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Article

Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites

1
Geospatial Analysis and Modelling (GAM) Research Group, Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS (UTP), Seri Iskandar 32610, Malaysia
2
C-CORE and Department of Electrical Engineering, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
3
Centre of Urban Resource Sustainability, Institute of Self-Sustainable Building, Universiti Teknologi PETRONAS (UTP), Seri Iskandar 32610, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editors: Robin Teigland, Torsten Linders, Sergio Leandro and Ivan Masmitja
Remote Sens. 2021, 13(18), 3587; https://doi.org/10.3390/rs13183587
Received: 1 June 2021 / Revised: 25 July 2021 / Accepted: 26 August 2021 / Published: 9 September 2021
Rising sea level is generally assumed and widely reported to be the significant driver of coastal erosion of most low-lying sandy beaches globally. However, there is limited data-driven evidence of this relationship due to the challenges in quantifying shoreline dynamics at the same temporal scale as sea-level records. Using a Google Earth Engine (GEE)-enabled Python toolkit, this study conducted shoreline dynamic analysis using high-frequency data sampling to analyze the impact of sea-level rise on the Malaysian coastline between 1993 and 2019. Instantaneous shorelines were extracted from a test site on Teluk Nipah Island and 21 tide gauge sites from the combined Landsat 5–8 and Sentinel 2 images using an automated shoreline-detection method, which was based on supervised image classification and sub-pixel border segmentation. The results indicated that rising sea level is contributing to shoreline erosion in the study area, but is not the only driver of shoreline displacement. The impacts of high population density, anthropogenic activities, and longshore sediment transportation on shoreline displacement were observed in some of the beaches. The conclusions of this study highlight that the synergistic use of multi-sensor remote-sensing data improves temporal resolution of shoreline detection, removes short-term variability, and reduces uncertainties in satellite-derived shoreline analysis compared to the low-frequency sampling approach. View Full-Text
Keywords: optical imaging satellites; subpixel shoreline detection; GEE; sea-level rise optical imaging satellites; subpixel shoreline detection; GEE; sea-level rise
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MDPI and ACS Style

Adebisi, N.; Balogun, A.-L.; Mahdianpari, M.; Min, T.H. Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites. Remote Sens. 2021, 13, 3587. https://doi.org/10.3390/rs13183587

AMA Style

Adebisi N, Balogun A-L, Mahdianpari M, Min TH. Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites. Remote Sensing. 2021; 13(18):3587. https://doi.org/10.3390/rs13183587

Chicago/Turabian Style

Adebisi, Naheem, Abdul-Lateef Balogun, Masoud Mahdianpari, and Teh H. Min. 2021. "Assessing the Impacts of Rising Sea Level on Coastal Morpho-Dynamics with Automated High-Frequency Shoreline Mapping Using Multi-Sensor Optical Satellites" Remote Sensing 13, no. 18: 3587. https://doi.org/10.3390/rs13183587

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