Satellite Derived Shorelines at an Exposed Meso-tidal Beach

ABSTRACT Cabezas-Rabadán, C.; Pardo-Pascual, J.E.; Palomar-Vázquez, J.; Ferreira, Ó., and Costas, S., 2020. Satellite Derived Shorelines at an exposed meso-tidal beach. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1027–1031. Coconut Creek (Florida), ISSN 0749-0208. Shoreline position data offer extremely valuable information for understanding coastal dynamism and beach changes. This research applies SHOREX system for defining the shoreline position from free mid-resolution Landsat-8 (L8) and Sentinel-2 (S2) satellite imagery. This system allows an automatic definition of Satellite Derived Shorelines (SDS) over large regions and periods. Accuracy and utility of the resulting SDS have been previously assessed with positive results at low energy, microtidal, Mediterranean beaches. This work assesses SDS extracted using SHOREX at a mesotidal and moderate to highly (during storms) energetic environment, namely at Faro Beach, a barrier beach located in Ria Formosa (Algarve, South Portugal). Accuracy was defined for 14 SDS derived from S2 and 10 from L8 by measuring the differences in position with respect to the shoreline inferred from profiles obtained on close dates (or simultaneously) to imagery acquisition. For non-simultaneous datasets, the water level was estimated for the time of the satellite images acquisition using oceanographic data and run-up formulations. The measured and estimated shoreline positions were then compared with the extracted SDS. The overall accuracy is good, with errors about 5 m RMSE, supporting the application of the used methodology to define shoreline dynamics and evolution at challenging environments, as mesotidal exposed and dynamic beaches.

[1]  Ad Reniers,et al.  On the accuracy of automated shoreline detection derived from satellite imagery: A case study of the sand motor mega-scale nourishment , 2018 .

[2]  Jaime Almonacid-Caballer,et al.  An efficient protocol for accurate and massive shoreline definition from mid-resolution satellite imagery , 2020 .

[3]  J. Palomar-Vázquez,et al.  Characterizing beach changes using high-frequency Sentinel-2 derived shorelines on the Valencian coast (Spanish Mediterranean). , 2019, The Science of the total environment.

[4]  Alfonso Fernández-Sarría,et al.  Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery , 2018, Remote. Sens..

[5]  David P. Roy,et al.  A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring , 2017, Remote. Sens..

[6]  Kristen D. Splinter,et al.  Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery , 2019, Coastal Engineering.

[7]  Jesús Palomar-Vázquez,et al.  Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid-term coastal evolution indicator , 2016 .

[8]  Ángel Balaguer-Beser,et al.  C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint , 2017 .

[9]  Luis Pedro Almeida,et al.  Coastal vulnerability assessment based on video wave run-up observations at a mesotidal, steep-sloped beach , 2011, Ocean Dynamics.

[10]  Jaime Almonacid-Caballer,et al.  Detecting problematic beach widths for the recreational function along the Gulf of Valencia (Spain) from Landsat 8 subpixel shorelines , 2019, Applied Geography.

[11]  Jesús Palomar-Vázquez,et al.  Evaluation of storm impact on sandy beaches of the Gulf of Valencia using Landsat imagery series , 2014 .

[12]  L. Ruiz,et al.  Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision , 2012 .

[13]  Miguel Ortega-Sánchez,et al.  Automatic Methodology to Detect the Coastline from Landsat Images with a New Water Index Assessed on Three Different Spanish Mediterranean Deltas , 2019, Remote. Sens..