I. Overview
The OGC Federated Marine SDI 2024 Pilot – Bridging Land and Sea addresses the integration of terrestrial and marine geospatial datasets across the intertidal zone, a highly dynamic and operationally critical area. Sponsored by the UK Hydrographic Office (UKHO), NOAA, and the National Geospatial-Intelligence Agency (NGA), and supported by Ordnance Survey, the US Geological Survey (USGS), and the Canadian Hydrographic Service (CHS), the pilot showcases innovative, standards-based solutions developed by Compusult, Pangaea Innovations, and TCarta. Using technologies such as OGC APIs, Discrete Global Grid Systems (DGGS), and satellite-derived hydrospatial data, the pilot demonstrates scalable approaches for erosion monitoring, port operations, and shoreline awareness. The Engineering Report highlights the importance of vertical datum reconciliation, semantic uplift, and dynamic 4D integration methods.
In parallel, a Draft Guide and Best Practices Report (D002) is being developed to consolidate implementation guidance, international standards alignment, and lessons learned. It introduces five actionable best practices for sustainable and interoperable coastal data infrastructures: (1) Unified Geospatial Reference through modern vertical datums and separation surfaces; (2) FAIR Data Principles using rich metadata and recognized catalog standards; (3) Mind the Gap by addressing spatial and temporal voids in the intertidal zone; (4) Coordinated Governance via multi-agency data frameworks like IGIF-Hydro; and (5) Scalable Resolution Management for integrating multi-scale elevation data with techniques like TINs and DGGS. These practices aim to improve cross-domain geospatial coordination and support climate resilience, safety of navigation, and integrated coastal zone management.
II. Executive summary
The Federated Marine Spatial Data Infrastructure (FMSDI) 5 Pilot addresses the growing challenge of integrating terrestrial and marine datasets across the dynamic and operationally critical intertidal zone. Intertidal areas, where land meets sea, present complex environmental and data management challenges, especially as coastal dynamics intensify under climate change.
The FMSDI 5 Pilot was designed to respond directly to the needs and objectives articulated by the project sponsors, including the UK Hydrographic Office (UKHO), the US National Oceanic and Atmospheric Administration (NOAA), and the National Geospatial-Intelligence Agency (NGA). Supporting organizations such as Ordnance Survey, the US Geological Survey (USGS), Natural Resources Canada (NRCAN), and the Canadian Hydrographic Service (CHS) contributed valuable expertise and alignment with national geospatial strategies. Sponsors prioritized improving interoperability between land and sea datasets, accelerating the adoption of open standards, and promoting sustainable, scalable approaches to coastal data integration, monitoring, and management.
The pilot brought together Compusult, Pangaea Innovations, and TCarta to explore innovative, standards-based solutions that enable seamless land-sea data integration. Each organization contributed a complementary approach:
Compusult demonstrated a web-based platform that combines land and sea data into unified visualizations and supports navigational decision-making through dynamic tidal modeling.
Pangaea Innovations showcased the use of Discrete Global Grid Systems (DGGS) to link diverse terrestrial and marine datasets using a simple, scalable indexing system that eliminates the need for complex data harmonization.
TCarta applied satellite technologies to generate dynamic, real-time shoreline and bathymetric data, offering a cost-effective solution for continuous coastal monitoring.
Additionally, a separate Draft Guide and Best Practices Engineering Report developed by OceanWise and Pelagis captures key lessons and provides practical recommendations for integrating terrestrial and marine data across the coastal zone.
Key findings from the pilot include:
The adoption of a Unified Geospatial Reference using modern vertical datums and separation surfaces enables precise integration of land and marine elevation data, eliminating discontinuities at the coastline.
Applying FAIR Data Principles through rich metadata and international catalog standards improves data discoverability, automation, and reuse across federated systems.
Addressing intertidal data voids—through the Mind the Gap approach—ensures that spatial and temporal gaps between land and sea datasets are filled using remote sensing, targeted surveys, or documented interpolation.
Implementing Coordinated Governance frameworks such as IGIF-Hydro clarifies institutional responsibilities, reduces duplication, and accelerates policy alignment across sectors.
Scalable Resolution Management allows the fusion of multi-scale elevation datasets using techniques like TINs and DGGS, balancing local detail with regional context for resilient coastal planning.
FMSDI 5 confirms that a next-generation Marine Spatial Data Infrastructure must be dynamic, federated, and standards-driven to support coastal resilience, environmental stewardship, and operational effectiveness. The pilot’s results lay the groundwork for future implementations that will empower coastal communities and maritime stakeholders to make better, faster, and more informed decisions.
III. Keywords
The following are keywords to be used by search engines and document catalogues.
fmsdi, intertidal, vertical datum, coastal, land, hydrospatial
IV. Contributors
All questions regarding this submission should be directed to the editor or the submitters:
| Name | Affiliation |
|---|---|
| Stelios Contarinis | HARTIS Integrated Nautical Services |
| Christos Kastrisios | University of New Hampshire / HARTIS |
| Craig Coffin | Compusult |
| Matthew Purss | Pangaea Innovations |
| Ross Smith | TCarta |
| Caroline Levey | OceanWise |
| Glenn Laughlin | Pelagis Data Solutions |
| Rob Thomas | Open Geospatial Consortium |
| Trevor Taylor | Open Geospatial Consortium |
V. Future Outlook
Looking ahead, the FMSDI 5 Pilot sets the stage for broader adoption of federated, standards-based marine spatial data infrastructures that can dynamically integrate land and sea datasets. Future initiatives will focus on operationalizing demonstrated approaches such as DGGS-based indexing, semantic uplift, and real-time EO-derived shoreline updates, enabling seamless interoperability across agencies and jurisdictions. Emphasis will also be placed on aligning with global initiatives like the UN-GGIM IGIF-H and the IHO S-100 framework, supporting climate resilience, coastal planning, and maritime safety.
The Draft Best Practice Report developed during the pilot will be expanded and refined in future collaborative work to produce a final version. This will consolidate implementation guidance and promote consistent, standards-aligned approaches to coastal data integration. Continued adoption of open frameworks and modular architectures will support the evolution of a Marine SDI that is adaptable, coordinated, and designed for long-term interoperability.
VI. Value Proposition
The FMSDI 5 Pilot demonstrates the practical and strategic value of a federated, standards-based approach to integrating land and marine geospatial data across the intertidal zone. By enabling seamless interoperability through open APIs, semantic uplift, and dynamic indexing systems like DGGS, the pilot empowers agencies to make faster, data-driven decisions in navigation safety, coastal planning, and environmental management. It reduces redundancy, enhances data usability across jurisdictions, and lays the groundwork for more resilient and efficient marine spatial data infrastructures that can support both public and private sector needs.
1. Introduction
The fifth version of the Federated Marine Spatial Data Infrastructure (FMSDI5) Pilots addresses one of the most complex challenges in geospatial data management—data integration at the land-sea interface. This interface represents the transitional zone where land-based and marine-based data systems meet. Differences in data standards, methodologies, scaling, and spatial-temporal coverage across agencies create significant interoperability barriers. Dynamic natural processes, such as tidal shifts, erosion, sedimentation, and human activities, further reshape the intertidal zone, adding to the complexity.
1.1. Aims
The initiative explores innovative methods to unify disparate datasets and models into consistent workflows. It highlights practical solutions through demonstrators and prototypes that align with international geospatial standards. These efforts are grounded in real-world scenarios that emphasize interoperability across agencies and domains.
This report (D001) compiles the outcomes, lessons learned, and experiences from the Pilot. The content emphasizes:
Key challenges and practical solutions for integrating terrestrial and marine geospatial data across the intertidal zone.
Technical and organizational contributions of participating stakeholders and solution providers.
Technology demonstrator platforms that showcase cross-domain data interoperability through open standards and APIs.
Recommendations to support global alignment of land-sea data integration efforts with evolving standards and frameworks.
A Draft Guide and Best Practices Report (D002) to aid organizations in addressing the complexities of merging data at the land/sea interface.
1.2. Objectives
The FMSDI Pilot focuses on two primary objectives:
Defining best practices for achieving seamless data interoperability across land-sea boundaries.
Developing dynamic data integration approaches that enable near real-time, lossless conflation of terrestrial and marine datasets.
2. Background
2.1. The Land/Sea Interface: Definition and Importance
The inter-tidal and nearshore region, also referred to as the “white ribbon”, is the area of the shoreline that alternates between being exposed to air during low tide and submerged underwater during high tide. This dynamic region serves as the boundary between terrestrial and marine ecosystems and undergoes constant changes due to tidal cycles.
Figure 1 — Natural shoreline gradation illustrating the land-sea interface. Source: NSW Department of Primary Industries – Fish Habitat Network.
The intertidal zone holds significant ecological importance as a habitat for a diverse array of species, including plants, animals, and microorganisms that are uniquely adapted to survive in both aquatic and terrestrial conditions. It supports intricate food webs, provides breeding grounds for marine species, and functions as a natural filter by trapping sediments and processing nutrients, thereby enhancing water quality.
Economically, the intertidal zone contributes through resources such as fisheries, aquaculture, and tourism. It also plays a crucial role in coastal protection by absorbing wave energy and mitigating the impacts of storm surges. Environmentally, this zone offers valuable insights into changes such as sea-level rise, erosion, and the effects of climate change. It serves as a natural laboratory for studying sediment dynamics, coastal morphology, and the interaction of biological and physical processes.
The intertidal zone also holds cultural and recreational value, being a space for traditional practices, heritage activities, and leisure pursuits like fishing and tide pooling. Furthermore, it is pivotal for sustainable coastal zone management and urban planning, influencing policies related to conservation, development, and disaster mitigation.
2.2. Tides Geography
Tides, as well known, are the periodic rise and fall of sea levels caused primarily by the gravitational forces exerted by the Moon and the Sun on Earth. The interaction of these forces with Earth’s rotation generates tidal bulges in the oceans. As Earth rotates, these bulges shift, creating the high and low tides experienced along coastlines. The Moon’s gravitational pull has the most significant influence, with the Sun’s gravity acting as a secondary force, modifying the intensity of tides depending on their alignment with Earth.
Tidal patterns vary globally due to factors such as the Earth’s tilt, ocean basin shapes, and coastal configurations. There are three main tidal patterns: diurnal, semidiurnal, and mixed. Diurnal tides consist of one high and one low tide each day, common in locations like the Gulf of Mexico. Semidiurnal tides, observed in areas like the Atlantic coast, feature two high and two low tides of approximately equal height within a day. Mixed tides, prevalent in the Pacific, display two high and two low tides of unequal height daily.
Spring and neap tides further illustrate tidal variability. Spring tides occur during full and new moons when the Sun, Moon, and Earth align, amplifying tidal forces and resulting in higher high tides and lower low tides. Conversely, neap tides occur during the first and third quarters of the lunar cycle when the Sun and Moon are at right angles to Earth, diminishing tidal effects and producing lower high tides and higher low tides.
Local geography plays a significant role in shaping tidal behavior. Coastal and underwater topography can amplify tidal ranges in narrow inlets, bays, or estuaries, leading to phenomena like tidal bores. In contrast, open ocean regions may experience minimal tidal changes due to the lack of such constraining features.
In addition to the vertical rise and fall of water, tides generate tidal currents, which are horizontal water movements associated with changing tides. Flood currents carry water inland as the tide rises, while ebb currents move seawards as the tide falls. These currents influence sediment transport, nutrient cycling, and coastal erosion, making them essential to both natural processes and human activities.
Tidal patterns are also subject to long-term variations due to factors such as Earth’s axial tilt, orbital eccentricity, and the reshaping of ocean basins. Over decades or centuries, these changes can alter tidal ranges and frequencies, impacting coastal ecosystems and infrastructure.
The effects of climate change are expected to amplify tidal impacts. Rising sea levels will increase the baseline water level, intensifying high tides and making low-lying areas more vulnerable to flooding. These shifts highlight the importance of understanding and predicting tidal behavior to mitigate risks and protect coastal environments.
2.3. Challenges in Harmonizing Land and Marine Data
Harmonizing land and marine data presents numerous challenges stemming from the distinct approaches, priorities, and methodologies of the respective communities. One significant challenge lies in differing scaling practices. Land data often focuses on localized, high-resolution features, while marine data typically emphasizes broader, regional scales to accommodate vast oceanic expanses. This disparity complicates efforts to create consistent models that accurately represent both environments.
Temporal aggregation poses another obstacle. Terrestrial data may prioritize long-term trends and static features, whereas marine data often requires high-frequency updates to account for dynamic conditions such as tides, currents, and seasonal variations. Aligning these temporal frameworks is essential but requires sophisticated integration techniques to avoid information loss or misrepresentation.
Data density further complicates harmonization efforts. Land data is frequently collected at a high density in urban or economically significant areas, while marine data often suffers from uneven coverage, especially in remote or deep-sea regions. This uneven distribution results in gaps that hinder the creation of comprehensive, interoperable datasets.
Figure 2 — Land/Sea Data Integration Challenges
This diagram summarizes key technical challenges in the integration of intertidal data—an area that inherently lies at the boundary between land and sea. It highlights five interrelated categories of complexity:
Multiple Data Types: The integration of raster (e.g., satellite imagery), vector (e.g., coastline polygons), point cloud (e.g., lidar), and time-series (e.g., tide gauges) data requires harmonization at both structural and semantic levels.
Multiple Resolutions: Land datasets often feature high-resolution detail for infrastructure or cadastral purposes, while marine datasets may generalize features for navigational safety. This leads to scale mismatches and spatial discontinuities when aligning features across the shoreline.
Multiple Vertical Datums: Differences in reference surfaces—such as Chart Datum, Mean Sea Level (MSL), and ellipsoidal heights—must be reconciled to merge terrestrial and bathymetric data. This is especially important in intertidal zones where elevation differences define feature visibility and interpretation.
Multiple Dimensions: Intertidal data is not static. Elevation, time, and uncertainty are critical dimensions in feature representation, requiring support for 4D spatio-temporal models in analysis and display.
Multiple Governance Frameworks: Land and marine environments are managed by different organizations and jurisdictions, often operating under separate legal mandates. Issues include mixed or split accountabilities, differing legal frameworks, inconsistent standards and tools, lack of coordination, and mismatched funding or prioritization.
These challenges are inherently interdependent. Solving one often exacerbates or reveals others. For instance, transforming data to a common vertical datum may expose inconsistencies in resolution or sampling frequency. The cyclic nature of these challenges reinforces the need for integrated strategies and holistic data models.
In addition semantic differences in terminology, data quality standards, and methodologies across agencies exacerbate the challenge.
3. Data Integration Strategies
3.1. Semantic Uplift and Mapping for Cross-Domain Transformation
Harmonizing data between the land and marine domains involves addressing several intricate challenges to achieve seamless interoperability. One of the key aspects is the need for semantic uplift and the application of mapping rules for cross-domain data transformation. The complexity is heightened by the need to address differences in scaling, temporal aggregation, and data density between land and marine datasets. These challenges require innovative approaches and tools to ensure that data integration occurs with minimal loss of information and maximum fidelity to the original datasets.
Semantic uplift is an essential process in cross-domain data transformation, where data from one domain is enriched to align with the conceptual models and semantics of another domain. This ensures that data originally designed for land or marine applications can be accurately interpreted and utilized in the other domain with minimal information loss.
Semantic uplift involves adding context, metadata, and attributes to the source data to enhance its expressiveness and compatibility. For example, a marine dataset describing bathymetric features might require additional annotations to align with terrestrial elevation models, such as vertical datum transformations or feature type classifications.
Mapping rules form the foundation of the transformation process, defining how features, attributes, and relationships in the source data correspond to those in the target domain. These rules ensure consistent and predictable data conversion and typically include:
Feature Type Mapping: Identifying equivalent or analogous feature types between land and marine datasets (e.g., mapping “seafloor elevation” to “topographic contour”).
Attribute Transformation: Converting attributes to match the target domain’s specifications, such as units of measurement or coordinate systems.
Contextual Translation: Applying domain-specific knowledge to interpret and adapt data, such as linking marine habitat classifications with terrestrial land use categories.
Data Quality and Constraints: Preserving or recalibrating quality metrics and constraints to maintain data integrity after transformation.
3.2. Minimizing Information Loss in Dynamic Data Integration
Integrating dynamic data across land and marine domains requires employing strategies that minimize information loss. This is essential when dealing with datasets that differ in resolution, temporal scales, and semantic contexts. Several approaches support preserving data fidelity and usability:
Enriching Data with Semantic Uplift: Adding context, metadata, and attributes to source data ensures alignment with the target domain’s conceptual model, preserving critical information during transformation.
Defining Standardized Mapping Rules: Establishing clear mapping rules guides transformations by accounting for feature types, attribute conversions, and domain-specific semantics, ensuring accurate translation of information.
Using Hierarchical Aggregation: Employing hierarchical structures to aggregate or disaggregate data when transitioning between resolutions or scales minimizes detail loss while maintaining compatibility.
Analyzing Error Propagation: Tracking and quantifying errors during integration helps identify potential points of information loss, allowing for necessary adjustments to reduce their impact.
Interpolating and Filling Gaps: Using advanced interpolation techniques addresses missing values, ensuring spatial and temporal continuity without compromising the integrity of the original data.
Establishing Quality Metrics: Defining cross-domain metrics ensures integrated datasets meet standards for accuracy, resolution, and consistency.
Validating Iteratively: Continuously validating integrated data against benchmarks or through expert reviews helps identify and resolve discrepancies early in the process.
Leveraging Standards and Frameworks: Employing international standards, such as OGC Web API frameworks, facilitates structured integration, reducing potential loss during transformation.
4. Best Practices Development
The D002 Draft Guide and Best Practices Report outlines a practical path forward for improving the integration of land and sea datasets—particularly in the dynamic and often underrepresented intertidal zone. It builds on globally recognized frameworks such as the IHO S-100 series, OGC standards, and the UN-GGIM IGIF-Hydro strategy.
At the core of this report are five interlinked best practices designed to transform fragmented or siloed coastal data into cohesive, usable resources that support real-world decision-making.
These best practices were developed through collaborative input from domain experts, national mapping agencies, and hydrographic offices involved in the pilot. Their formulation was informed by extensive dialogue with stakeholders from the sponsoring organizations and other institutions across Canada, the UK, and the US. The practices are grounded in operational implementations, cross-jurisdictional governance experiences, and a detailed evaluation of interoperability challenges encountered in the intertidal zone.
They emerged from in-depth analysis of use cases—such as coastal inundation modelling—and are closely aligned with international frameworks like IGIF-Hydro, as well as standards including ISO 19115, S-100, and GeoDCAT. Collectively, they address persistent issues in vertical referencing, metadata harmonization, data accessibility, and fragmented governance.
4.1. Best Practice 1: Unified Geospatial Reference
Accurate integration of coastal data requires all observations—whether from land or sea—to reference a common geodetic framework. Disconnected vertical and horizontal datums between topographic and hydrographic datasets remain one of the most persistent technical barriers to land-sea integration. This is especially critical in the context of coastal inundation modelling, where mismatches in reference systems can lead to significant errors in flood risk assessments.
A Geodetic Reference Frame provides the essential baseline for referencing features consistently across land, sea, and the coastal interface. Best practices emphasize the use of a modern vertical control network, incorporating GNSS Continuously Operating Reference Stations (CORS) and geoid-based height systems. These allow elevation data—such as those from LiDAR or bathymetric sonar—to be referenced to a gravity-based vertical datum, minimizing distortions from local tidal or ellipsoidal frames.
To harmonize datasets:
Apply vertical separation surfaces to transform between ellipsoidal, geoidal, and tidal datums.
Prefer the geoid as the zero-height reference surface for coastal modelling.
Where national models exist (e.g., NOAA’s VDatum, UKHO’s VORF, CHS’s HyVSEPs), use these to ensure consistent height referencing across domains.
Always record the datum, epoch, transformation method, and vertical orientation convention in metadata.
Land-sea elevation integration is not just about technical accuracy—it’s foundational for delivering trustworthy, interoperable datasets that can support planning, risk reduction, and long-term resilience. Without a unified reference frame, even the most advanced models or visualizations risk misrepresenting reality.
4.2. Best Practice 2: FAIR Data Principles
Ensure datasets are Findable, Accessible, Interoperable, and Reusable (FAIR) by providing comprehensive metadata and aligning with established international standards. When working across land and sea domains, metadata plays a critical role in determining whether data is fit for purpose—particularly when sources differ in coordinate systems, data quality, or lineage.
Each data product should:
Be accompanied by metadata compliant with ISO 19115 (Geographic Metadata) or national profiles (e.g., UK GEMINI), including spatial reference systems, vertical datums, accuracy, lineage, and acquisition methods.
Clearly describe data quality indicators and uncertainty metrics, especially for elevation datasets.
Follow ISO 19131 Data Product Specification for defining intended use and requirements of datasets.
Include transformation history and any associated accuracy degradation when converting between coordinate systems.
To enable machine-readable access and discovery:
Register datasets in federated catalogs using standards like GeoDCAT-AP or OGC API — Records.
Prefer formats and services that support structured discovery, such as WMS/WCS, OGC Tiles, or linked data endpoints.
Where applicable, formats like Bathymetric Attributed Grid (BAG) should be used to encapsulate both elevation and vertical uncertainty in a single product.
Adhering to FAIR principles reduces duplication, supports AI-enabled workflows, and builds long-term value into your coastal datasets through transparency and reusability.
4.3. Best Practice 3: Mind the Gap
The “white ribbon”—the intertidal zone between land and sea—is often poorly surveyed due to overlapping jurisdictional responsibilities and challenging environmental conditions. This results in persistent data voids that hinder coastal modelling, flood risk assessments, and infrastructure planning.
Where land and marine datasets do not overlap:
First attempt to fill the gap with new observations, such as:
Satellite-derived elevation (e.g., stereo imagery, SDB)
Airborne LIDAR, especially topo-bathy systems
Targeted local surveys using sonar or UAV platforms
If fresh acquisition is not feasible, interpolation techniques (e.g., triangulation, cubic spline) may be applied. However:
These methods should be selected based on the geomorphology of the area.
Introduced artefacts or assumptions must be clearly documented.
Error metrics and confidence levels should be quantified and included in metadata.
Note that interpolation is a last resort. While cost-effective, it risks misrepresenting seabed morphology, especially in dynamic coastal systems.
When filling gaps:
Prefer integration of OGC-compliant formats (e.g., GeoTIFF, 3D Tiles)
Use point or vector-based data as a foundation for creating TIN models, which preserve accuracy better than raster up/downsampling
Record all processing steps and assumptions to support data transparency and downstream usage
Closing the white ribbon gap ensures spatial continuity, improves model fidelity, and supports decision-making across land-sea interfaces.
4.4. Best Practice 4: Coordinated Governance
Governance is as critical as technology when it comes to integrating intertidal and coastal data. The coastal zone sits at the boundary of multiple jurisdictions—land agencies, hydrographic offices, environmental authorities—each with different mandates, data standards, and legal frameworks. Without coordinated governance, efforts become fragmented, data remains siloed, and key information gaps persist.
The report emphasizes the importance of:
Shared governance models that clarify roles, responsibilities, and data stewardship across agencies
Legal harmonization across land and marine domains to reduce overlaps, gaps, and contradictions
Multi-agency collaboration, supported by formal agreements, to ensure transparency in data policies, funding, and planning
A recommended framework is the IGIF-Hydro Umbrella Governance Model, which:
Builds on the UN-GGIM’s Integrated Geospatial Information Framework (IGIF)
Aligns national, regional, and local efforts
Promotes interoperable data systems, shared policies, and cross-sector coordination
Adopting such a model enables agencies to:
Reduce duplication of effort
Share authoritative data for planning and emergency response
Support consistent, standards-based coastal data integration across scales
Ultimately, governance must evolve in parallel with technical capability to deliver on the promise of a seamless, resilient, and usable land-sea geospatial infrastructure.
4.5. Best Practice 5: Scalable Resolution Management
Land and marine data are frequently collected at different spatial resolutions, driven by environmental constraints, technology limitations, or differing mandates. Attempting to force uniform resolution across these datasets can result in loss of accuracy, artificial smoothing, or misleading artefacts.
Instead of resampling or generalizing, adopt scalable and flexible data structures that preserve detail where needed:
Use point clouds or vector datasets as foundational inputs to avoid loss from rasterization.
Build TIN (Triangulated Irregular Network) models to interpolate across varying point densities without upsampling.
Consider hierarchical grid systems such as Discrete Global Grid Systems (DGGS) to manage multiscale data integration.
These structures support:
Integration of high-resolution data in critical zones (e.g., flood-prone coastal settlements)
Generalization at regional or national scale for planning and monitoring
On-demand transformation into gridded models for simulation or visualization
When upsampling or downsampling is unavoidable:
Document the transformation methods and any loss of precision
Avoid misleading visual continuity across resolution boundaries
Use caution when interpreting derived products in decision-making workflows
The objective is to retain local accuracy without sacrificing broader context. By embracing resolution-aware methods, practitioners can create continuous coastal elevation models that respect the complexity of source data while remaining usable across diverse applications.
4.6. Supporting Content
For expanded technical context, implementation guidance, and case-based insights, refer to the full Draft Guide and Best Practices Engineering Report (~39 pages, 30–40 min read). It covers:
Topo-bathymetric surface integration techniques
Data product specifications and quality standards
Governance and institutional models
Geodetic reference frames and vertical transformation methods
Audience-focused implementation approaches and design principles
A case study on coastal inundation modelling
Appendices covering:
Communities of Practice (UK, Canada, US)
Land and marine data characteristics
Future directions (e.g., vertical land motion, semantic alignment)
Comparison of S-57 and land data (UK)
Introduction to Discrete Global Grid Systems (DGGS)
You may access the full report here: Read Online (HTML) | Download PDF
5. Technical Demonstrations
To validate and operationalize the best practices outlined above, three technical demonstrations were conducted by pilot participants. These demonstrations explore real-world challenges and solutions in harmonizing terrestrial and marine geospatial data in intertidal and coastal zones. Each prototype highlights specific aspects of integration—ranging from vertical referencing and data interoperability to decision support and monitoring systems.
The demonstrations reflect the capabilities of different platforms and partners working within varied coastal environments. They serve as practical examples of how the best practices can be applied to support coastal resilience, hazard mitigation, and spatial planning at both national and regional scales.
The following sections summarize the purpose, implementation, and outcomes of each demonstration.
5.1. Compusult (D100): Coastal Erosion Monitoring and Prediction
5.1.1. Purpose
The purpose of Compusult’s demonstration for this project is to showcase the integration of terrestrial and marine data sets into a unified operational picture, and to explore challenges encountered when integrating land and sea data from heterogeneous sources.
Figure 3 — Examples of Land-Sea Data Integration
5.1.2. Scenario Description
The demonstration illustrates two primary use cases leveraging Compusult’s Web Enterprise Suite (WES) platform.
5.1.2.1. Land and Sea Data Integration Scenario
In this scenario, a geospatial analyst integrates terrestrial and marine data from multiple sources into a common operational picture.
WES is utilized to create data portfolios centered on thematic or geographic areas of interest. For this demonstration, two portfolios were created: one for The Solent (UK) and one for Chesapeake Bay (USA). Diverse land and sea datasets have been harmonized into a unified map-based view.
5.1.2.2. Vessel Navigation Scenario
In this scenario, a search and rescue vessel with a draught of 1 meter must navigate the intertidal waters of The Solent.
Compusult’s implementation of an OGC API Process and OGC API Map facilitates identification of navigable waters based on terrain elevation, bathymetric soundings, and tidal conditions. A similar approach was applied to the Chesapeake Bay region.
5.1.3. Technical Objectives
The technical objectives were to:
Aggregate terrestrial and marine data from disparate sources into a unified operational picture.
Prototype an OGC API Process combining land and sea data for navigability analysis in intertidal zones.
Demonstrate the application of OGC standards for dynamic, standards-based spatial querying and visualization.
An instance of WES was configured to serve as the demonstration platform for these objectives.
5.1.4. Platform
Figure 4 — Web Enterprise Suite (WES)
Compusult’s Commercial-Off-The-Shelf (COTS) Web Enterprise Suite (WES) serves as the demonstration platform.
WES is a modular system built upon Open Geospatial Consortium (OGC) and ISO standards, supporting integration with a wide variety of commercial and open-source geospatial tools and services.
Web Enterprise Suite product information is available at https://www.webenterprisesuite.com.
The WES demonstration portal for FMSDI 5 can be accessed at https://wes-ogc.compusult.com.
5.1.4.1. Data Integration Portfolios
Two thematic portfolios were developed to demonstrate land and sea data integration:
5.1.4.1.1. The Solent, UK
The portfolio integrates datasets from:
Ordnance Survey Maps API
UKHO S-102 Bathymetric Surface
UKHO Seabed Mapping Service
UKHO Wrecks and Obstructions (Shapefiles)
Figure 5 — Data Integration Portfolio - The Solent, UK
5.1.4.1.2. Chesapeake Bay, USA
The portfolio integrates datasets from:
US Geological Survey (USGS) Imagery Topo Map
NOAA National Geodetic Survey (NGS) Continually Updated Shoreline Product (CUSP)
NOAA Historical Composite Shoreline
Figure 6 — Data Integration Portfolio - Chesapeake Bay, USA
5.1.4.2. Vessel Navigation Visualization
The vessel navigation service implements an OGC API Process and OGC API Map to visualize navigable waters in intertidal zones of The Solent and Chesapeake Bay.
5.1.4.2.1. OGC API – Processes
An OGC API Process calculates navigable and non-navigable waters.
User inputs include:
Area of interest
Vessel draught (in meters)
Simulated tidal surge (in meters)
Date and time (for historical tide data)
Datasets used:
Digital Elevation Model derived from National Coastal Asset Register
UKHO Admiralty Seabed Mapping Service bathymetry
OceanWise tidal data (real-time and historical)
Figure 7 — Process Wizard
5.1.4.2.2. OGC API – Maps
The vessel navigation process outputs an OGC API Map:
Navigable waters shown in blue
Non-navigable waters shown in red
Intertidal zones represented with a light gray ribbon
Figure 8 — Vessel Navigation Scenario Map
5.1.4.2.3. Cesium 3D Map Client
The WES 3D client visualizes the vessel navigation scenario in a three-dimensional environment using CesiumJS.