Coastal zones are home to about 40% of the world's population and include key infrastructure and ecosystems. These regions are crucial for economic activities like maritime transport or the deployment of offshore renewable energy, are vital for human settlement and contain unique habitats. Erosion, sediment transport, climate-change, and human activities exert pressure on coastal zones and make them highly dynamic. Accurate mapping of shallow water bathymetry is essential for effective and sustainable management, yet many areas remain unmapped or have outdated bathymetry data. A pivotal technology facing the challenge of bathymetry mapping on a large scale is Satellite-Derived Bathymetry (SDB), which has become a game-changing method for understanding and managing coastal areas by delivering accurate information about underwater topography. SDB leverages data from Earth Observation (EO) satellites, such as the Copernicus Sentinel-2 satellites. EO technologies enable continuous, global-scale observations across expansive and often inaccessible areas, democratizing data access and allowing regions with limited resources to benefit from these advancements without significant financial investment. The extensive archives of EO data establish robust baselines that facilitate the analysis of long-term environmental changes, aiding in the creation of informed management strategies. The immense potential of EO has been recognized by diverse stakeholders, including the European Commission, which enlisted Mercator Ocean International to collaborate with EOMAP (as lead), Deltares, and GGSgc to deliver a global coastal satellite-derived bathymetry dataset. This initiative employs state-of-the-art methodologies - including the inversion of the radiative transfer equation, intertidal bathymetry, wave kinematics, and active satellite LiDAR measurements – to reach the greatest possible coastal bathymetry coverage from the shoreline down to a maximum depth of -35 m. The dataset will be made publicly accessible in a 100m spatial resolution grid within the Copernicus Marine Service. Our presentation gives an overview of the technological processes involved in creating this dataset, shares initial results and findings and demonstrates the potential of very high-resolution SDB grids for coastal zone monitoring using the identical techniques. Fundamental to achieving the UN Ocean Decade goals, this shared comprehensive global dataset not only advances our scientific understanding of coastal zones but is also essential for promoting international cooperation in coastal conservation and for collective sustainable ecosystem management. The results can contribute to the Nippon Foundation-GEBCO Seabed 2030 Project, which aims to provide a global 100m resolution bathymetry grid by 2030. The project positions EO instruments at the forefront of fostering innovative monitoring solutions, driving scientific discovery, and crafting resilient management frameworks necessary for adapting to and mitigating the impacts of climate change on coastal ecosystems. As such, this project embodies a pivotal advancement towards sustainable ocean management and more resilient coastal communities, together with understanding the blue planet more comprehensively.

For state and federal beach nourishment projects, agencies often face challenges to provide rapid assessments of volume losses immediately after a storm event. These assessments play an important role in quantifying losses and assisting in the decision-making process regarding disaster declarations. Traditionally, the immediate post-storm beach assessment is conducted using visual estimates aided by limited measurements (beach elevation, scarp height, distance from dune to waterline, etc). Rapid assessments based on visual estimates and limited measurements often have a significant margin of error, especially due to the lack of data in the offshore part of the beach profile. Traditional beach profile surveys including the dry-beach and the offshore portion of the beach profile are only collected at a later date, after initial assessments and disaster declarations. Utilizing Satellite-Derived Bathymetry (SDB) to quantify the offshore portion of the profile immediately after a storm could address the issue of lack of offshore data when conducting rapid post-storm assessments for disaster declaration. SDB data is spatially complete, can be available for multiple dates pre- and post-storm (typically a few days after the storm), and it can be used to improve beach volume loss estimates of rapid post-storm assessments. However, SDB is also subject to limitations inherent in the methods and data processing which will be discussed in this paper. The applicability of SDB is assessed here thorough comparative analysis between pre- and post- storm SDB datasets and traditional topo-bathy beach profile surveys. Both SDB data and traditional surveys were obtained at the same dates for the study area, Coquina Beach, located at the southern end of Anna Maria Island, Manatee County, Florida. By conducting this comparative analysis and examining the differences between traditional beach profile surveys and SDB data, the usefulness and limitations of using SDB in estimating preliminary volume losses after a storm event are elucidated. This analysis demonstrated that SDB data can contribute to greater accuracy in post-storm assessments to assist in initial economical loss estimate and disaster declarations as well as facilitate faster disaster response.

Global bathymetry data is essential for coastal mapping, modeling, and management, especially in insufficiently mapped regions. Ocean surface Wave Kinematics Bathymetry from satellite data provides a solution independent of water clarity, seabed habitats, and seafloor brightness. This study presents a fully automatic, scalable, and globally applicable Wave Kinematics Bathymetry processing workflow at 100 m resolution. Validated across eleven sites, it introduces automatic post-processing that eliminates false positives by up to 80 %, reduces depth errors by an average of 4.6 m and enhances data reliability. Deployed on the AWS cloud platform, this scalable method advances efficient global coastal bathymetry mapping.

Satellite-Derived Bathymetry (SDB) methods have found their way into the hydrographers’ toolbox and are part of integrated survey concepts, nautical charts and support global and European programs such as Seabed2030 or EMODnet Bathymetry. The concept of the ‘physics-based’ SDB describes the calculation of bathymetry by modelling the sunlight path from the sun to the seafloor to the satellite sensor. It is a highly sophisticated model which enables the calculation of shallow water depth in the absence of any other survey or ground-truth data. Thus, bathymetric data can also be retrieved for remote and inaccessible areas - in contrast to empirical SDB approaches. Key questions which arise for SDB results are vertical accuracy, potential and feasibility for different sites and the methods to upscale SDB solutions. These questions are addressed in the current European innovation project 4S. Within the project SDB-Online was developed, a fully physics-based SDB concept which is installed in a cloud and accessible via a web user interface. The backend is parallelised and can be accessed via application programming interface (API) which allows a fully scalable and automatic SDB processing. In this study SDB-Online results are validated at ten sites, ranging from the higher latitudes of Canada to turbid UK waters to the Caribbean. Furthermore, a relationship between the Secchi Disc Depth and the cutoff depth of the SDB results is established and a global map of water-clarity potential of the SDB solution is presented.

Smart monitoring, planning and decision making for projects in the coastal and nearshore regions requires spatial and temporal understanding on the environmental parameters. Very often time and budget constraints preclude a comprehensive physical and environmental survey data collection exercise. Bathymetry, for example, is typically valid for one timestamp (during the period of data collection), one-dimensional (e.g. single beam surveys), and has sparse resolution in the shallow nearshore regions. In recent years, significant advances in satellite sensor technology and analysis have been developed to produce relevant information for coastal and nearshore monitoring applications at a fraction of both the time and cost of traditional methods. Aquatic Earth Observation techniques have been evolving since the 1970s. The recent advances on satellite sensor hardware and analytics have allowed the once crude methodology to be efficiently applied into practice-in particular very high-resolution satellite data availability and the sound understanding on the physical modelling of the light path from the surface/seafloor to the sensor. Applying over 20 years of continuous research and development, EOMAP has advanced a unique physics-based procedure which allows mapping of shallow water bathymetry, water quality parameters, seafloor characteristics and topography in dense spatial grids. Uncertainties in Earth Observation products are subject to a number of environmental factors that need to be accounted for. At the core of the technology are state-of-the-art algorithms for extracting quantitative environmental information from the aquatic remote sensing signal. Mechanisms for quantifying uncertainties and flagging relative reliabilities are embedded in the algorithms, which include: (1) allowance for coupled atmospheric and in-water parameter retrievals, which includes a correction of the (terrestrial) adjacency effect, critical for the accurate remote sensing of any coastal or inland water body, (2) a physically accurate implementation of the bi-directional effect inside the water column, at the water surface and in the atmosphere, (3) accounting for the full range of reflecting, absorbing and scattering properties of the water body and the interfaces. Those procedures are included in EOMAP’s Watcor-X physics-based Satellite-Derived Bathymetry (SDB) software. This paper provides an overview of SDB, demonstrates successful project applications, and describe tools that support coastal and nearshore monitoring projects through the use of the software in the Pacific, Caribbean Sea and Arabian waters. We showcase the capability to monitor spatial seabed changes in highly dynamic environments, and demonstrate the latest technology that jointly incorporates the passive multispectral satellite imagery with complementary active Satellite-Lidar bathymetric data technology using NASA’s ICESAT-2 Advanced Topographic Laser Altimeter System (ATLAS) sensor.

The objective of tins article is to provide an overview of the Satellite Derived Bathymetry methods, how data can be integrated into survey campaigns and finally to showcase thine use cases. Bathymetric data in the shallow water zone is of increasing importance to support various applications such as safety of navigation, reconnaissance surveys, coastal zone management or hydrodynamic: modelling. A gap was identified between data demand, costs and the ability to map with ship and airborne sensors, This has led to the rise of a new tool to map shallow water bathymetry using multispectral satellite image data, widen! known as Satellite Derived Bathymetry (SUB).