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Cited by 247Climate change and permafrostRemote Sensing in AgricultureRemote-Sensing Image Classification

A raster version of the Circumpolar Arctic Vegetation Map (CAVM)

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Raynolds, Martha K., Walker, Donald A., Balser, Andrew, Bay, Christian, Campbell, Mitch, Cherosov, Mikhail M., Daniëls, Fred J.A., Eidesen, Pernille Bronken +21 more·2019·Remote Sensing of Environment
DOI 10.1016/j.rse.2019.111297
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Abstract

Land cover maps are the basic data layer required for understanding and modeling ecological patterns and processes. The Circumpolar Arctic Vegetation Map (CAVM), produced in 2003, has been widely used as a base map for studies in the arctic tundra biome. However, the relatively coarse resolution and vector format of the map were not compatible with many other data sets. We present a new version of the CAVM, building on the strengths of the original map, while providing a finer spatial resolution, raster format, and improved mapping. The Raster CAVM uses the legend, extent and projection of the original CAVM. The legend has 16 vegetation types, glacier, saline water, freshwater, and non-arctic land. The Raster CAVM divides the original rock-water-vegetation complex map unit that mapped the Canadian Shield into two map units, distinguishing between areas with lichen- and shrub-dominated vegetation. In contrast to the original hand-drawn CAVM, the new map is based on unsupervised classifications of seventeen geographic/floristic sub-sections of the Arctic, using AVHRR and MODIS data (reflectance and NDVI) and elevation data. The units resulting from the classification were modeled to the CAVM types using a wide variety of ancillary data. The map was reviewed by experts familiar with their particular region, including many of the original authors of the CAVM from Canada, Greenland (Denmark), Iceland, Norway (including Svalbard), Russia, and the U.S. The analysis presented here summarizes the area, geographical distribution, elevation, summer temperatures, and NDVI of the map units. The greater spatial resolution of the Raster CAVM allowed more detailed mapping of water-bodies and mountainous areas. It portrays coastal-inland gradients, and better reflects the heterogeneity of vegetation type distribution than the original CAVM. Accuracy assessment of random 1-km pixels interpreted from 6 Landsat scenes showed an average of 70% accuracy, up from 39% for the original CAVM. The distribution of shrub-dominated types changed the most, with more prostrate shrub tundra mapped in mountainous areas, and less low shrub tundra in lowland areas. This improved mapping is important for quantifying existing and potential changes to land cover, a key environmental indicator for modeling and monitoring ecosystems. The final product is publicly available at www.geobotany.uaf.edu and at Mendeley Data, DOI: 10.17632/c4xj5rv6kv.1.

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  • The Arctic tundra biome encompasses a 5.1 million km2 region bounded by the Arctic Ocean to the north and the boreal forest biome to the south.

    “Earth's northernmost continental landmasses and island archipelagos are home to the Arctic tundra biome, which collectively encompasses a 5.1 million km 2 region bounded by the Arctic Ocean to the north and the boreal forest biome to the south (Raynolds et al. 2019).”

    From NOAA Arctic Report Card 2025: Tundra Greenness (2025) · cites this paper as Raynolds et al. 2019

    Section 2.1 (Map extent; page unavailable) defines the mapped Arctic by a southern treeline and a seaward coastline, supporting the claim's general boundaries. Section 3 (Results; page unavailable) gives its total area as 7.02 million km², not 5.1 million km²; it separately reports 3.24 million km² of vegetated map units. (LLM, conf=0.88)

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Research works printed but not linked: 13

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Authors
Raynolds, M. K., Walker, D. A., Balser, A., Bay, C., Campbell, M., Cherosov, M. M., Daniëls, F. J. A., Eidesen, P. B., Ermokhina, K. A., Frost, G. V., Jedrzejek, B., Jorgenson, M. T., Kennedy, B. E., Kholod, S. S., Lavrinenko, I. A., Lavrinenko, O. V., Magnússon, B., Matveyeva, N. V., Metúsalemsson, S., Nilsen, L., Olthof, I., Pospelov, I. N., Pospelova, E. B., Pouliot, D., Razzhivin, V., Schaepman-Strub, G., Šibík, J., Telyatnikov, M. Y., & Troeva, E.
Affiliations
  • University of Alaska Fairbanks (US)
  • Aarhus University (DK)
  • Siberian Branch of the Russian Academy of Sciences (RU)
  • University of Münster (DE)
  • University Centre in Svalbard (SJ)
  • Russian Academy of Sciences (RU)
  • Alaska Biological Research (United States) (US)
  • Environment and Climate Change Canada (CA)
  • Náttúrufræðistofnun (IS)
  • UiT The Arctic University of Norway (NO)
  • Natural Resources Canada (CA)
  • Slovak Academy of Sciences (SK)
  • Central Siberian Botanical Garden (RU)
Corresponding author
Raynolds, Martha K.
ORCID
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2019-10
Volume
232
Pages
111297
ISSN
0034-4257 (ISSN-L)
DOI
10.1016/j.rse.2019.111297
OpenAlex
W2957984918
Cited by
247
References
0
Citations by year
2026: 14 · 2025: 35 · 2024: 45 · 2023: 34 · 2022: 37 · 2021: 60 · 2020: 19 · 2019: 3
FWCI
11.79
Type
journal article
Language
en
Open access
Licence
Locations
  • Remote Sensing of Environment (publishedVersion, cc-by-nc-nd)
  • Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by-nc-nd)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by-nc-nd)
  • Zurich Open Repository and Archive (University of Zurich)
Funders
  • National Aeronautics and Space Administration (NNX13AM20G, NNH16CP09C)
  • Russian Foundation for Basic Research (18-04-01010 \u0410)
  • National Science Foundation (1737750, 1263854)
  • Russian Foundation for Fundamental Investigations
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Climate change and permafrost
  • Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
  • Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
Keywords
Arctic tundra vegetation, land cover mapping, vegetation types, shrub tundra, NDVI, AVHRR, MODIS, unsupervised classification, accuracy assessment, altitude, summer temperature, Canadian Shield, saline water

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