Enhanced SAR-Based Shoreline Extraction in Microtidal Beaches Through Improved Preprocessing of Sentinel-1 and TerraSAR-X Data

Shoreline extraction from synthetic aperture radar (SAR) imagery has been increasingly explored due to its all-weather, day-and-night observation capabilities. In this study, a robust methodology for automatic shoreline detection was developed and validated using SAR data from Sentinel-1 (S1, 20 images) and TerraSAR-X (TSX, two images). SAR images acquired over four microtidal Mediterranean sandy and gravel beaches were processed using a multistep workflow that included preprocessing, noise reduction, land–sea segmentation by clustering or thresholding methods, shoreline extraction, and outlier detection techniques. The accuracy of the SAR-derived shorelines was evaluated against reference ones obtained from high-resolution aerial orthomosaics or PlanetScope imagery. The results of the S1 analyses demonstrated excellent accuracy and stability for gravel beaches [approximately 6 m of mean absolute deviation (MAD)], and for sandy beaches (approximately 7 m of MAD), in this latter case with significant variations observed between the two sites. In a comparative assessment, TSX data achieved higher accuracy in terms of MAD (2.5 m) compared to S1 (6.5 m) in the same context, but only in the image with good meteorological conditions (no differences were obtained in the other date). In general, the use of the block-matching and 3-D filtering filter significantly improved image quality, reducing noise artifacts and enhancing the contrast between land and sea, especially in not-perfect meteorological conditions, which usually influenced SAR-derived shoreline accuracy. Using three classes in the classification also produced better results, and outlier detection played a minor role. Overall, this study demonstrates that the innovative integration of advanced image processing techniques and classification algorithms significantly enhances the reliability of SAR-based shoreline detection. The findings underscore the potential of SAR imagery as a valuable tool for coastal monitoring. Achieving an accuracy close to that obtainable with multispectral data, shoreline extracted from SAR could be successfully used in areas with frequent cloud cover or limited optical data availability.