used all around the world in coastal monitoring strategies, allowing both high temporal and spatial sampling frequency, with low logistic and costs efforts. The present paper deals with a new tool for coastal images processing, aimed at the automatic shoreline detection and data analysis. The tool is composed by a shoreline detection routine implemented in a web-application, addressed at images processing (i.e. shoreline extraction and geo-rectification), data analysis and sharing results about beach actual state and shore evolution in quasi-real time. The Shoreline Detection Model (SDM) is based on a new algorithm, implementing image-processing procedures, which allows extracting the sea/land boundary from automatic segmented Timex images. The SDM calibration and validation has been performed on different coastal images derived from a video monitoring system installed at Alimini (Lecce, IT) in 2005, by comparing automatic shoreline contours with the manual detected ones. Moreover, in December 2015, new video monitoring systems were installed in South Italy (Porto Cesareo and Torre Canne, Apulia region), at sandy beaches affected by erosion phenomena. The application of the SDM on images recorded by the new systems has allowed testing the model feasibility at sites characterized by different morphological features and geographical exposition. The present describes in detail the SDM algorithm and the image processing procedures used. The results of the model calibration and validation performed at Alimini and the tests performed at Porto Cesareo on first images are reported.

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Acknowledgements

This research is partially supported by Authority of Basin of Apulia Region (Italy). We thank our colleagues from ACIC (http://www.acic-tech.be) who provided expertise in web-application building and management. Intervention co-financed by the Development Fund and Cohesion 2007-2013 - APQ search Apulia Region "Regional program in support of smart specialization and social and environmental sustainability FutureInResearch".

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  1. Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Politecnico di Bari, Via E. Orabona, 4, 70125, Bari, Italy

    Nico Valentini, Alessandra Saponieri, Matteo Gianluca Molfetta & Leonardo Damiani

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  1. Nico Valentini
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  2. Alessandra Saponieri
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  3. Matteo Gianluca Molfetta
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Correspondence to Nico Valentini.

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Communicated by: H. A. Babaie

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Valentini, N., Saponieri, A., Molfetta, M.G. et al. New algorithms for shoreline monitoring from coastal video systems. Earth Sci Inform 10, 495–506 (2017). https://doi.org/10.1007/s12145-017-0302-x

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