The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea

Arctic environments are changing rapidly. To assess climate change impacts and guide conservation, there is a need to effectively monitor areas of high biodiversity that are difficult to access, such as the deep sea. Greenland (Kalaallit Nunaat), like many remote countries with large deep-sea exclusive economic zones (EEZs), lacks consistent access to the funding and logistics required to maintain advanced and expensive technologies for seafloor exploration. To fill this need, video and camera imaging technologies have been adapted to suit the unique requirements of Arctic environments and the social and economic needs of Greenland. Since 2015, a benthic monitoring program carried out by the Greenland Institute of Natural Resources (GINR) has provided the only large-scale, comprehensive survey in this region, including collection and analysis of photos and GoPro video footage recorded as deep as 1,600 m (Blicher, and Arboe, 2021). In line with the “collect once, use many times” principle, GINR is exploring the versatility of these data, which were originally designated for monitoring and evidence-based management. A potential research avenue for these data is polar blue carbon—the carbon stored and sequestered in ocean habitats—including benthic communities that either live on the seafloor (such as corals and sponges) or are transported there by ocean currents (such as algal detritus). This paper outlines Greenland’s affordable deep-sea technology, based on a towed camera system (Yesson, 2023), and its potential application to rapid, standardized artificial intelligence (AI)-based analysis.

Publication Details

Journal
UCL Discovery (University College London)
Published
2025-04-01
Primary Topic
Spectroscopy and Chemometric Analyses
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article

The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea

UCL Discovery (University College London)
Spectroscopy and Chemometric Analyses
article

The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea

article en

Abstract

Arctic environments are changing rapidly. To assess climate change impacts and guide conservation, there is a need to effectively monitor areas of high biodiversity that are difficult to access, such as the deep sea. Greenland (Kalaallit Nunaat), like many remote countries with large deep-sea exclusive economic zones (EEZs), lacks consistent access to the funding and logistics required to maintain advanced and expensive technologies for seafloor exploration. To fill this need, video and camera imaging technologies have been adapted to suit the unique requirements of Arctic environments and the social and economic needs of Greenland. Since 2015, a benthic monitoring program carried out by the Greenland Institute of Natural Resources (GINR) has provided the only large-scale, comprehensive survey in this region, including collection and analysis of photos and GoPro video footage recorded as deep as 1,600 m (Blicher, and Arboe, 2021). In line with the “collect once, use many times” principle, GINR is exploring the versatility of these data, which were originally designated for monitoring and evidence-based management. A potential research avenue for these data is polar blue carbon—the carbon stored and sequestered in ocean habitats—including benthic communities that either live on the seafloor (such as corals and sponges) or are transported there by ocean currents (such as algal detritus). This paper outlines Greenland’s affordable deep-sea technology, based on a towed camera system (Yesson, 2023), and its potential application to rapid, standardized artificial intelligence (AI)-based analysis.

UCL Discovery (University College London)
Openalex Percentile: Top 50%
Spectroscopy and Chemometric Analyses
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The Potential of Low-Tech Tools and Artificial Intelligence for Monitoring Blue Carbon in Greenland’s Deep Sea · UCL Discovery (University College London) (2025) | TGRS Research Map | TGRS