Remote sensing-based automatic detection of shoreline position

A case study in apulia region

Journal Article (2021)
Author(s)

Anna Spinosa (TU Delft - Mathematical Physics, Deltares)

Alex Ziemba (TU Delft - Mathematical Physics, Deltares)

Alessandra Saponieri (University of Salento)

Leonardo Damiani (Politecnico di Bari)

Ghada El Serafy (TU Delft - Mathematical Physics, Deltares)

DOI related publication
https://doi.org/10.3390/jmse9060575 Final published version
More Info
expand_more
Publication Year
2021
Language
English
Issue number
6
Volume number
9
Article number
575
Pages (from-to)
1-20
Downloads counter
134
Collections
Institutional Repository
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Remote sensing and satellite imagery have become commonplace in efforts to monitor and model various biological and physical characteristics of the Earth. The land/water interface is a continually evolving landscape of high scientific and societal interest, making the mapping and monitoring thereof particularly important. This paper aims at describing a new automated method of shoreline position detection through the utilization of Synthetic Aperture Radar (SAR) images derived from European Space Agency satellites, specifically the operational SENTINEL Series. The resultant delineated shorelines are validated against those derived from video monitoring systems and in situ monitoring; a mean distance of 1 and a maximum of 3.5 pixels is found.