Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy

Abstract

SAET (Shoreline Analysis and Extraction Tool) is a novel open-source tool to enable the completely automatic detection of shoreline position changes using the optical imagery acquired by the Sentinel-2 and Landsat 8 and 9 satellites. SAET has been developed within the ECFAS (European Coastal Flood Awareness System) project, which is intended to be the first European service for coastal flood forecasting, management, and recovery analysis. The tool is developed to characterise the shoreline response associated with punctual events such as coastal storms as well as any other phenomenon. For a given beach segment, SAET facilitates the selection of the satellite images closest in time to the analysed events that offer an adequate cloud coverage level for analysing the shoreline change. Subsequently, the tool automatically downloads the images from their official repositories, pre-processes them and extracts the shoreline position with sub-pixel accuracy. In order to do so, an initial approximate definition of the shoreline is carried out at the pixel level using a water index thresholding, followed by an accurate extraction operating on the shortwave infrared bands to produce a sub-pixel line in vector formats (points and lines). The tool offers different settings to be adapted to the different coastal environments and beach typologies. Its main advantages refer to its autonomy, its efficiency in extracting complete satellite scenes, its flexibility in adapting to different environments and conditions, and its high subpixel accuracy. This work presents an accuracy assessment on a long Mediterranean sandy beach of SDSs extracted from L8 and S2 imagery against coincident alongshore reference lines, showing an accuracy of about 3 m RMSE. At the same time, the work shows an example of the usage of SAET for characterising the response to Storm Gloria (January 2020) on the beaches of Valencia (E Spain). SAET provides an efficient and completely automatic workflow that leads to accurate SDSs while only relying on publicly available information. The tool appears to be a useful extraction tool for beach monitoring, both for public administrations and individual users.

Geoinformation Technology in Support of Arctic Coastal Properties Characterization: State of the Art, Challenges, and Future Outlook

“…However, this tool can be used locally by the user. [72] provide a more descriptive analysis on the SAET tool and its implementation. SAET is available for download from Zenodo.…”

Assessing Satellite-Derived Shoreline Detection on a Mesotidal Dissipative Beach

“…The instantaneous SDWLs were defined from the freely available optical Sentinel-2 imagery using the software SAET v4 (https://github.com/jpalomav/SAET_master) with different configuration parameters (Figure 5). The workflow followed four main phases (see details in [15]) comprising the image downloading, the segmentation for defining the APS, its masking, and the final extraction of the sub-pixel waterline.…”

“…The instantaneous SDWLs were defined from the freely available optical Sentinel-2 imagery using the software SAET v4 (https://github.com/jpalomav/SAET_master) with different configuration parameters (Figure 5). The workflow followed four main phases (see details in [15]) comprising the image downloading, the segmentation for defining the APS, its masking, and the final extraction of the sub-pixel waterline. thresholding method by Otsu [21], and finally defined the continuous sets of pixels that constitute the limit of the water mask (i.e., the water/land interface) by applying the morphological filters of dilation and erosion (that would displace it landward/seawards, respectively).…”

“…Satellite-derived shoreline (SDS) algorithms such as CoastSat [10], SHOREX [11], and CASSIE [12] have tackled this challenge by devising efficient approaches to overcome such limitations (see review and benchmark comparison in Vos et al [13]). Sustained in the subpixel solution proposed by Pardo-Pascual et al [14] and in the workflow followed by SHOREX, the tool SAET [15] has appeared as a new alternative focused on offering high autonomy, efficiency and robustness in the extraction. This goal is accomplished by enabling its application along large coastal segments while tuning the settings and extraction parameters according to the respective coastal characteristics.…”

“…SAET is a versatile tool that enables choosing among different parameters and methods for defining the approximate and the subpixel WL [15]. Their combined testing was preliminarily addressed by Pardo-Pascual et al [18] across a variety of coastal types.…”