On the Use of Multipolarization Satellite SAR Data for Coastline Extraction in Harsh Coastal Environments: The Case of Solway Firth

Abstract

This study deals with coastline extraction using multi-polarization spaceborne Synthetic Aperture Radar (SAR) imagery acquired over coastal intertidal areas. The latter are very challenging environments where mud flats lead to a large variability of normalized radar cross section (NRCS), which may trigger a significant number of false edges during the extraction process. The performance of SAR-based coastline extraction methods that rely on a joint combination of multi-polarization information (either single-or dual-polarization metrics) and speckle filtering (either local and non-local approaches) are analyzed using Global Pointing System (GPS) samples and collocated SAR imagery collected under different incidence angles. Our test site is an intertidal zone with a wetland (i. e., salt marsh) in the Solway Firth, southwest along the Scottish-English border. Experimental results, obtained processing a pair of RadarSAT-2 full-polarimetric and a pair of Sentinel-1 dual-polarimetric SAR imagery augmented by co-located GPS samples, show that: a) the multi-polarization information outperforms the singlepolarization counterpart in terms of extraction accuracy; b) among the single-polarization channels, the cross-polarized one performs best; c) both single-and dual-polarization methods perform better when non-local speckle filtering is applied; d) the joint combination of non-local speckle filter and dual-polarization information provides the best accuracy; e) the incidence angle plays a role in the extraction accuracy with larger incidence angles resulting in the best performance when dual-polarization metric is used.

An Overview of Advances in Signal Processing Techniques for Classical and Quantum Wideband Synthetic Apertures

“…Modern SARs produce valuable information content especially if they operate in multichannel [49], multi-polarization [50,51], or multi-temporal mode [52]. The multispectral SAR typically provides images with higher spatial resolution but poorer spectral resolution.…”

“…In practice, it is desired to remove this specific noise ζ in (8) (see Fig. 4(a)) through denoising or despeckling filters [52]. However, it is not always possible, at least not without degrading useful information [52,54].…”

“…4(a)) through denoising or despeckling filters [52]. However, it is not always possible, at least not without degrading useful information [52,54]. In other words, a positive effect of speckle suppression takes place simultaneously with a negative effect of smearing of image edges and details.…”

Coastline extraction from ALOS-2 satellite SAR images

“…The obtained shape is smoothened by mathematical morphology. Study (Ferrentino et al 2020) proposes a model-driven pipeline consisting of noise filtering, morphological filtering, and edge detection. It shows that noise filtering plays an important role when such a model-driven approach is used and affects the results significantly.…”

An Unsupervised Port Detection Method in Polarimetric SAR Images Based on Three-Component Decomposition and Multi-Scale Thresholding Segmentation

“…To avoid the wrong segmentation caused by the intensity intersection of different regions, Wang et al [16] proposed a classification scheme of mud and sand flats on intertidal flats using different polarimetric decomposition components. Ferrentino et al [17] proposed a coastline extraction scheme in harsh coastal environments using a global constant false alarm rate (CFAR) thresholding segmentation of a normalized cross-section in different polarimetric channels. However, it is still difficult to segment the land and water along ports using the existing polarimetric methods since the port water regions are interfered with by surrounding strong scattering buildings and ships.…”