TCarta Marine, a global provider of hydrospatial products and services, has expanded its role in the Seabed 2030 Ocean Survey project that seeks to map the entire ocean floor by 2030. Having already directly contributed extensive, satellite-derived bathymetry (SDB) to the endeavor, TCarta has developed capacity building initiatives to train international hydrographic offices in creating their own SDB data sets for Seabed 2030 and other applications.
Seabed 2030 was launched by The Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans program (GEBCO) to produce a publicly accessible bathymetric data set of the seafloor. The project is officially endorsed by the UN Decade of Ocean Science for Sustainable Development.
As a Seabed 2030 partner, TCarta has contributed 150,000 square kilometers of 10-meter resolution seafloor depth measurements from its Global Satellite Derived Bathymetry (G-SDB) product line. The contributed data sets include the Red Sea in the Middle East and Caribbean coastal zones of Belize and Turks and Caicos.
TCarta has taken its Seabed 2030 participation a step further by developing capacity building training programs to instruct international hydrographic offices in the production of SDB data for their coastlines. TCarta personnel completed training with the Mexican Hydrographic Office in 2022. The firm will begin a similar instructional program in Jamaica this year with an export grant from the State of Colorado.
The capacity building sessions train participants in the use of TCarta’s Trident (SDB) Toolbox, a series of software applications that operate within Esri ArcPro to extract bathymetric measurements from satellite, aerial and UAV imagery using Machine Learning (ML) and satellite-based LiDAR technology. The generated G-SDB data contain bathymetric measurements to depths of more than 30 meters, depending on water clarity, at 10-meter resolution.
“Seabed 2030 is making these bathymetric data sets available for coastal resilience, environmental protection, and other important applications outside of traditional nautical charting,” said TCarta president, Kyle Goodrich.
“In 2022, TCarta provided high-resolution bathymetric coverage of areas where little to no data was previously accessible to the public,” said Hayley Caitlin Drennon of the Lamont-Doherty Earth Observatory. “The data collected in the Caribbean and Indian Ocean provides first-order information of the seafloor surrounding coastal communities most at risk for sea level rise. The importance of their work was immediately seen in a partner project, Monaco Explorations, which utilized data collected by TCarta around Mauritius and Seychelles in its 2022 Indian Ocean Mission to fulfill their goals of protecting the biology of the region, while also employing new exploration techniques. Starting with Mesoamerica, our goal is to empower smaller nations to create their own high-quality bathymetric products for the protection and sustainable development of their coastal resources. They are free to contribute the derived data sets to Seabed 2030 and to incorporate them into their own projects.”
With offices in the United States, Jamaica, and Canada, TCarta has built an international business on cost-effectively and safely deriving onshore and offshore data sets using multispectral imagery captured by Earth observation satellites – without negative impact on the natural habitat. TCarta products and services are relied upon by governmental, insurance, oil & gas, environmental, and infrastructure development clients in applications as diverse as natural resource monitoring, tsunami modeling, disaster & hazard response, and hydrologic studies. The TCarta product lines include high-resolution satellite-derived water depth and seafloor map products as well as 90- and 30-meter GIS-ready bathymetric data aggregated from numerous information sources. TCarta has also recently unveiled the use of ICESat-2 LiDAR data sets for use in SDB validation, and the TCarta Global Satellite Derived Bathymetry (G-SDB) off-the-shelf products. G-SDB is generated with Machine Learning and ICESat-2 laser data at 10m resolution to depths of 30m depending on water clarity.
