New Methodology for Shoreline Extraction Using Optical and Radar (SAR) Satellite Imagery
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Published:2023-03-16
Issue:3
Volume:11
Page:627
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ISSN:2077-1312
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Container-title:Journal of Marine Science and Engineering
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language:en
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Short-container-title:JMSE
Author:
Zollini Sara1ORCID, Dominici Donatella1ORCID, Alicandro Maria1ORCID, Cuevas-González María2ORCID, Angelats Eduard2ORCID, Ribas Francesca3ORCID, Simarro Gonzalo4ORCID
Affiliation:
1. DICEAA—Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, Via G. Gronchi 18, 67100 L’Aquila, Italy 2. Geomatics Research Unit, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Av. Carl Friedrich Gauss 7, 08860 Castelldefels, Spain 3. Department of Physics, Universitat Politècnica de Catalunya, C. Jordi Girona 1-3, 08034 Barcelona, Spain 4. Department of Marine Geosciences, Instituto de Ciencias del Mar (ICM-CSIC), Passeig Maritim de la Barceloneta 37-49, 08003 Barcelona, Spain
Abstract
Coastal environments are dynamic ecosystems, constantly subject to erosion/accretion processes. Erosional trends have unfortunately been intensifying for decades due to anthropic factors and an accelerated sea level rise might exacerbate the problem. It is crucial to preserve these areas for safeguarding not only coastal ecosystems and cultural heritage, but also the population living there. In this context, monitoring coastal areas is essential and geomatics techniques, especially satellite remote sensing imagery, might prove very advantageous. In this paper, a semi-automatic methodology to extract shorelines from SAR (Synthetic Aperture Radar) Sentinel-1 and optical Sentinel-2 satellite images was developed. An experimental algorithm, called J-Net Dynamic, was tested in two pilot sites. The semi-automatic methodology was validated with GNSS (Global Navigation Satellite System) reference shorelines and demonstrated to be a powerful tool for a robust extraction of the shoreline both from optical and SAR images. The experimental algorithm was able to extract the shoreline closer to the reference with SAR images on the natural beach of Castelldefels and it was demonstrated to be less sensitive to speckle effects than the commonly used Canny Edge Detector. Using the SAR images of the urban beach of Somorrostro, the Canny detector was not able to extract the shoreline, while the new algorithm could do it but with low accuracy because of the noise induced by man-made structures. For further investigation, the Sentinel-2-extracted shorelines were also compared to the ones extracted by a state-of-the-art tool, CoastSat, in the two beaches using both automatic and manual thresholds. The mean errors obtained with J-Net Dynamic were generally higher than the ones from CoastSat using the manual threshold but lower if using the automatic one. The proposed methodology including the J-Net Dynamic algorithm proves to extract the shorelines closer to the reference in most of the cases and offers the great advantage of being able to work with both optical and SAR images. This feature could allow to reduce the time lag between satellite derived shorelines paving the way to an enhanced monitoring and management of coastal areas.
Funder
Spanish government “ERDF A way of making Europe” of the European Union
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
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