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. 2019 Mar 12;6:190037.
doi: 10.1038/sdata.2019.37.

Circumpolar Permafrost Maps and Geohazard Indices for Near-Future Infrastructure Risk Assessments

Free PMC article

Circumpolar Permafrost Maps and Geohazard Indices for Near-Future Infrastructure Risk Assessments

Olli Karjalainen et al. Sci Data. .
Free PMC article


Ongoing climate change is causing fundamental changes in the Arctic, some of which can be hazardous to nature and human activity. In the context of Earth surface systems, warming climate may lead to rising ground temperatures and thaw of permafrost. This Data Descriptor presents circumpolar permafrost maps and geohazard indices depicting zones of varying potential for development of hazards related to near-surface permafrost degradation, such as ground subsidence. Statistical models were used to predict ground temperature and the thickness of the seasonally thawed (active) layer using geospatial data on environmental conditions at 30 arc-second resolution. These predictions, together with data on factors (ground ice content, soil grain size and slope gradient) affecting permafrost stability, were used to formulate geohazard indices. Using climate-forcing scenarios (Representative Concentration Pathways 2.6, 4.5 and 8.5), permafrost extent and hazard potential were projected for the 2041-2060 and 2061-2080 time periods. The resulting data (seven permafrost and 24 geohazard maps) are relevant to near-future infrastructure risk assessments and for targeting localized geohazard analyses.

Conflict of interest statement

The authors declare no competing interests.


Figure 1
Figure 1. Schematic depiction of modelling data, model calibration and evaluation, and resulting data layers employed in this study.
Observational data on mean annual ground temperature (MAGT) and active layer thickness (ALT), together with geospatial data, were used to calibrate statistical models using generalized linear models (GLM), generalized additive models (GAM), random forest (RF) and generalized boosted models (GBM). The modelling outputs were predictions of MAGT and ALT in current conditions and a derived map for suitable conditions for permafrost (i.e., predicted MAGT ≤ 0 °C). Models were evaluated with a distance-blocked cross-validation scheme that accounted for spatial autocorrelation, and with past MAGT and ALT observations. Three emission trajectories (RCPs = representative concentration pathways) were implemented to simulate MAGT and ALT under future conditions. Finally, additional geospatial predictors affecting local hazard potential were used with MAGT and ALT predictions to formulate geohazard indices.
Figure 2
Figure 2. Mean annual ground temperature (MAGT, n = 797, black symbols) and ALT observation sites (active layer thickness, n = 303, white symbols) in the Northern Hemisphere north of 30°N.
Modelled extent of near-surface permafrost occurrence, (predicted MAGT ≤ 0 °C), undifferentiated by continuity zone is shown for the present (2000–2014) and future (2041–2060 and 2061–2080) periods under a moderate climate-forcing scenario RCP4.5 (representative concentration pathways). In certain areas, especially in northwestern Russia, thaw of near-surface permafrost is projected to progress rapidly between the two future periods (dark blue zone), whereas in many other locations the change is minimal owing to, for example, the altitudinal cooling effect of a topographical barrier. World Borders dataset is distributed under CC BY-SA 3.0 license ( on
Figure 3
Figure 3. Geohazard indices in an orthographic projection showing near-surface permafrost degradation related risks to infrastructure.
Displayed here, in a moderate Representative Concentration Pathway (RCP) 4.5 scenario for 2041-2060 and 2061–2080, are settlement index Is (a,b, refs,), risk zonation index Ir (c,d, ref.), AHP (analytic hierarchy process based index) Ia (e,f) and consensus of the three Ic (g,h). Each index consists of three mutually exclusive classes delimiting areas of low, moderate and high hazard potential. World Borders dataset is distributed under CC BY-SA 3.0 license ( on

Dataset use reported in

  • Sci Data. doi: 10.1038/s41467-018-07557-4

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