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

Autor:	Abdul-Lateef Balogun, Masoud Mahdianpari, Naheem Adebisi, Teh Hee Min
Rok vydání:	2021
Předmět:	Shore geography geography.geographical_feature_category Contextual image classification Science Sampling (statistics) sea-level rise Coastal erosion Temporal resolution General Earth and Planetary Sciences Environmental science subpixel shoreline detection Tide gauge GEE Physical geography Scale (map) Sea level optical imaging satellites
Zdroj:	Remote Sensing, Vol 13, Iss 3587, p 3587 (2021) Remote Sensing Volume 13 Issue 18 Pages: 3587
ISSN:	2072-4292
DOI:	10.3390/rs13183587
Popis:	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.
Databáze:	OpenAIRE
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