The Blue Oil that will Fuel the Digital Hydrospace

Geospatial data, information, and technologies have progressed tremendously since the first location-based data were acquired and products like maps and charts were produced.

In an increasingly digital hydrospace, which covers approximately 71% of the Earth’s surface, there are expectations for improved efficiency, safety, and sustainability from marine stakeholders and the blue economy. Hydrospatial data will be the ‘blue oil’ that will fuel digital maritime space and meet expectations.

Discovery and Data

We are in the middle of an important decade for the sustainability of our planet and the vital role the water domain plays in achieving our sustainable development goals and targets is not lost. A primary objective for exploration and discovery is data collection, and with advancing technologies, the acquisition of hydrospatial data is growing.

Referred to as “the last great mapping endeavour of our planet”, the Nippon Foundation-GEBCO Seabed 2030 Project which aims to be the most accessible and reliable source of bathymetry data is together with the UN Decade of Ocean Science driving the modern discovery of oceans. This marine discovery mission is supported by industry initiatives, such as Fugro’s crowdsourced bathymetry program and Shell’s Ocean Discovery XPRIZE, and voluntary geographic information from initiatives such as citizen science programs.

Refining the ‘Blue Oil’ for Integration

Riding on these strong currents of attention the oceans are gaining, there are many growing demands for hydrospatial data, information, technology, and innovation within the maritime and geospatial communities.

The advantage is that we speak the common language of data and the challenge is finding common (spatial) reference points to understand each other and unlock insights. The ‘blue oil’ data collected would therefore require ‘refinement’, or in data terms, processing and standardization to be made useful products.

Already the full spectrum of the marine domain is interconnected from inland waters and waterways to the estuaries, intertidal, subtidal, and deep sea. The water cycle further expands this complex interconnectivity of the marine with the terrestrial and atmospheric ecosystems. Planet Earth is a system of systems and an integrated approach is required to address environmental challenges on the global, regional, and local scales. Similarly, there have been various waves of digitalization, from computerization to predictive big data analytics, and a common bridge to all is integration.

With the Integrated Geospatial Information Management Framework (IGIF-Hydro) and  S-100 Universal Hydrographic Data Model, and various other initiatives from the United Nations Global Geospatial Information Management Working Group on Marine Geospatial Information, the International Hydrographic Organization’s Marine Spatial Data Infrastructures, the UNESCO Intergovernmental Oceanographic Commission’s International Oceanographic Data and Information Exchange, and the Open Geospatial Consortium Marine Domain Working Group.

There has been growing emphasis and accompanying GIS technologies from the industry to enable open and FAIR (findable, accessible, interoperable, and reusable) data sharing in the diverse marine geospatial community and beyond.

There are challenges to data acquisition in both remote water resources and busy port waters due to accessibility. Rapidly evolving technologies have opened up new frontiers to study the world’s dynamic marine environments and water resources.

Advances in remote sensing technology and unmanned systems have enhanced the large-scale (near)real-time monitoring of physical oceanography, marine debris, oil spills, sea ice extent and thickness, and more. Autonomous underwater vehicles and satellite imagery, for example, can collect high-resolution coastal bathymetric data, and unmanned aerial vehicles, drones, or sensors can be used to provide real-time hydrospatial data.

One of the most significant recent trends in the geospatial world is the integration of  (Geo) Artificial Intelligence (AI) / Machine Learning (ML) and digital twin technologies into geospatial data analysis and modeling. By integrating these cutting-edge technologies, there is great potential in analyzing and training large datasets of hydrospatial data, such as temperature, salinity, tidal currents, biodiversity, and ships, for forecasting and monitoring in marine space.

Today, the marine community is already making headway in these technological integrations. For instance, open-access AI platforms like ReefCloud which has enabled the rapid identification of organisms from benthic photographs. Similarly, GeoAI could be used to detect “ghost fishing ships” or “dark ships” whose…