Understanding TID
This StoryMap explores the concept of the GEBCO Type Identifier (TID), why it exists and how it is used
The GEBCO Grid
Founded in 1903, and operating under the joint auspicies of the International Hydrographic Organization (IHO) and the Intergovernmental Oceanographic Commission (IOC) of UNESCO , the General Bathymetric Chart of the Oceans (GEBCO) provides authoritative, publicly available information on bathymetric (depth) data sets of the world ocean.
GEBCO's main product is the GEBCO grid. Publicly available for everyone in the world to see and download , the GEBCO grid is a global terrain model for ocean and land, providing elevation data, in meters, on a 15 arc-second interval grid. [In this StoryMap, we will focus on the ocean (bathymetry) of the GEBCO grid]
GEBCO 2023 Bathymetry
Creating this bathymetric product is not easy, as many different types of data have to come together in the most harmonious and seamless way possible to create the world ocean map that we all love. Underneath the GEBCO Ocean Map are many different types of data , contributed by countless organizations and individuals around the world. The GEBCO Grid is a combination of direct and indirect seafloor depth measurements.
On the left, this slider shows the bathymetry of the 2023 GEBCO grid, while on the right, we see all the different types of data underneath the GEBCO grid represented with different colors. As shown in the legend, each color corresponds to a number that represents a different type of data. These numbers and what they mean are explained below, in the " Type Identifier (TID) " section of the StoryMap.
In this StoryMap we will learn the differences between mapped and unmapped, how the GEBCO Ocean map is created, the different types of data that are used to create this product, how everything is organized using a code called Type Identifier (TID) and why this code is important.
Mapped Vs. Unmapped
When visualizing the world map, we may look at the ocean and think that it is mapped to its entirety.
Especially when we zoom in and detailed areas of the ocean floor are revealed, like this area of the Mid-Atlantic Ridge.
However, we know that the ocean is not mapped to its entirety since, as we get even closer into the map, we can see how some areas remain very detailed, yet others look very blurry.
These are the differences between mapped and unmapped.
Mapped: Based on direct depth measurements, these are areas that would show us characteristics of the ocean floor to the greatest detail and accuracy.
With this type of visualization is easier to identify these type of measurements.
This is the same map as before, but now unmapped portions of the ocean are covered in black, which allows for mapped portions of the ocean to be highlighted.
Unmapped: Never measured before or based on indirect depth measurements, like interpolation or prediction, these are areas that even though they give a rough idea on what the ocean floor looks like, it is not to the greatest detail or with the most accuracy. Therefore, the reason why, as we get closer, it looks blurred out.
Now with this slider you can see for yourself the differences between mapped and unmapped in the GEBCO bathymetric grid.
Turns out that, as of 2023, only ~25% of the ocean floor is mapped to modern standards.
Similar to the previous example, the interactive map below shows the areas that are based on direct measurement (mapped) with color, versus the areas that are based on indirect measurements (unmapped) in black, giving us a visual idea on how much has been mapped so far, and how much more work needs to be done to complete our world ocean map.
Seabed 2030
The Nippon Foundation - GEBCO Seabed 2030 Project is a collaborative project to inspire the complete mapping of the world’s ocean by 2030, and to compile all bathymetric data into the freely-available GEBCO Ocean Map.
Seabed 2030 aspires to empower the world to make policy decisions, use the ocean sustainably, and undertake scientific research that is informed by a detailed understanding of the global ocean floor.
Types of Data
Within the framework of Seabed 2030, a portion of the ocean is considered mapped if it is based on direct depth measurements.
Here, for example, this map shows areas of the Caribbean Region that are considered mapped.
However, just by looking at it with the naked eye, we can't tell which types of direct depth measurements support this grid.
Multibeam
Most of this grid is mapped with Multibeam data. Collected using multibeam echosounders and being able to record measurements from the deepest parts of the world ocean, multibeam sonar is one of the most efficient ways of mapping the deep sea. Learn More.
Singlebeam
However, there are other types of direct depth measurements that contribute significantly in our effort of mapping the world ocean.
Part of this region is also based on Singlebeam data. Despite the narrow trackline of data acquired with singlebeam sonars, they can contribute significant new information about the shape of our seafloor. Learn More.
Seismic
Seismic data is the principal geophysical method used to image the subsurface in both land and marine environments. Seafloor depth data can also be derived from seismic data, and can reveal amazing features of the seafloor, like the ones present in this area of the Gulf of Mexico that was mapped with 3D seismic imaging .
ENC Soundings
Soundings extracted from Electronic Nautical Charts (ENCs), though sparse, also contribute important information about the seafloor that is used in the GEBCO grid. This type of data can be difficult to visualize at first, however, each sounding provides a reliable measure on the depth of our seafloor and contributes significantly to the global effort. Learn More
Satellite Derived Bathymetry (SDB)
Optical techniques can also be used to measure bathymetry in areas where the water is shallow and clear. In this example, Satellite Derived Bathymetry (SDB) reveals the details of the seafloor surrounding the Bahamas. Learn More.
LiDAR
LiDAR, or Light Detection and Ranging, data is another optical technique used to measure depth in shallow clear water, like these areas around islands in the Easter Caribbean. Learn More
Within the framework of Seabed 2030, a portion of the ocean based on indirect depth measurements is considered unmapped. Predicted bathymetry in the GEBCO grid is derived from satellite altimetry data, which measures fluctuations in sea surface height due to the gravity effects of underwater topography. Interpolated bathymetry indicates areas where the distance between measurements is greater than the resolution of the GEBCO grid.
The variable resolution, quality and data density of these different data types is important to consider when assembling the GEBCO grid. Distinguishing between direct and indirect depth measurements helps identify which portions of the ocean have yet to be mapped.
Lidar data (far left); Singlebeam collection (middle left); ENC Chart (middle right); Multibeam collection (far right)
Type Identifier (TID)
The Type Identifier (TID) grid accompanies the GEBCO grid and helps users of the data product understand which grid cells are supported by which data type, and helps distinguish direct from indirect measurements.
The following table describes the format and coding of the TID grid for the direct depth measurement examples we saw in the previous section.
The GEBCO grid also has TID codings and formats for indirect depth measurements as follows:
GEBCO TID Grid
The TID grid allows us to see which type of data was used to populate each cell of the GEBCO grid. In this example, we can see both the seabed depth in the Caribbean, and we can swipe the slide bar to see the types of data sources that were assembled [See Legend].
How TID is Important to Data Contribution
If a grid is contributed to the Seabed 2030 Project that includes large areas of interpolation or predicted bathymetry, a TID Grid is important for data assembly. This not only helps us distinguish mapped from unmapped areas in the global grid, but it impacts how well we can integrate data from multiple contributors.
There are a variety of ways the Seabed 2030 Regional Centers can assemble precise TID information, and here we present several examples.
Example 1: No TID information supplied
In 2021, the team at the Atlantic and Indian Oceans Regional Center (AIORC) of the Seabed 2030 Project downloaded , from Marine Geoscience Data System (MGDS) , a gridded dataset corresponding to the Central Indian Ridge. Generated from swath data collected in May - July 2001 aboard ORV Sagar Kanya during cruise SK165, visualization of these grids clearly reveals interpolated areas surrounding the multibeam data.
The following swipe shows part of the original grids as they were downloaded compared with the same grids after the team manually removed the interpolated data from the grids. While this was a relatively quick solution based on the nature of the data in the grid, doing this manually for more complex surveys would be extremely time consuming.
In this grid, warmer colors like red and orange represent shallower waters, while darker colors like green and blue represent deeper waters.
Example 2: Assembling TID based on sounding locations
A Digital Elevation Model (DEM) of the seafloor within and around Brazil’s EEZ was contributed by the Directorate of Hydrography and Navigation of the Brazilian Navy. The contribution was accompanied by an image showing the extent of multiple data types that were assembled to create the DEM.
A TID was necessary to help identify which grid nodes were sourced from each data type. After some discussion and reaching a mutual agreement, the Directorate of Hydrography and Navigation of the Brazilian Navy provided XY points (Lat/Lon), with no depth measurement, to help us identify the TID for each grid cell.
This mutually agreed solution resulted in:
- Precise identification of areas that have been mapped in a way that is fully consistent with Seabed 2030’s depth-dependent data density goals
- Brazilian-control of resolution of gridded data products within their EEZ
The following swipe shows Brazil's original DEM compared with the TID Grid generated by the AIORC team showing the different data types that supported the DEM.
Brazil's DEM limited to their EEZ (left); Corresponding TID of Brazil's DEM (right). Data types used in the DEM include singlebeam, multibeam, seismic, ENC soundings and predicted bathymetry.
Example 3: Using shapefiles to characterize TID
In early 2023, the AIORC team received information about a publicly available 3D Bathymetric Map corresponding to Uruguay's EEZ. Upon download and visualization of said product, it was evident that it would be a valuable addition to the GEBCO Ocean Map. However, the accompanying paper explained how this map was created using different types of available bathymetric data, including multibeam and seismic data.
Bathymetric Map of Uruguay's offshore
Identification of the different data types used was necessary in order to do the appropiate integration of the product into the GEBCO Ocean Map. Therefore, the AIORC Team initiated contact with the authors of the paper corresponding to this Bathymetric map: The National Administration of Fuels, Alcohols and Portland or Uruguay (ANCAP). After discussions and reaching a mutual agreement, ANCAP agreed to share the shapefiles of each data type used to create the bathymetric map.
Although simple, this type of additional information was enough for the team to identify which areas of the bathymetric map were supported by direct measurements versus indirect measurements.
3D Bathymetric Map as it was downloaded (left); TID of 3D Bathymetric map (right)
Conclusion
The TID is a crucial element for the assembly and integration of different data types into the GEBCO Ocean Map. As we have seen, there are a variety of approaches that can be taken to accomplish a TID, and this effort is not meant to be taxing on the contributor. The Regional Data Centers for the Seabed 2030 Project are always open to work with contributors and stakeholders in order to make the documentation and submission process as easy as possible.
Join the global movement! GEBCO Data Contribution Form
