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Data Services for the Digital Earth

TerraNexus OGC Federated Marine Spatial Data Infrastructure 2025 - Project Demonstrator

Connecting the Land and the Sea with DGGS

The Challenge of the Intertidal Zone

The Intertidal Zone is a very challenging environment, both from the environmental and the data integration challenge perspectives. Environmentally, this is a highly dynamic setting which is constantly changing - sometimes quite violently. And, this significantly affects both our population as well as our local and global economies. Especially with the increased volatility we are experiencing and expecting to increase in response to Human Induced Climate Change.

To better understand and mitigate the risks and impacts of climate change affecting our coastal communities we are collecting an every increasing amount of data from an every increasing number of sources. This creates some real challenges for us, because these data are diverse, collected by multiple organisations, using multiple equipment and methods of collection across a wide range of data resolutions and spatial contexts.

This creates silos and incompatabilities between data collections. But, to solve the environmental, societal and economic challenges the intertidal zone presents we need to be able to use all of these data to derive useful and actionable knowledge and insights. And, the conventional approach to data integration challenges requires all of the data to be "harmonised" first before we can ask the questions we need of it. This approach is difficult to scale and is not sustainable.

Our Approach

At Pangaea Innovations we take an alternate view to the data challenge. Rather than working harder to solve the data interoperability problem using the conventional approach, we are re-imagining the way data can be brought together. Because of this we are pioneers in the development, implementation and standardisation of Discrete Global Grid Systems (DGGS).

DGGS technologies provide a common and simple way for us to search, discover and integrate spatial data without having to continually perform complex, inefficient and, in some cases, error creating spatial transformation operations. As a spatial data infrastructure DGGS are unique in that they are not defined or tuned to the data. This means that all data indexed by a given DGGS can be easily integrated regardless of their data formats, data resolution, data type and spatial context (i.e. horizontal, vertical and temporal coordinate reference systems).

Our approach to this project has been to explore and test the ability and effectiveness of using DGGS technologies, via our TerraNexus DGGS platform, to index, search and enable integration of terrestrial and marine data collections across the intertidal zone. This has involved an assessement of the value proposition presented by different classes of DGGS - from 2D, to 3D, and ultimately to 4D (3D + time).

Because of the superiority of 4D DGGS over 2D and 3D DGGS in addressing the FMSDI challenge our demonstrator (presented here) will primarily focus on showcasing the use of our TerraNexus 4D DGGS.

Technical Objectives

The Technical Objectives for Pangaea Innovations under this project were primarily to explore the specific data integration challenges that impact the ability to discover and integrate both terrestrial and marine data across the Intertidal Zone, whilst maintaining data integrity and fidelity (i.e. without needing to harmonise data first before any spatial and semantic questions can be asked). Our focus was to implement a DGGS-based mechanisms to connect these data via DGGS Zone Identifiers (i.e. Zone Indices).

The key challenges we focused on include:

  • Horizontal and Vertical Datum variations between data collections

  • Data format differences between data collections

  • Describing and representing building infrastructure data collections as 3D (and 4D) objects that can be properly referenced and indexed by a DGGS.

  • Exploring the Pros and Cons of applying 2D, 3D and 4D (3D+time) DGGS infrastructures to the intertidal zone data interoperability Challenge.

Platform Information

The TerraNexus FMSDI5 demonstrator leverages a CesiumJS application viewer embeded into a Django web application. This is a simple viewer that enables users to perform OGC API DGGS opperations to query the TerraNexus DGGS enabled data stores of relevant project data collections. The returned query responses are automatically presented to the user in 4D via the CesiumJS viewer.

The viewer enables users to drive space-time interogation of data in the specified areas of interest via DGGS index queries rather than complex space-time operations (which require data to be harmonised first before any queries can be successfully applied).

The DGGS Query operation(s) are driven via the "controls" toolbox located in the top right hand corner of the Viewer. This toolbox includes drop-down control panels to adjust visual aspects of the Viewer and the OGC API DGGS ZoneQuery input parameters.

This Button (located at the top of the "controls" toolbox) executes the OGC API DGGS ZoneQuery operation. The query parameters are configured in the "DGGS Query Parameters" section below.

This query will send an API request to the TerraNexus OGC API DGGS Server. The resonse will be a JSON document that includes a list of DGGS Zones successfully returned by the Query and a list of "links" and "link_templates" that refer to the collections that are indexed by these DGGS Zones.

The Viewer will parse this response document and automatically send off OGC API DGGS ZoneInfo and ZoneData queries to:

  • Get the DGGS Zone Geometry information for each Zone from TerraNexus.

  • Get the data associated with each Zone from the TerraNexus data collections store.

The returned information is then visualised by the Viewer.

This is useful to show data and DGGS Zone boundaries that extend below the surface representation of the Earth in the Viewer.This Control Panel includes controls to:

  • Show/Hide the Oceans

  • Adjust the level of opacity/transparency of the Earth.

  • Make the surface of the Earth Translucent.

This toolbox enables the Area of Interest Bounding Boxs displayed by the Viewer to be Shown or Hidden. This is useful to be able to better see data and DGGS Zones that are obscured by the Area of Interest Bounding Box(s).

Options include toggles to show/hide:

  • All Areas of Interest

  • Major Areas of Interest

  • Minor/Detailed Areas of Interest

There is also a selector that enables a user to choose an Area of Interest and then Zoom to that Area of Interest in the Viewer.

This toolbox enables the user to specify input parameters to include in the OGC API DGGS ZoneQuery operation.

Options/paremeters include:

  • Selection of the Discrete Global Grid Reference System (DGGRS) to query.

  • Selection of a Pre-Defined Area of Interest

    This will pre-fill the Bounding Box Extends for the Query based on the extents of the selected Area of Interest.

  • Custom Area of Interest Specification

    This enables a user to specify the parameters to define a custom 2D or 3D Area of Interest using the input fields for "Minimum Longitude", "Minimum Latitude", "Maximum Longitude", "Maximum Latitude", "Minimum Ellipsoidal Height" and "Maximum Ellipsoid Height"

  • DGGS Grid Refinement Level

  • Minimum Time

  • Maximum Time

  • A checkbox to select whether, or not, to show only DGGS Zones that are mapped to collection data (i.e. only show zones where the data has been indexed to the DGGS Zone)

  • A checkbox to select whether, or not, to show DGGS Zone Geometries

  • A checkbox to select whether, or not, to show DGGS Zone Boundary Wireframes

  • A checkbox to select whether, or not, to show DGGS Zone Meshes (i.e. a "solid" representation of the DGGS Zone(s))

The Southampton and Solent region presents distinctive intertidal challenges that significantly impact maritime operations, environmental management, and infrastructure maintenance. The complex interaction between the double high water phenomenon (M4/M2 harmonic interactions) and the extensive intertidal zones creates unique operational challenges for anyone working at the land-sea interface in this region.

Primary Intertidal Characteristics

The region's intertidal areas are characterized by extensive mudflats and salt marshes, particularly in Southampton Water. These areas experience variable exposure patterns due to the double high water effect, where the tide appears to pause during its ebb. This creates extended periods of high water, fundamentally affecting how the intertidal zone behaves compared to other coastal regions.

Infrastructure Implications

The port infrastructure in Southampton faces particular challenges due to these intertidal conditions. The extended high water periods affect inspection and maintenance schedules for quay walls, dock structures, and marine terminals. The frequent cycling between wet and dry conditions accelerates infrastructure degradation, especially in the splash zone where corrosion risks are highest.

Navigation Considerations

The dynamic nature of the intertidal zone directly impacts navigation. The extensive mudflats in Southampton Water influence channel characteristics, requiring careful monitoring of sediment movement patterns. This becomes particularly critical in areas where the navigable channel margins interact with intertidal zones, affecting both commercial shipping and recreational vessel operations.

Environmental Management

The region contains significant protected intertidal habitats, including the Solent Maritime Special Area of Conservation. These areas require careful management as they provide essential ecosystem services and support diverse wildlife populations. The interaction between port operations and these sensitive environments presents ongoing management challenges, particularly regarding erosion control and habitat preservation.

Operational Adaptations

To address these challenges, port operations must integrate precise understanding of the intertidal zone dynamics. This includes scheduling maintenance activities during optimal tidal windows, managing sediment accumulation in berthing pockets, and ensuring safe access to marine structures. The double high water phenomenon provides unique operational windows but also requires more complex planning for activities in the intertidal zone.

The Chesapeake Bay, North America's largest estuary, contains extensive intertidal zones where traditional data management approaches face significant challenges. These include pronounced data discontinuity between terrestrial and marine domains, complex temporal variations from tidal cycles and seasonal changes, inconsistent resolutions and projections across diverse data sources, and substantial difficulties in integrating oceanographic, meteorological, ecological, and anthropogenic datasets. These integration challenges hamper comprehensive understanding and effective management of this dynamic ecosystem, requiring innovative approaches to synthesize information across the land-water interface.

Primary Intertidal Characteristics

The Chesapeake Bay exhibits a variable tidal range (0.6-2.8 feet) creating subtle but critical elevation gradients. Substrate diversity ranges from sandy beaches along the eastern shore to mudflats in the upper Bay, supporting varied benthic communities. Vegetation displays distinct zonation patterns with Spartina alterniflora dominating daily-flooded low marshes and Spartina patens prevailing in high marsh areas. This environment demonstrates significant temporal dynamism through seasonal salinity shifts, winter ice effects in northern regions, episodic storm reshaping, and long-term habitat migration responding to environmental changes.

Infrastructure Implications

Traditional hardened shorelines eliminate habitat and redirect erosion, while aging infrastructure faces increasing climate stresses with adaptation costs exceeding $1.8 billion for public assets. Stormwater systems experience tidal backflow, reducing drainage capacity during high tides and worsening urban flooding. Utilities face accelerated corrosion, storm surge vulnerability, and maintenance access challenges. Transportation networks contend with nuisance flooding, bridge scour, and compromised evacuation routes during combined high tide and storm events.

Navigation Considerations

Shifting sediment patterns alter channels and increase dredging needs while reducing nautical chart reliability. Tide-dependent access restricts marina use, commercial fishing operations, and creates safety hazards for recreational boaters. Navigation aids become less reliable as conditions change, while increased turbidity reduces hazard visibility. Moorage infrastructure requires significant adaptation, with fixed docks becoming less functional and floating structures needing enhanced storm protection as anchorages experience altered holding conditions.

Environmental Management

Intertidal zones fall under overlapping regulatory jurisdictions with inconsistent permitting processes across agencies and localities. Monitoring efforts struggle with temporal and spatial coverage limitations, while restoration designs must balance immediate habitat needs against long-term sustainability under changing climate conditions. Stakeholder engagement is complicated by property rights concerns, cultural attachments to traditional practices, environmental justice considerations, and challenges in economically valuing ecosystem services.

Operational Adaptations

Management approaches are evolving toward adaptive frameworks with early warning systems and real-time monitoring networks. Infrastructure modifications increasingly incorporate "tide-smart" designs, including alternative routing systems, backflow prevention, raised critical facilities, and relocatable structures for high-risk areas. Data integration advances through common standards across terrestrial and marine programs, while education initiatives update emergency responder training, inform waterfront property owners about adaptation options, and build public support for nature-based solutions and managed retreat where necessary.

Pros

  • Surface (2D) DGGS partition the entire Earth into a hierarchy of global grids, each with equal area cells (or "Zones") at finer and finer resolution.

  • The DGGS Zones that make up the Discrete Global Grid Hierarchy all have common and simple geometries (e.g. triangles, quadrilaterals, hexagons, etc...)

  • Each DGGS Zone is uniquely indexed. This allows for rapid and immutable spatial queries to be achieved through a single index lookup rather than a complex series of spatial operations.

  • The consistency between DGGS Zones enables data and query processes to be scaled up by leveraging massively parallel "Big Data" operations.

  • Benchmark testing on the TerraNexus Surface (2D) DGGRS show an ~80% to 99% efficiency improvement for the "Point in Polygon" spatial query operation.

Cons

  • Surface (2D) DGGS only index the lateral surface dimensions (e.g. x,y or longitude, latitude) of the Earth.

  • The Discrete Global Grid Hierarchy of a Surface (2D) DGGS is fixed to the surface of the Earth Model (i.e. ellipsoid or authalic sphere). This limits the ability to apply highly efficient index-based search operations to 3D data - which is the actual coordinate context of all spatial data.

  • This means that height and/or temporal dimensions of data are not able to leverage the massive efficiency improvements that DGGS index operations enable.

  • Height Datum differences between datasets and data collections cannot be directly addressed using Surface (2D) DGGS indexing. Data transformation and resampling still MUST occur first in order to search for and find spatially coincident data across the intertidal zone.

Pros

  • Volumetric (3D) DGGS, like Surface (2D) DGGS, partition the entire Earth into a hierarchy of global grids, each with equal sized cells (or "Zones") at finer and finer resolution. However, 3D DGGS partition the entire Earth and not just its surface.

  • The DGGS Zones that make up the Discrete Global Grid Hierarchy all have common and simple geometries (e.g. triangular prisms, quadrilateral prisms, hexagonal prisms, etc...)

  • Each DGGS Zone is uniquely indexed. This allows for rapid and immutable spatial queries to be achieved through a single index lookup rather than a complex series of spatial operations.

  • The consistency between DGGS Zones enables data and query processes to be scaled up by leveraging massively parallel "Big Data" operations.

  • Height Datum differences between datasets and data collections can now be directly addressed using Volumetric (3D) DGGS indexing.

  • Benchmark testing on the TerraNexus Volumetric (3D) DGGS to the 3D extension of the "Point in Polygon" data integration test is yet to be done. However, given the exponential increase in the problem (compared to the 2D case), and the requirements of conventional approaches to solve it, we expect to see a very similar (if not greater) improvement in data query performance from the TerraNexus Volumetric (3D) DGGS.

Cons

  • Volumetric (3D) DGGS are able to only index the spatial component of a data observation. Conventional approaches to include time-based queries of datasets and data collections are still required in order to perform full "space-time" queries of data.

  • This means that temporal dimensions of data are not able to leverage the massive efficiency improvements that DGGS index operations enable.

  • Increased care must be taken when creating tiled and/or pyramid resolution views of data based on the zones of a Volumetric (3D) DGGS. This is especially true for feature data collections.

Pros

  • Spatio-Temporal (4D) DGGS, like Surface (2D) and volumetric (3D) DGGS, partition the entire Earth into a hierarchy of global grids, each with equal sized cells (or "Zones") at finer and finer resolution. However, 4D DGGS partition the entire Earth through a given time period and not just in 2D or 3D.

  • The DGGS Zones that make up the Discrete Global Grid Hierarchy all have common and simple geometries (e.g. hypercubes, etc...)

  • Each DGGS Zone is uniquely indexed. This allows for rapid and immutable spatio-temporal queries to be achieved through a single index lookup rather than a complex series of spatio-temporal operations.

  • The consistency between DGGS Zones enables data and query processes to be scaled up by leveraging massively parallel "Big Data" operations.

  • Height Datum differences between datasets and data collections can now be directly addressed using Volumetric (3D) DGGS indexing.

  • Temporal differences between datasets and data collections can now be directly addressed using Spatio-Temporal (4D) DGGS indexing.

  • Benchmark testing on the TerraNexus Spatio-Temporal (4D) DGGS to the 4D extension of the "Point in Polygon" data integration test is yet to be done. However, given the exponential increase in the problem (compared to both the 2D and 3D cases), and the requirements of conventional approaches to solve it, we expect to see a very similar (if not greater) improvement in data query performance from the TerraNexus Spatio-Temporal (4D) DGGS.

Cons

  • Increased care must be taken when creating tiled and/or pyramid resolution views of data based on the zones of a Spatio-Temporal (4D) DGGS. This is especially true for feature data collections, particularly for "static", or long lived features (e.g. Pier Infrastructure at a Port). Without care, the number of zones indexed to a feature can be huge, which presents a potential data volume management challenge.

    Fortunately, it is possible to implement a flexible approach to indexing data across space and time. However, additional research and development activities are necessary to properly define and implement a best practice for tiled/pyramid indexing of feature collections.

Notice

This resource is for demonstration purposes only. It has not been built to be a robust, load-balanced and error-resilient production tool. But as a visual tool to assist potential customers to get a feel of some of the things TerraNexus can do for them.

The backend servers supporting this demonstrator are quite constrained. Performance will vary depending on the load on the TerraNexus server in responding to front-end client operations driven through this Demonstration Viewer.

This may include include partial of fully failed search requests, and may also cause the TerraNexus website to become unresponsive for a period of time.

Please be patient when exploring data using this Demonstration Viewer.