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Satellite-based coastal monitoring through variance image composites (SatVar)

Martín-Gallego, Pilar ORCID: https://orcid.org/0000-0002-8459-1244; Montes, Juan ORCID: https://orcid.org/0000-0002-0365-5155; Delgado-Fernandez, Irene ORCID: https://orcid.org/0000-0001-8101-0670; Río, Laura del ORCID: https://orcid.org/0000-0001-6537-4773; Plomaritis, Theocharis A. ORCID: https://orcid.org/0000-0002-9819-0927; Marston, Christopher ORCID: https://orcid.org/0000-0002-2070-2187. 2026 Satellite-based coastal monitoring through variance image composites (SatVar). International Journal of Applied Earth Observation and Geoinformation, 154, 105630. 19, pp. 10.1016/j.jag.2026.105630

Abstract

The past decade has seen rapid advancements in satellite remote sensing data availability and analysis. In coastal environments, this has enabled regional to global assessments of shoreline trends, a key practical application for management and planning. However, coastal zones are inherently dynamic, while instantaneous shorelines only capture the state of the system at a particular moment in time. This study introduces a novel approach for monitoring dynamic coastal environments using satellite imagery, adapting the principle from ground-based video monitoring systems. The SatVar approach presented here uses freely available, medium resolution satellite imagery and Google Earth Engine. The method takes advantage of the increasing availability of cost-free Sentinel-2 imagery and the flexibility of collections acquired over different time periods to automatically detect highly dynamic zones through variance composites, image compositing and segmentation to obtain medium-term trends of coastal dynamics. Natural boundaries are rarely abrupt, so a zone-based (instead of a line-based) approach provides more nuanced information about transitional zones. The identified highly dynamic zones correspond to morphological processes described in literature, and are also used for shoreline extraction. This combined information can enrich understanding of coastal dynamics and overcome some of the limitations of instantaneous shorelines. The approach is tested at three locations with different morphodynamic characteristics and tidal regimes: Sancti Petri (Spain, mesotidal), Narrabeen (Australia, microtidal) and Sefton (UK, macrotidal). Potential applications to monitor changes outside the upper shoreface such as coastal dune dynamics or back-barrier environments are also discussed.

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