Assessment of the shoreline dynamics in San Andres Island: A remote sensing and EOF analysis approach

Abstract

This study investigates the spatial and temporal variability of the shoreline of San Andres Island (SAI), located in an internationally recognized protected area in the Colombian Caribbean Sea, using Sentinel-2 satellite images covering six years (2015–2021). The data were downloaded using Google Earth Engine and processed with the CoastSat tool. Coastal indicators NSM, EPR, and LRR were calculated. Afterward, an Empirical Orthogonal Functions (EOF) analysis was implemented to comprehend the favored spatial patterns of the coasts in two significant regions of the island and their corresponding temporal fluctuation. As a result, the statistical indicators revealed that more than 60 % of the transects displayed erosional trends in both study areas. This study found three prevailing patterns that account for a significant portion of the variability in the data. The first EOF mode revealed a cross-shore movement of the shoreline, as shown by a spatial structure with no crossings by zero in the two zones analyzed. The second EOF mode had zero crossings or nodal locations, representing alongshore movement. The third EOF mode was related to a coastal phenomenon known as "breathing," which influenced the curvature of the coastline. The spatial variability is thus explained by the incoming waves (first and second phase) and the beach form (third phase). For both zones, the temporal modes of variability were correlated with wave parameters and with less significance by the wind speed. Additionally, accretion and erosion patterns based on remote sensing were generated for those zones. The insights gained from this study hold significant promise for policymakers aiming to mitigate coastal erosion and enhance the resilience of San Andres Island. By integrating these findings into decision-making processes, effective strategies can be developed to protect and sustain this vital coastal ecosystem for future generations.