The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods. Much of the coastal shallow water zone worldwide remains unmapped using recent techniques and is, therefore, poorly understood. Optical satellite imagery is proving to be a useful tool in predicting water depth in coastal zones, particularly in conjunction with other standard datasets, though its quality and accuracy remains largely unconstrained. A common challenge in any prediction study is to choose a small but representative group of predictors, one of which can be determined as the best. In this respect, exploratory analyses are used to guide the make-up of this group, where we choose to compare a basic non-spatial model versus four spatial alternatives, each catering for a variety of spatial effects. Using one instance of RapidEye satellite imagery, we show that all four spatial models show better adjustments than the non-spatial model in the water depth predictions, with the best predictor yielding a correlation coefficient of actual versus predicted at 0.985. All five predictors also factor in the influence of bottom type in explaining water depth variation. However, the prediction ranges are too large to be used in high accuracy bathymetry products such as navigation charts; nevertheless, they are considered beneficial in a variety of other applications in sensitive disciplines such as environmental monitoring, seabed mapping, or coastal zone management.

Pockmarks are seabed depressions developed by fluid flow processes that can be found in vast numbers in many marine and lacustrine environments. Manual mapping of these features based on geophysical data is, however, extremely time-consuming and subjective. Here, we present results from a semi-automated mapping toolbox developed to allow more efficient and objective mapping of pockmarks. This ArcGIS-based toolbox recognizes, spatially delineates, and morphometrically describes pockmarks. Since it was first developed, the toolbox has helped to map and characterize several thousands of pockmarks on the UK continental shelf, especially within the central North Sea. This paper presents the latest developments in the functionality of the toolbox and its adaptability for application to other geographic areas (Barents Sea, Norway, and Malin Deep, Ireland) with varied pockmark and seabed morphologies, and in different geological settings. The morphometric characterization of vast numbers of pockmarks allows an unprecedented statistical analysis of their morphology. The outputs from the toolbox provide an objective, quantitative baseline for combining this information with the geological and oceanographical knowledge of individual areas, which can provide further insights into the processes responsible for their development and their influence on local seabed conditions and habitats.

Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, potentially offering a higher revision period to map shoreline position and change, but this can only be feasible if we have a better interpretation of what shorelines as extracted from SAR imagery represent on the ground. This study aims to assess the application of shorelines extracted from SAR from publicly available satellite imagery to map and capture intra-annual to inter-annual shoreline variability. This is assessed in three tidally controlled coastal study areas that represent sand and gravel beaches with different backshore environments: low-lying dunes and marsh; steep, rocky cliff; and urban environments. We have found that SAR shorelines consistently corresponded to positions above the high-water mark across all three sites. We further discuss the influence of the scene geometry, meteorological and oceanographic conditions, and backshore environment and provide a conceptual interpretation of SAR-derived shorelines. In a low-lying coastal setting, the annual change rate derived through SAR presents a high degree of alignment with the known reference values. The present study contributes to our understanding of the poorly known aspect of using shorelines derived from publicly available SAR satellite missions. It outlines a quantitative approach to automatically assess their quality with a new automatic detection method that is transferable to shoreline evolution assessments worldwide.

Nearshore bathymetric data are used in many coastal monitoring applications, but acquisition conditions can be challenging. Shipborne surveys are prone to the risk of grounding in shallow waters, and scheduled airborne surveys often fail to coincide with optimal atmospheric and water conditions. As an alternative, since its launch in 2018, ICESat-2 satellite laser profile altimetry data provide free and readily available data on a 91-day repeat cycle, which may contain incidental bathymetric returns when suitable environmental conditions prevail. In this paper, the vertical accuracy of extracted, refraction-adjusted ICESat-2 nearshore marine bathymetric data is evaluated at four test sites in a Northern hemisphere, temperate latitude location. Multiple ICEsat-2 bathymetric values that occurred in close horizontal proximity to one another were averaged at a spatial scale of 1 m and compared with Multibeam Echosounder bathymetric survey data and Global Navigation Satellite System reference data. Mean absolute errors of less than 0.15 m were observed up to depths of 5 m, with errors of less than 0.24 m (to 6 m), 0.39 m (to 7 m) and 0.52 m (to 10 m). The occurrence of larger bathymetric errors with depth, which increase to 0.54 m at maximum photon depths of 11 m, appears to be primarily related to reduced numbers of geolocated photons with depth. The accuracies achieved up to 6 m suggest that the manual extraction, refraction adjustment and bathymetric filtering steps were effective. Overall, the results suggest that ICESat-2 bathymetric data accuracy may be sufficient to be considered for use in nearshore coastal monitoring applications where shipborne and airborne bathymetric data might otherwise be applied.

In this manuscript, we present the first version of the user-needs specification and the service-providers feasibility-analysis produced by the Monitoring Coastal Change from Space consortium for the Coastal Erosion project (2019 to 2021). The scope of the European Space Agency (ESA) Coastal Erosion project is the development and demonstration of innovative EO products that will be driven by end-user organizations and provided as services to agencies and communities with responsibilities of monitoring coastal change. This project involves end users from the UK (British Geological Survey), Canada (ARCTUS), Ireland (Geological Survey Ireland), Spain (MITECO assisted by IHCantabria) and France (IGNFI). This consortium led by ARGANS and supported by isardSAT and adwäisEO, is developing innovative approaches that best exploit the novel observational capabilities of both synthetic aperture radar (SAR - e.g. Sentinel-1) and multi-spectral optical (e.g. Sentinel-2) earth observation (EO) data. End-Users have defined seventeen products that represent the coastal change of different observable geometries (1D, 2D and 3D). We have clustered these into five general EO products: (1D) waterlines and shoreline indicators; (2D) Land Use, Land Cover and habitats maps; (3D) Topo Bathymetric Digital Elevation Models; (CSI) Coastal State Indicators. The rationale, benefits and feasibility of each type of product is presented. The next step is to expand this first version of the requirements the requirements from the broader community of end-users to produce a final consolidated version of the users-needs and feasibility analysis.