LAUSR

Coastline extraction by exploiting optical images is challenging during adverse weather conditions. This letter proposes coastline extraction from synthetic aperture radar (SAR) data. Since collecting in-situ data is expensive and not always possible, the Doppler parameter is used to delineate coastlines when neither in-situ data nor cloud-free optical images are available. We propose a novel coastline extraction method based on classic coastal dynamic variation, such as Doppler centroid ( $f_{\text {DC}}$ ), since the coastline is static and has zero Doppler with respect to the dynamic sea-state. The results of the Doppler-based novel technique allow us to investigate the impact of natural hazards on coastline degradation. We compare the proposed method to state-of-the-art (SOA) coastline extraction methods based on polarimetric correlations and the reference method from Sentinel-2. The results show that using scattering from dual and cross-polarization for coastline extraction is more reliable than using co-polarization. Based on empirical distributions and using the constant false alarm rate (CFAR) method, the relevant threshold has been adapted to distinguish land and sea in an unsupervised manner. We compare the results of polarimetric and Sentinel-2 with Doppler-based coastline extraction, which emphasizes the accuracy of the proposed $f_{\text {DC}}$ method for extracting coastlines at full resolution.