I. Executive Summary
Rising sea levels together with increasing storm surges are amongst the most challenging issues for coastal communities in the context of global warming. The retreating ice sheets of the Circumpolar Arctic are a key contributor to sea level rise with consequences felt around the world.
The Federated Marine Spatial Data Infrastructure (FMSDI) initiative is a key component of OGC and the Marine Domain Working Group. The program is designed to engage with stakeholders from the marine dataspace to identify opportunities to assist, improve, and scale out core business processes complemented by the OGC suite of standards and best practices. The FMSDI-2023 pilot represents the fourth phase of the program with a focus on the interface between land and sea. A primary goal of this pilot is to advance the FMSDI concept to increasing threats posed by climate change.
The project is divided into three threads, each with application to distinct geographies.
Thread 1: Digital Twin of Land and Sea Interfaces — Singapore
With approximately 30% of Singapore’s land mass being less than 5m above sea level, the seamless integration of land and marine data is integral to Singapore’s focus on coastal protection and climate resilience. The management of land and water is separated organizationally between the Singapore Land Authority (SLA) and the Maritime & Port Authority (MPA), respectively. Each agency is responsible for data assets specific to their jurisdiction presenting a challenge for cross-organizational concerns. This theme addresses the geospatial integration requirements through the development of a multi-dimensional Digital Twin of the Singapore coastline.
Thread 2: Digital Arctic Connecting Land and Sea — Canada
This thread addresses the data integration issues in the context of Digital Twins for the Canadian Arctic. With the loss of sea ice, continuing ocean warming, stronger winds and currents, and accelerated shoreline erosion affecting Arctic communities, efficient data usage and analysis is of the utmost importance for Canada.
Figure 1
Thread 3: Integrating Land & Sea for Various Use Cases — Caribbean
This thread investigates how data developed primarily for navigation at sea can be used to better understand the opportunities in the Caribbean to support local capacity building and the application of marine data in expanded sea-land contexts.
Approach
The FMSDI 2023 pilot is managed through the OGC Collaborative Solutions and Innovation (COSI) Program. Each thread is a distinct project with a set of participants tackling specific use cases and scenarios important to the respective project sponsor.
Weekly project meetings are scheduled to encourage collaboration between the participants and sponsors and provide checkpoints to ensure the project scope meets the sponsor’s expectations.
The FMSDI 2023 pilot also features a series of persistent demonstrators as one of its outputs. These demonstrators are workflows and applications that stakeholders can access for outreach, testing, and experimentation purposes. The demonstrators will be available even after the project is completed and are therefore referenced as persistent, but will only be available until December 2024. These demonstrators showcase how geospatial data can be used in an operational context or highlight the gaps in the resources available online, including data sources, metadata, access processes, and standards. As each participant has a unique solution platform, each has taken different approaches, all of which are available for review by stakeholders. Security concerns, such as authentication and authorization, are unique to each participant and have been communicated to stakeholders and participant contacts. For further details and access to the demonstrators, please refer to the link provided.
Common across the three threads is the application of the OGC FAIR principles — Findable, Accessible, Interoperable, and Reusable. Underpinning the use of the FAIR principles is the role of the core OGC Standards and Best Practices. Previous work products related to FMSDI form the core information model while the OGC standards, enhanced through the alignment and support of industry standards such as the IHO S-100 standard, address many of the requirements central to each thread.
Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. The Open Geospatial Consortium shall not be held responsible for identifying any or all such patent rights.
Recipients of this document are requested to submit, with their comments, notification of any relevant patent claims or other intellectual property rights of which the recipients may be aware that might be infringed by any implementation of the standard set forth in this document, and to provide supporting documentation.
II. Keywords
The following are keywords to be used by search engines and document catalogues.
marine, msdi, marineDWG, climate, coastal resilience
III. Contributors
| Name | Organization | Contact | Deliverable(s) |
|---|---|---|---|
| Sina Taghavikish | OGC | staghavikish@ogc.org | Project Manager |
| Rob Thomas | NewFoundView | robert@newfoundview.com | Consultant |
| Glenn Laughlin | Pelagis Data Solutions | glennlaughlin@pelagis.io | D001 Engineering Report |
| D100: Digital Twin of Land and Sea Interfaces — Singapore | |||
| Peng Yue | Wuhan University | pyue@whu.edu.cn | D111 |
| Pascal Broglie | Geomatys | pascal.broglie@geomatys.com | D112 |
| Jérôme St-Louis | Ecere | jerome@ecere.com | D113 |
| Jason MacDonald | Compusult | jasonm@compusult.net | D114 |
| D101/D102: Digital Arctic Connecting Land and Sea — Canada | |||
| Jason MacDonald | Compusult | jasonm@compusult.net | D131 |
| Gordon Plunkett | Esri Canada | gplunkett@esri.ca | D132 |
| Paul Churchyard | HSR.Health | paul@healthsolutionsresearch.org | D133 |
| Glenn Laughlin | Pelagis Data Solutions | glennlaughlin@pelagis.io | D134 |
| D103: Integrating Land & Sea for Various Use Cases — Caribbean | |||
| Stelios Contarinis | Hartis | stelios.contarinis@hartis.org | D121 |
| Andrew Bell | OceanWise | andrew.bell@oceanwise.eu | D122 |
| Paul Churchyard | HSR.Health | paul@healthsolutionsresearch.org | D123 |
| Jason MacDonald | Compusult Limited | jasonm@compusult.net | D124 |
| Ropo Ogundipe | GG-IS | ropo.ogundipe@gg-is.com | D125 |
IV. Acknowledgements
OGC appreciates the continued support from the following member organizations as sponsors of this project.
 Maritime and Port Authority of Singapore (MPA) |  Singapore Land Authority (SLA) |  Natural Resources Canada (NRCan) | ||
 National Oceanic and Atmospheric Administration (NOAA) |  UK Hydrographic Office (UKHO) |
V. Terms and definitions
Albedo
a reflection coefficient that describes the reflecting power of a surface
Data Cube
a multi-dimensional (“n-D”) array of values. Typically used in contexts where these arrays are massively larger than the hosting computer’s main memory
FAIR Climate Service
Climate resilience information system where the entire architecture is following FAIR principles
- FAIR principles1
The approach of making digital assets Findable, Accessible, Interoperable, and Reusable.
Abbreviated terms
ArcticSDI
Arctic Spatial Data Infrastructure
ARD
Analysis Ready Dataset
AMSR
Advanced Microwave Scanning Radiometer
API
Application Programming Interface
ARD
Analysis Ready Dataset
ARDC
Analysis Ready Data Cube
ATLAS
Advanced Topographic Laser Altimeter System
C3S
Copernicus Climate Change Service
CAFF
Conservation of Arctic Flora and Fauna
CARRA
Copernicus Arctic Regional Reanalysis
CCI
Climate Change Initiative
CDR
Climate Data Record
CDS
Climate Data Store
CEOS
Committee on Earth Observation Satellites
CF
Climate and Forecast
CKAN
Comprehensive Knowledge Archive Network
CMIP
Coupled Model Intercomparison Project
COG
Cloud Optimized GeoTIFF
CRIS
Climate Resilience Information System
CSV
Comma-Separated Values
CSW
Catalog Services for the Web
CWIC
CEOS WGISS Integrated Catalog
DEM
Digital Elevation Model
DGGS
Discrete Global Grid System
DTM
Digital Terrain Model
DWG
Domain Working Group
ECMWF
European Centre for Medium-Range Weather Forecasts
ECV
Essential Climate Variable
EDR
Environmental Data Retrieval
EO
Earth Observation
EPSG
European Petroleum Survey Group
ER
Engineering Report
ERA5
fifth generation ECMWF atmospheric reanalysis of the global climate
ESA
European Space Agency
EUMETSAT
European Organisation for the Exploitation of Meteorological Satellites
FAIR
Findable, Accessible, Interoperable, Reusable
GADM
Database of Global Administrative Areas
GDAL
Geospatial Data Abstraction Library
GeoBON
Group on Earth Observations Biodiversity Observation Network
GDC
Geospatial Data Cube
GML
Geography Markup Language
GRIB
General Regularly-distributed Information in Binary form
HDF
Hierarchical Data Format
ICESAT-2
Ice, Cloud and Land Elevation Satellite
IGIF-H
Integrated Geospatial Information Framework — Hydro
IHO
International Hydrographic Organization
IoT
Internet of Things
IPCC
Intergovernmental Panel on Climate Change
IUCN
International Union for Conservation of Nature
ISO
International Organization for Standardization
JSON
JavaScript Object Notation
ML/AI
Machine Learning / Artificial Intelligence
MPA
Maritime & Port Authority
MSDI
Marine Spatial Data Infrastructure
NASA
National Aeronautics and Space Administration
NCAR
National Center for Atmospheric Research
NetCDF
Network Common Data Form
NOAA
National Oceanic and Atmospheric Administration
NRCan
Natural Resources Canada
NSIDC
National Snow & Ice Data Center
OECD
Organization of Economic Cooperation and Development
OGC
Open Geospatial Consortium
OMSv3
OGC Observations, Measurements & Samples version 3.0
OPeNDAP
Open-source Project for a Network Data Access Protocol
OSM
OpenStreetMap
PAHO
Pan American Health Organization
PAME
Protected Areas of the Marine Environment
QGIS
Quantum Geographic Information System
RCI
Regional Climate Indicator
RCM
Regional Climate Model
RCP
Representative Concentration Pathway
REST
Representational State Transfer
S3
Simple Storage Service
SDG
Sustainable Development Goal
SLA
Singapore Land Authority
STAC
SpatioTemporal Asset Catalogs
TIE
Technical Interoperability Experiments
UKHO
United Kingdom Hydrographic Office
UN-FCCC
United Nations Framework Convention on Climate Change
UN-GGIM
United Nations Committee of Experts on Global Geospatial Information Management
USGS
United States Geological Survey
WCS
Web Coverage Service
WCPS
Web Coverage Processing Service
WFS
Web Feature Service
WG Climate
Joint Working Group on Climate
WGISS
Working Group on Information Systems and Services
WMO
World Health Organization
WMS
Web Map Service
WMTS
Web Map Tile Service
WPS
Web Processing Service
XML
Extensible Markup Language
1. Introduction
The FMSDI 2023 pilot focuses on the coastal domain representing arguably the most important realm on which billions of people depend each day. Yet, as a result of climate change, marine pollution, and population growth, coastlines around the world are being transformed through habitat loss, sea level rise, and a significant increase in micro-plastics entering local food chains.
A major challenge for all stakeholders with an interest in coastal environments is quantifying the rate of change to the environment affecting dependent ecosystem services. In the Arctic, important factors include identifying the rapidly changing characteristics of sea ice, anticipating the consequences of rising temperatures, changing habitats and biodiversity loss, and predicting the rate of thaw of permafrost with its diminishing role sequestering global greenhouse gases.
For the Caribbean, recent major weather events highlight the susceptibility of this region to warming oceans. Island economies are especially dependent on the ecosystem services provided by its coastal zones while coastal erosion poses a significant threat to local populations. Coastal and marine policies designed to mitigate the effects of climate change are impacted by a lack of extensive data connecting the coastal environment with the needs of stakeholders.
Singapore connects the major shipping routes of Southeast Asia and hosts one of the world’s busiest seaports. Singapore is also one of the lowest-lying island countries with most of the island extending no more than 15m above sea level. As a result, Singapore is particularly susceptible to sea level rise, storm surge, and major coastal weather events. With a highly developed coastline, identifying the risk levels associated with coastal inundation is of the highest priority.
1.1. The role of the pilot
The FMSDI 2023 pilot is expressly designed to evaluate the key features and benefits of a standards-based approach to data discovery and application in support of stakeholders vested in the changing coastal environments of the Canadian Arctic, the Caribbean islands, and the Republic of Singapore. Of keen interest is the integration of distinct data products in a manner representing the coastal environment as a seamless transition from the ocean floor to the land surface. This transitional realm has its own unique organization and function as host to critical habitat and/or essential ecosystem services serving the needs of coastal communities.
One of the compelling challenges of this work is to overcome the disparity between marine and terrestrial data systems and define a digital twin representation of the coastal environment improving the ‘time to decision’ for stakeholders.
The FMSDI 2023 project required each participant to create persistent demonstrators. These demonstrators are essentially workflows and applications that can be accessed by stakeholders for outreach, testing, and experimentation purposes and made available until December 2024. Each persistent demonstrator resulting from this pilot has unique characteristics. Some demonstrate how geospatial data and information can be used in an operational context, while others showcase what is currently possible and what gaps exist with the resources that can be discovered on the internet. The demonstrators include various data sources, metadata, access processes to online data, and various standards used for data discovery, access, and processing interfaces. Due to the different solution platforms of each participant, various approaches were made available for review by stakeholders. Issues such as security (authentication and authorization) are unique to each participant and details are provided through outreach to stakeholders and participant contacts.
2. Thread 1: Digital Twin of Land & Sea — Singapore
Singapore is an island-country with an industrialized coastline of roughly 131km with no point more than 15km from the coast. As a result, Singapore is extremely vulnerable to severe coastal events and, as such, maintains an extensive system of land-use and observation networks.
The Singapore Land Authority (SLA) is responsible for the effective use of land resources in support of the economic and social development of Singapore. As the gatekeeper of Singapore’s land use, SLA focuses on the following three core principles.
Developmental — the optimization of state land and properties
Regulatory — registration and management of land and property transactions as a guarantor of all property rights
Geospatial — development of the geospatial management strategy
Underpinning the core principles, the Survey & Geomatics Division is charged to uphold the national geospatial infrastructure for Singapore. The survey division maintains the national coordinate reference system and underlying control points while providing the GNSS Continuously Operating Reference System (CORS) infrastructure for positioning services.
Singapore’s Maritime & Port Authority (MPA) acts as the central agency responsible for assuring the operational efficiencies of Singapore as a premier global port of call. Additionally, the Singapore MPA safeguards Singapore’s strategic maritime interests with representation within the International Hydrographic Office (IHO) and the International Maritime Office (IMO). To facilitate these operational and strategic interests, MPA maintains Singapore’s national MSDI platform — GeoSpace-sea — a single integrated platform providing seamless access to authoritative marine and coastal spatial data products. The platform serves the needs of a diverse set of stakeholders ranging from the sea port operations, shipping and navigation, marine biodiversity, submarine infrastructure, and waterfront use, including recreation and tourism.
Aside from the operational requirements for SLA and MPA, integration of the terrestrial, maritime, and cadastral data products is a priority for Singapore in its role within the United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM). The development of a digital twin modeling Singapore’s coastal area is integral to Singapore’s commitment to meeting the UN’s Sustainable Development Goals (SDG). Singapore is in a unique situation balancing the needs of continued economic development with the social and environmental constraints addressing food security, biodiversity protection, and a transition to clean energy. By integrating the national mapping, hydrographic surveys, and cadastral rights database with advanced systems and technologies, Singapore is well on its way to meet its strategic plan “Limited Land — Unlimited Space”.
Key to this strategy is its investment in developing the vertical space below and above its land surface. Changes to the State Lands Act and Land Acquisition Act allow for the development of industrial spaces 30m below ground level (“Clarification of extent of underground ownership”). This change requires SLA to move from a 2D Cadastre model of its land registry to a 3D Cadastre model using the Singapore Height Datum (SHD) as its base vertical reference.
Integration between Land & Sea — Vertical Datum Relationships
The Singapore Height Datum is derived from the localized Mean Sea Level calibrated against a tide gauge previously located at Singapore’s Victoria Dock [1935-1937].
Figure 2 — Victoria Dock, Singapore - circa 1935
This vertical datum is the baseline for Singapore’s extensive precise levelling network and provides a common reference point for integration with Singapore’s bathymetric profile. Singapore’s multi-beam bathymetric surveys are based off the Admiralty Chart Datum which is offset from the Singapore Height Datum by a fixed vertical distance of ~1.56m. As a result, the bathymetry data product provided by MPA is adjusted by this vertical distance to align with the SLA provided terrain model.
A detailed review of the datum relationships and issues encountered processing the SLA terrain model is provided in Annex A.
2.1. Contributions
The following table summarizes the contributions of each Participant. Details for each contribution are provided in subsequent sections.
Table 1 — Singapore Theme Participant Contributions
| Organization | Deliverable | Scenario |
|---|---|---|
| Wuhan University | D111 | Analysis-Ready Datasets for Predictive Visualization of Storm Surge Events |
| Geomatys | D112 | A Digital Twin framework for Advanced Visualization of Storm Surge Events |
| Ecere | D113 | Modelling Storm Surge via a Multi-dimensional Geospatial Data Cube |
| Compusult | D114 | Flood Modelling & Emergency Preparedness |
2.1.1. D111: Analysis-Ready Datasets for Predictive Visualization of Storm Surge Events
The ongoing escalation of global climate change presents a significant challenge for Singapore, a coastal city-state surrounded by the sea on all sides. Greenhouse gas emissions are causing global warming, polar ice melting, and sea-level rise at an accelerated pace. Frequent extreme weather events, such as hurricanes and storms, further intensify the risk of coastal erosion. Consequently, there is a need to rely on sensor data and spatial analysis techniques to effectively assess potential risks and implement mitigation measures.
Background
Wuhan University (WHU) plays a role in researching and teaching all aspects of surveying and mapping, remote sensing, photogrammetry, and geospatial information sciences in China. The School of Remote Sensing and Information Engineering, WHU, is a university research center dedicated to developing standard-based geospatial information technology for applications in Earth science with a focus on geospatial interoperability, geoprocessing, disaster responses, and Machine Learning.
This project demonstrator extends previous work products integrating heterogeneous EO data for flood warning and impact assessment in storm analysis in Hainan Province, China. An assessment client that covers data discovery, integration, processing, and visualization is configured for the Singapore use-case. Refined models and methods are used for developing a demonstration client focusing on the analysis and visualization of storm surge data, addressing potential risks and assessing the impact of storm events.
2.1.1.1. Approach
The focus of this work product involves the following three major deliverables.
Integration of DTM and Marine Depth Data
The first goal of this project involves integrating the digital terrain model for the research area in Singapore with marine depth data to establish a consistent elevation reference.
Data Integration and Management with GeoDataCube
The second goal is to consolidate and manage data from various sources effectively. This will be achieved by utilizing the GeoDataCube framework to ensure data synergy and maintainability.
Simulation of Sea-Level Rise
In the final goal, a flood model simulation tool is used to explore the potential range of coastal inundation resulting from sea-level rise. This step provides stakeholders with a view towards mitigating the challenges posed by rising sea levels.
The solution aims to provide a visual reference tool for coastal regions facing challenges from rising sea levels and coastal inundation due to global warming, natural disasters, and related factors. These organizations are eager to gain a clear understanding of the potential impacts on their communities, infrastructure, and residents as sea levels gradually rise and encroach upon critical infrastructure. The solution addresses this need by transforming complex data into intuitive visualizations, enabling users to vividly comprehend the potential scenarios that may unfold.
Against this background, the demonstrator platform is used to analyze various data related to sea level rise. The potential impact areas under different sea level rise scenarios are based on appropriate models and used to visualize coastal inundation providing decision-makers with a better understanding of possible consequences and challenges with appropriate measures to mitigate risk.
2.1.1.2. Solution Architecture
The project solution is based on the WHU implementation of the OGC GeoDataCube model extended to achieve the seamless integration of multi-dimensional datasets. The GeoDataCube framework represents the central data repository populated using an integration pipeline to successfully load and transform data from multiple sources, ensuring the unified management and analysis of data.
The WHU GeoDataCube schema comprises four fundamental dimensions: product, space, time, and variables. Within the product dimension, essential information is provided for each dataset, including the product name, data type, sensor, and satellite platform. Product names act as the primary data identifiers, usually combining data source and product type, while data types distinguish between raster and vector data. The spatial dimension employs a series of rule-based grids to precisely describe spatial location information, guaranteeing accurate geospatial referencing of the data. The temporal dimension encompasses the data acquisition time and the employed time standards, supporting the meticulous management and analysis of time-series data. The variable dimension directs attention to the granularity of raster data, facilitating the specific description of various variable attributes within remote sensing imagery, such as rainfall, temperature, and wind speed.