In this study, we propose a new baseline and transect method, the open-source digital shoreline analysis system (ODSAS), which is specifically designed to deal with very irregular coastlines. We have compared the ODSAS results with those obtained using the digital shoreline analysis system (DSAS). Like DSAS, our proposed method uses a single baseline parallel to the shoreline and offers the user different smoothing and spacing options to generate the transects. Our method differs from DSAS in the way that the transects’ starting points and orientation are delineated by combining raster and vector objects. ODSAS uses SAGA GIS and R, which are both free open-source software programs. In this paper, we delineate the ODSAS workflow, apply it to ten study sites along the very irregular Galician coastline (NW Iberian Peninsula), and compare it with the one obtained using DSAS. We show how ODSAS produces similar values of coastline changes in terms of the most common indicators at the aggregated level (i.e., using all transects), but the values differ when compared at the transect-by-transect level. We argue herein that explicitly requesting the user to define a minimum resolution is important to reduce the subjectivity of the transect and baseline method.

Coasts are continually changing and remote sensing from satellite has the potential to both map and monitor coastal change at multiple scales. This study aims to assess the application of shorelines extracted from Multi-Spectral Imagery (MSI) and Synthetic Aperture Radar (SAR) from publicly available satellite imagery to map and capture sub-annual to inter-annual shoreline variability. This is assessed at three macro-tidal study sites along the coastline of England, United Kingdom (UK): estuarine, soft cliff environment, and gravel pocket-beach. We have assessed the accuracy of MSI-derived lines against ground truth datum tideline data and found that the satellite derived lines have the tendency to be lower (seaward) on the Digital Elevation Model than the datum-tideline. We have also compared the metric of change derived from SAR lines differentiating between ascending and descending orbits. The spatial and temporal characteristics extracted from SAR lines via Principal Component Analysis suggested that beach rotation is captured within the SAR dataset for descending orbits but not for the ascending ones in our study area. The present study contributes to our understanding of a poorly known aspect of using coastlines derived from publicly available MSI and SAR satellite missions. It outlines a quantitative approach to assess their mapping accuracy with a new non-foreshore method. This allows the assessment of variability on the metrics of change using the Open Digital Shoreline Analysis System (ODSAS) method and to extract complex spatial and temporal information using Principal Component Analysis (PCA) that is transferable to coastline evolution assessments worldwide.