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Articles | Volume 15, issue 6
Articles | Volume 15, issue 6
https://doi.org/10.5194/bg-15-1663-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/bg-15-1663-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 6
Research article
 | 
21 Mar 2018
Research article |  | 21 Mar 2018

High-resolution digital mapping of soil organic carbon in permafrost terrain using machine learning: a case study in a sub-Arctic peatland environment

Matthias B. Siewert

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Short summary
Large amounts of soil organic carbon are stored in the circumpolar permafrost region. This article aims to improve how we map this carbon. Typically the amount of soil organic carbon is estimated using soil or land cover maps. Here the amount of carbon is modeled using machine learning. This is done at a very fine spatial resolution of 1 × 1 m. This reveals a lot of small-scale landscape variability and underlines the importance of permafrost-related landforms vulnerable to a warming climate.
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Changing Permafrost in the Arctic and its Global Effects in...
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