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Shoreline variations, triggered by climate change, eustatism, and tectonic, drive the coastal landscape evolution over multiple spatial and temporal scales. Among the many different existing coast types, sandy coasts are the most sensitive to coastal erosion and accretion processes and, at the same time, often host valuable anthropogenic assets. The rapid and ongoing evolution of these coastal environments poses challenges for their management, necessitating cost-effective and highly reliable methods for measuring these changes. Many remotely sensed shoreline extraction methods have been proposed in the literature, providing valuable tools for improving coastal management. Even if these methodologies allow the demarcation of the shoreline, its pixelated shape usually requires refinement through subsequent smoothing or vector generalization processes. It is important to note that the position of the thus extracted coastline is not a direct result of a measured physical quantity but rather a product of these refinement techniques. To address this problem, we developed a sub-pixel resolution method for extracting shorelines from remotely sensed images of sandy beaches, leveraging the radiometric signature of the shoreline. Validated through precise Global Navigation Satellite System field surveys for positioning the beach foreshore, this method was successfully applied to three beaches in Sicily, in the central Mediterranean, all exhibiting similar microtidal conditions. Its robust design allows for application across various satellite images, employing a straightforward radiometric interpolation method adaptable to different spatial resolutions. This method would be a valuable tool for coastal managers in detecting and mitigating coastal erosion and developing and maintaining anthropogenic coastal assets.
Caldareri et al. (Fri,) studied this question.