Articles | Volume 15, issue 6
https://doi.org/10.5194/bg-15-1663-2018
https://doi.org/10.5194/bg-15-1663-2018
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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Cited articles

Åkerman, H. J. and Johansson, M.: Thawing permafrost and thicker active layers in sub-arctic Sweden, Permafrost Periglac., 19, 279–292, https://doi.org/10.1002/ppp.626, 2008.
Andersson, J.: Assessing the ecosystem carbon storage in two subarctic areas – Phytomass and soil organic carbon stock at Abisko in Sweden and Utsjoki in Finland, Master Thesis, 22 January 2016, Stockholm University, Stockholm, 2016.
ArcticDEM: ArcticDEM, available at: https://www.pgc.umn.edu/data/arcticdem/ (last access: 12 March 2018), 2017.
Bartsch, A., Widhalm, B., Kuhry, P., Hugelius, G., Palmtag, J., and Siewert, M. B.: Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?, Biogeosciences, 13, 5453–5470, https://doi.org/10.5194/bg-13-5453-2016, 2016.
Baughman, C. A., Mann, D. H., Verbyla, D. L., and Kunz, M. L.: Soil surface organic layers in Arctic Alaska: Spatial distribution, rates of formation, and microclimatic effects, J. Geophys. Res.-Biogeo., 120, 1150–1164, https://doi.org/10.1002/2015JG002983, 2015.
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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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